System

Abstract

To provide a system that generates a sentence reflecting the user's feeling.SOLUTION: A system includes: means for generating a prompt sentence for instructing the generation of a sentence on the basis of an input from a user; means for generating the sentence using the generated prompt sentence and a generative AI model; means for determining a transmission destination of the sentence on the basis of contents of the generated sentence; means for identifying a feeling state of the user using a feeling engine; means for generating a prompt sentence for instructing adjustment of tone of the generated sentence on the basis of the generated sentence and the feeling state of the user; means for adjusting the tone of the sentence using the generated prompt sentence and the generative AI model; and transmission means for transmitting the adjusted sentence to the determined transmission destination.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Previously, various documents for internal and external communication were created manually by each employee. However, this was a time-consuming process that reduced employee productivity. In addition, information such as deadlines, importance, and recipients was often omitted, further reducing work efficiency. [Means for solving the problem]

[0005] The present invention provides a generative AI means for generating text based on user input, a sending means for sending the text generated by the generative AI means, and a destination determination means for determining a destination based on the content of the text generated by the generative AI means. This reduces the amount of work required by each person, improves employee productivity, and prevents information such as deadlines, importance, and recipients from being overlooked. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] In one embodiment of the present invention, the generative AI uses natural language processing technology to analyze user input and generate sentences based on that. Specifically, if a user inputs, "I would like to create an email about a new product launch," the generative AI extracts the key points and generates sentences using appropriate honorifics and business terms.

[0029] "Example 2"

[0030] The sending means sends the generated text to the specified destination. Specifically, the generative AI sends the generated text to an email server, which then forwards it to the destination email address.

[0031] "Example 3"

[0032] Furthermore, the destination determination means determines the destination based on the content of the generated text. Specifically, if the text generated by the generative AI contains the phrase "announcement of a new product," the destination determination means determines to send it to the email address of the marketing department.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: A user enters a request into the system: "I want to create an email about a new product launch."

[0036] Step 2: The generative AI uses natural language processing techniques to analyze the user input and extract the key points.

[0037] Step 3: The generative AI generates sentences using appropriate honorifics and business terms based on the extracted key points.

[0038] "Example 2"

[0039] Step 1: The text generated by the generative AI is passed to the sending means.

[0040] Step 2: The sending means sends the generated text to the mail server.

[0041] Step 3: The email server forwards the generated document to the specified recipient's email address.

[0042] "Example 3"

[0043] Step 1: The text generated by the generative AI is passed to the destination determination means.

[0044] Step 2: The destination determination means determines the destination based on the content of the generated text.

[0045] Step 3: Specifically, if the phrase "announcement of new product" is included, the destination determining means determines that it should be sent to the email address of the marketing department.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0048] In conventional text generation systems, the process of properly analyzing user input, generating prompts, and generating text is complicated and difficult to perform efficiently. Furthermore, there was a lack of functionality to automatically determine the destination of the generated text, which increased the user's workload. Furthermore, there was a need to reduce work time and improve productivity by sending the generated text.

[0049] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0050] In this invention, the server includes an input means for receiving input from a user, a prompt generation means for analyzing the input from the input means and generating a prompt sentence, a generative AI means for generating a sentence using the prompt sentence generated by the prompt generation means, a transmission means for transmitting the sentence generated by the generative AI means, and a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means. This makes it possible to efficiently analyze the user's input and generate an appropriate prompt sentence to generate the sentence, and further to automatically determine the destination of the generated sentence, thereby reducing the user's effort, shortening work hours, and improving productivity.

[0051] An "input means" is a device or software for receiving input from a user.

[0052] A "prompt generation means" is a device or software that analyzes the user's input received from the input means and generates a prompt sentence to be passed to the generative AI means.

[0053] "Generative AI means" refers to a device or software that uses artificial intelligence technology to generate sentences using prompt sentences generated by a prompt generation means.

[0054] "Transmission means" refers to a device or software for transmitting text generated by the generative AI means.

[0055] The "destination determination means" is a device or software that determines the destination based on the content of the text generated by the generative AI means.

[0056] The present invention relates to a system that receives input from a user, generates a sentence based on the input, and transmits the sentence. A specific embodiment of this system will be described below.

[0057] The server has an input means for receiving input from a user. The user inputs text into an input field through a terminal. For example, the user inputs "I want to create an email about the launch of a new product."

[0058] The terminal transmits the user's input to the server. The server analyzes the received input and generates a prompt sentence using a prompt generation means. The prompt generation means analyzes the input using natural language processing technology and generates a prompt sentence to be passed to a generative AI model (e.g., GPT-4 (registered trademark)).

[0059] An example of a generated prompt is as follows:

[0060] Write an email about a new product launch. Include the following key points: new product features, release date, price, and how to purchase. Use appropriate honorifics and business terminology.

[0061] The server passes this prompt to the generative AI means, which analyzes the prompt and generates appropriate sentences based on the user's request using natural language processing techniques such as tokenization, part-of-speech tagging, and dependency analysis.

[0062] An example of a generated sentence is as follows:

[0063] Subject: New product announcement

[0064] Dear Customers,

[0065] We would like to express our sincere gratitude for your continued patronage. We are pleased to announce our new product, "XX." This product utilizes the latest technology and aims to provide a more comfortable user experience.

[0066] The release date is XX / XX, and the price is XX yen. You can purchase it on our website or at a retailer near you.

[0067] We sincerely hope for your continued patronage.

[0068] Sincerely,

[0069] The server uses a transmission means to send the generated text to the terminal. The terminal displays the received text to the user. The user can check the displayed text and make corrections or additions as necessary.

[0070] This system can efficiently analyze user input, generate appropriate prompts, and generate sentences. Furthermore, by automatically determining the destination of the generated sentences, it reduces user effort, shortens work time, and improves productivity.

[0071] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0072] Step 1:

[0073] The user provides input through the terminal.

[0074] The user inputs "I want to create an email about the launch of a new product" into the input field of the terminal. This input is written in natural language. The input data is in text format, and the terminal receives this input.

[0075] Step 2:

[0076] The device sends input to the server.

[0077] The terminal sends the user's input as an HTTP request to the server. The input data is in text format, and the server receives this request.

[0078] Step 3:

[0079] The server receives the input and generates a prompt.

[0080] The server analyzes the received input and generates a prompt using a prompt generation method. Specifically, it uses natural language processing technology to tokenize the input text and extract important keywords and phrases. Based on this, it generates a prompt to be passed to the generative AI model. For example, it generates a prompt such as, "Write an email about the launch of a new product. Include the following key points: the new product's features, release date, price, and how to purchase. Use appropriate honorifics and business terminology."

[0081] Step 4:

[0082] The server passes the prompt sentence to the generative AI model, which analyzes it and generates the sentence.

[0083] The server passes the generated prompt sentence to a generative AI model (e.g., GPT-4). The generative AI model analyzes the prompt sentence and generates an appropriate sentence based on the user's request. This analysis uses natural language processing techniques such as tokenization, part-of-speech tagging, and dependency analysis. The generated sentence is returned to the server in text format.

[0084] Step 5:

[0085] The server receives the generated text and sends it to the terminal.

[0086] The server receives the sentences generated by the generative AI model and sends them as an HTTP response to the terminal. The output data is in text format, and the terminal receives this response.

[0087] Step 6:

[0088] The terminal displays the generated text to the user.

[0089] The terminal displays the generated text received from the server to the user. The user can check the displayed text and make corrections or additions as necessary. The output data is in text format and is displayed in a format that the user can visually check.

[0090] (Application example 1)

[0091] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0092] The traditional ad copy creation process was often manual, requiring time and effort, resulting in inefficiency. Additionally, the quality of the ad copy depended on the skill of the person creating it, making it difficult to create consistent, high-quality ad copy.

[0093] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0094] In this invention, the server includes a generative AI means for generating text based on user input, a sending means for sending the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an input means for inputting information for automatically generating advertising copy, and a generation means for analyzing the information input by the input means and generating advertising copy. This automates the process of creating advertising copy, significantly reducing time and labor. It also enables consistent, high-quality advertising copy to be generated quickly.

[0095] "Generative AI methods" are artificial intelligence techniques that generate text based on user input.

[0096] "Transmission means" is a function for transmitting text generated by the generative AI means.

[0097] The "destination determination means" is a function for determining the destination based on the content of the text generated by the generative AI means.

[0098] The "input means" is a function for inputting information for automatically generating advertising copy.

[0099] The "generation means" is a function for analyzing information input by the input means and generating advertising copy.

[0100] A system for carrying out this invention is for automatically generating advertising copy based on input from a user. The system includes a generation AI means, a sending means, a destination determination means, an input means, and a generation means.

[0101] The server uses the OpenAI (registered trademark) API as a generative AI means. The user inputs information such as the purpose of the ad copy, the target audience, and the product features via a smartphone or computer terminal. The input means receives this information and generates a prompt text.

[0102] The generating means transmits the generated prompt text to the OpenAI API to generate advertising copy. The generated advertising copy is transmitted to the user by the transmitting means. The destination determining means determines an appropriate destination based on the content of the generated advertising copy.

[0103] As a concrete example, consider the case of generating ad copy for a new smartphone. The user enters the following information:

[0104] Product Name: New Smartphone

[0105] Target audience: Young people

[0106] Features: High-resolution camera, long battery life, stylish design

[0107] An example of a prompt generated based on this information is as follows:

[0108] Product Name: New Smartphone

[0109] Target audience: Young people

[0110] Features: High-resolution camera, long battery life, stylish design

[0111] Use this information to generate effective ad copy.

[0112] The server sends this prompt text to OpenAI's API to obtain the generated ad copy. The obtained ad copy is then sent to the user via a sending method. This automates the ad copy creation process, significantly reducing time and effort. It also enables consistent, high-quality ad copy to be generated quickly.

[0113] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0114] Step 1:

[0115] The user uses a smartphone or computer to input information such as the purpose of the ad copy, the target audience, and the product's features. The input information is sent to the server. The input data includes the product name, target audience, and features.

[0116] Step 2:

[0117] The server analyzes the received input data and generates a prompt. Specifically, it creates a prompt for generating advertising copy based on the input product name, target audience, and features. The generated prompt will have the following format:

[0118] Product Name: New Smartphone

[0119] Target audience: Young people

[0120] Features: High-resolution camera, long battery life, stylish design

[0121] Use this information to generate effective ad copy.

[0122] Step 3:

[0123] The server sends the generated prompt text to OpenAI's API, which generates ad copy based on the prompt text. The input data is the prompt text, and the output data is the generated ad copy.

[0124] Step 4:

[0125] The server receives the ad copy returned from the OpenAI API. The received ad copy is temporarily stored on the server.

[0126] Step 5:

[0127] The server determines the destination based on the content of the generated advertisement copy. The destination determination means analyzes the content of the advertisement copy and selects an appropriate destination. For example, if the advertisement copy is aimed at young people, a platform that is frequently used by young people is selected.

[0128] Step 6:

[0129] The server sends the generated advertising copy to the determined destination. The sending means converts the advertising copy into an appropriate format and sends it to the selected destination, so that the advertising copy reaches the target audience.

[0130] Step 7:

[0131] The user can check the sent ad copy and make corrections or regenerate it as necessary. If the user makes corrections, the process will be repeated from step 1.

[0132] Example 2

[0133] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0134] Conventional text generation systems require users to manually send the text they generate, which reduces work efficiency. Furthermore, the process of determining recipients and sending emails is cumbersome, placing a heavy burden on users. This creates challenges in terms of reducing work time and improving productivity.

[0135] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0136] In this invention, the server includes a generative AI means for generating text based on input from a user, a transmission means for transmitting the generated text, a means for transmitting the generated text to the server, a means for transferring the text received by the server to a mail server, and a means for the mail server to send the text to a specified destination. This allows text to be automatically generated based on a prompt text entered by a user and sent to a specified destination, thereby improving work efficiency and reducing the burden on the user.

[0137] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0138] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[0139] The "means for transmitting to the server" refers to a means for transmitting the text generated by the generative AI means to the server.

[0140] A "server" is a computer system that processes text received from a generative AI means and forwards it to a mail server.

[0141] "Means for transferring to the mail server" refers to the means by which the server transfers the received text to the mail server.

[0142] A "mail server" is a server that sends documents transferred from the server to a specified destination.

[0143] "Means for sending to the specified destination" refers to the means by which the mail server sends the text to the specified destination.

[0144] A "prompt" is an instruction that a user inputs to a generative AI means.

[0145] The present invention is a system that generates a sentence based on a prompt sentence entered by a user and automatically sends the sentence to a specified destination. A specific embodiment of this system will be described below.

[0146] First, the user inputs a prompt through the terminal interface, for example, "Please write an email introducing our new product." This prompt is an instruction for the generative AI model and determines the content of the text to be generated.

[0147] Next, the device receives the user's input and sends a prompt to the generative AI model. At this time, the device accesses the API of the generative AI model via the Internet. For example, OpenAI's GPT-4 can be used as the generative AI model.

[0148] The generative AI model analyzes the received prompt and generates an appropriate sentence, such as, "Hello, we'd like to introduce our new product. This product utilizes the latest technology and will make your daily life more convenient. Please give it a try."

[0149] The generated text is sent from the terminal to the server. The terminal sends data to the server using an HTTP request. The server connects to the mail server using the SMTP protocol to transfer the received text to the mail server and sends the text.

[0150] The mail server sends the received text to the specified destination email address. For example, if the destination is "example@example.com", the mail server will send an email containing the generated text to this address.

[0151] This system allows users to easily use generative AI models to generate text and send it to a specified destination, improving work efficiency and reducing the burden on users.

[0152] Examples of specific prompts include:

[0153] "Please create an email to introduce a new product."

[0154] Please prepare the minutes of the meeting.

[0155] Write a thank you letter to your customers.

[0156] In this way, users can create and quickly send texts that meet a variety of needs.

[0157] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0158] Step 1:

[0159] The user enters a prompt sentence through the terminal interface.

[0160] Specifically, the user opens a web browser on the device and enters "Please create an introductory email for our new product" into a dedicated input form.

[0161] Input: Prompt sentence (e.g. "Please create an email introducing our new product")

[0162] Output: The prompt statement is typed into the terminal.

[0163] Step 2:

[0164] The device receives user input and sends prompts to the generative AI model.

[0165] Specifically, the device sends an HTTP POST request to the API endpoint of the generative AI model over the Internet, which includes a prompt.

[0166] Input: prompt statement

[0167] Output: The prompt sentence is sent to the generative AI model.

[0168] Step 3:

[0169] A generative AI model analyzes the prompt and generates an appropriate sentence.

[0170] Specifically, the generative AI model analyzes the prompt and generates the sentence, "Hello, we'd like to introduce our new product. This product utilizes the latest technology and will make your daily life more convenient. Please give it a try."

[0171] Input: prompt statement

[0172] Output: Generated sentence

[0173] Step 4:

[0174] The terminal receives the generated text and sends it to the server.

[0175] Specifically, the device receives the generated text and sends an HTTP POST request to the server. This request includes the generated text.

[0176] Input: Generated sentence

[0177] Output: The generated text is sent to the server.

[0178] Step 5:

[0179] The server forwards the received text to the mail server.

[0180] Specifically, the server connects to a mail server using the SMTP protocol and sends the generated text.

[0181] Input: Generated sentence

[0182] Output: The generated text is sent to the mail server.

[0183] Step 6:

[0184] The mail server sends the message to the specified address.

[0185] Specifically, the mail server sends the received text to the specified destination email address. For example, if the destination is "example@example.com", the mail server will send an email containing the generated text to this address.

[0186] Input: Generated text, recipient's email address

[0187] Output: The generated text is sent to the specified destination.

[0188] (Application example 2)

[0189] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0190] Conventional security systems often lack the means to respond quickly and appropriately when an anomaly is detected. Furthermore, responses after an anomaly is often performed manually, which can lead to delays and human error. This reduces the reliability of security and reduces its effectiveness in situations where a rapid response is required.

[0191] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0192] In this invention, the server includes generative AI means for generating sentences based on input from a user, transmission means for transmitting the sentences generated by the generative AI means, destination determination means for determining a destination based on the content of the sentences generated by the generative AI means, anomaly detection means for acquiring data from a sensor and detecting anomalies, and warning message generation means for generating a warning message when an anomaly is detected. This makes it possible to automatically generate a warning message when an anomaly is detected and quickly send it to an appropriate destination.

[0193] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0194] The "transmission means" is a means for transmitting the text generated by the generative AI means to a specified destination.

[0195] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[0196] The "abnormality detection means" is a means for acquiring data from the sensor and detecting abnormalities.

[0197] The "warning message generating means" is a means for generating a warning message when an abnormality is detected.

[0198] A system for implementing this invention includes a generative AI means for generating text based on input from a user, a transmission means for transmitting the generated text, a destination determination means for determining a destination based on the content of the generated text, anomaly detection means for acquiring data from a sensor and detecting anomalies, and a warning message generation means for generating a warning message when an anomaly is detected.

[0199] Hardware and software used

[0200] Hardware: smartphones, security cameras, sensors

[0201] Software: Python, smtplib (email sending library), generative AI model, module for acquiring data from sensors

[0202] Data processing and calculation

[0203] 1. Data acquisition from sensors: Acquiring data in real time from sensors, for example, security cameras capturing video data.

[0204] 2. Anomaly detection: The acquired data is analyzed using anomaly detection means, and if an anomaly is detected, a flag is raised.

[0205] 3. Warning message generation: If an abnormality is detected, a warning message is generated using generative AI methods. For example, a message such as "A suspicious person has been detected. Please check immediately" can be generated.

[0206] 4. Determining destination: Based on the content of the generated warning message, the destination determination means determines the appropriate destination.

[0207] 5. Send email: The generated warning message is sent by email to the determined recipient using a sending means.

[0208] Specific examples

[0209] For example, if a security camera detects a suspicious person, the video data will be analyzed and the generative AI will generate a warning message stating, "A suspicious person has been detected. Please check immediately," and send it to a specified email address.

[0210] Prompt Sentence Examples

[0211] Analyze security camera footage and generate alert messages to be sent if a suspicious person is detected.

[0212] In this way, the present invention provides a system for quickly and appropriately responding when an abnormality is detected, thereby improving the reliability of security.

[0213] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0214] Step 1:

[0215] Acquiring data from sensors

[0216] The server receives data from sensors in real time. The input is raw data from the sensors, and the output is data converted into an analyzable format. Specifically, a security camera captures video data and sends it to the server.

[0217] Step 2:

[0218] Anomaly detection

[0219] The server analyzes the acquired data using anomaly detection means and sets a flag if an anomaly is detected. The input is the data acquired in step 1, and the output is the result of the anomaly detection (whether an anomaly was detected or not). Specifically, it analyzes the video data and detects suspicious individuals or abnormal behavior.

[0220] Step 3:

[0221] Warning message generation

[0222] If an anomaly is detected, the server generates a warning message using generative AI means. The input is the anomaly detection result and data from the sensor, and the output is the generated warning message. Specifically, it generates a message saying, "A suspicious person has been detected. Please check immediately."

[0223] Step 4:

[0224] Determining destination

[0225] The server's destination determination means determines the appropriate destination based on the content of the generated warning message. The input is the generated warning message, and the output is the determined destination address. Specifically, the content of the warning message is analyzed, and the email address of the appropriate person in charge is selected.

[0226] Step 5:

[0227] Send email

[0228] The server sends the generated warning message to the determined destination by email using a sending means. The input is the determined destination address and the generated warning message, and the output is the status of transmission completion. The specific operation is to send the email using an SMTP server.

[0229] Example 3

[0230] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0231] In conventional systems, when generating text based on information entered by a user, it was difficult to automatically determine the appropriate destination based on the content of the generated text. Furthermore, the destination of the generated text had to be determined manually, resulting in a decrease in work efficiency. Furthermore, the system lacked the functionality to automatically determine the appropriate destination when specific phrases were included, making it difficult to improve work productivity.

[0232] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0233] In this invention, the server includes a generation AI means for generating a sentence based on an input from a user, a transmission means for transmitting the sentence generated by the generation AI means, and a destination determination means for determining a destination based on the content of the sentence generated by the generation AI means. This makes it possible to automatically determine an appropriate destination based on the content of the generated sentence, thereby improving business efficiency. Furthermore, by automatically determining a destination when a specific phrase is included, business productivity can be improved.

[0234] "Generative AI means" is an artificial intelligence function that generates sentences based on input from the user.

[0235] The "transmission means" is a function for transmitting the text generated by the generation AI means.

[0236] The "destination determination means" is a function that determines the destination based on the content of the text generated by the generation AI means.

[0237] A "user" is a user who inputs a prompt sentence to the system.

[0238] A "prompt sentence" is an instruction sentence that the user inputs to the generation AI means.

[0239] The "particular phrase" is a keyword or expression that is important when analyzed by the destination determination means.

[0240] "Working time" is the time an employee spends performing work.

[0241] "Productivity" is an indicator that shows the efficiency and results of work.

[0242] This invention is a system that generates a sentence based on a prompt sentence entered by a user and automatically determines an appropriate destination depending on the content of the sentence. A specific embodiment of this system will be described below.

[0243] System configuration

[0244] The system consists of the following main components:

[0245] 1. Generation AI means

[0246] 2. Transmission Method

[0247] 3. How to determine the destination

[0248] Generation AI means

[0249] The generative AI means has the function of generating sentences based on input from a user. This function is realized using a generative AI model such as OpenAI's GPT-3 (registered trademark). When a user inputs a prompt sentence, the generative AI means generates an appropriate sentence based on the prompt sentence.

[0250] Transmission method

[0251] The sending means is a function for sending the text generated by the generating AI means. This function is realized using an email system or a messaging system. The generated text is sent to the destination determined by the destination determination means.

[0252] Destination determination method

[0253] The destination determination means has a function of analyzing the content of the text generated by the generation AI means and determining an appropriate destination. This function uses natural language processing technology to analyze the text and check whether it contains a specific phrase. For example, if the phrase "announcement of a new product" is included, the destination determination means determines that the text should be sent to the email address of the marketing department.

[0254] Specific examples

[0255] Below are some examples of prompts and their results:

[0256] Prompt Sentence Examples

[0257] "Please explain the features of your new smartphone."

[0258] Processing results

[0259] 1. The user enters a prompt statement.

[0260] 2. The generative AI means generates a sentence based on the prompt, such as:

[0261] "We're announcing a new product. The new smartphone features a modern processor, improved battery life, and a significantly improved camera."

[0262] 3. The generated text is passed to the destination determination means.

[0263] 4. The destination determination means analyzes the sentence and determines that it contains the phrase "new product announcement."

[0264] 5. The destination determination means determines that the email should be sent to the marketing department's email address.

[0265] 6. The text is sent to the destination determined by the sending method.

[0266] This system automatically sends a message generated based on a prompt entered by a user to an appropriate destination, thereby improving work efficiency and productivity. The flow of the specific process in the third embodiment will be described with reference to FIG.

[0267] Step 1:

[0268] The user enters a prompt statement.

[0269] The user accesses the system's web interface, enters "Please describe the features of your new smartphone" in the text box, and clicks the submit button.

[0270] Input: prompt statement

[0271] Output: Prompt for user input

[0272] Step 2:

[0273] The server generates sentences using a generative AI model.

[0274] The server receives the prompt sentence entered by the user and passes it to a generative AI model (e.g., GPT-3). The generative AI model generates an appropriate sentence based on the prompt sentence and returns it to the server.

[0275] Input: prompt statement

[0276] Output: Generated sentence

[0277] Step 3:

[0278] The server passes the generated text to the destination determination means.

[0279] The server receives the generated text and passes it to the destination determination means, which executes an algorithm to analyze the content of the text.

[0280] Input: Generated sentence

[0281] Output: The sentence to be analyzed

[0282] Step 4:

[0283] The destination determining means analyzes the text.

[0284] The destination determination means analyzes the generated text and checks whether it contains the phrase "new product announcement." For example, it uses natural language processing technology to tokenize the text and search for specific keywords.

[0285] Input: Text to be analyzed

[0286] Output: Analysis results (presence or absence of specific phrases)

[0287] Step 5:

[0288] The destination determination means determines the destination.

[0289] The destination determination means determines the destination based on the analysis result. For example, if the phrase "announcement of a new product" is included, the destination determination means selects the email address of the marketing department.

[0290] Input: Analysis results

[0291] Output: Determined destination

[0292] Step 6:

[0293] The server sends the text to the determined destination.

[0294] The server sends the text to the destination determined by the destination determination means, for example, to the marketing department's email address.

[0295] Input: Determined destination, generated text

[0296] Output: Email sent

[0297] (Application example 3)

[0298] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0299] In conventional text generation systems using generative AI, it is difficult to appropriately determine the destination of the generated text, and there is a lack of means to send the generated text quickly and efficiently. This has led to issues such as insufficient improvements in work efficiency and productivity.

[0300] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a generative AI means for generating a sentence based on an input from a user, a sending means for sending the sentence generated by the generative AI means, a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means, and an email sending means for sending the generated sentence by email. This makes it possible to automatically determine an appropriate destination based on the content of the generated sentence and send it by email quickly and efficiently.

[0301] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0302] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[0303] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[0304] The "email sending means" is a means for sending the generated text by email.

[0305] A system for implementing this invention includes a generative AI means for generating text based on input from a user, a sending means for sending the generated text, a destination determination means for determining a destination based on the content of the generated text, and an email sending means for sending the generated text by email.

[0306] The server uses OpenAI's GPT-3 as a generative AI method. GPT-3 generates the content of an advertising campaign based on a prompt entered by the user. For example, if a user enters the prompt "Please generate advertising copy for a new product launch," GPT-3 will generate advertising copy for the new product launch.

[0307] The generated text is temporarily stored by the sending means. Thereafter, the destination determining means analyzes the content of the generated text and determines an appropriate destination. For example, if the generated text contains the phrase "announcement of a new product," the destination determining means determines the email address of the marketing department as the destination.

[0308] The email sending means sends the generated text to the determined recipient by email using the Python smtplib library. The server connects to the SMTP server and sends the email using the appropriate authentication information.

[0309] As a concrete example, the following prompt sentence is input to the generative AI model:

[0310] "Generate advertising copy for a new product launch."

[0311] By inputting this prompt, the generative AI method can generate advertising copy for the new product launch, determine appropriate recipients based on the content of the copy, and distribute it via email, thereby enabling the content of advertising campaigns to be distributed quickly and efficiently.

[0312] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0313] Step 1:

[0314] The user inputs a prompt using a terminal. Specifically, the user inputs the prompt "Please generate advertising copy for the launch of a new product." This input is sent to the system.

[0315] Step 2:

[0316] The server uses a generative AI tool (OpenAI's GPT-3) to generate a sentence based on the prompt from the user. The input prompt is sent to GPT-3, and the generated ad copy is received. This ad copy is then passed on to the next processing step.

[0317] Step 3:

[0318] The server temporarily stores the generated copy of the advertisement by a transmission means. Specifically, the server stores the generated copy of the advertisement in a database or memory. The stored copy of the advertisement is passed to the next processing step.

[0319] Step 4:

[0320] The server uses the destination determination means to analyze the content of the generated advertisement copy and determine the appropriate destination. Specifically, it checks whether the advertisement copy contains the phrase "announcement of new product," and if so, determines the email address of the marketing department as the destination. This determined destination is passed to the next processing step.

[0321] Step 5:

[0322] The server uses the email sending mechanism to send the generated ad copy to the determined recipients by email. Specifically, it uses Python's smtplib library to connect to an SMTP server and sends the email using the appropriate authentication information. This process sends the ad copy to the marketing department.

[0323] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0324] "Example 1"

[0325] In one embodiment of the present invention, the generative AI means includes an emotion engine that recognizes a user's emotion. The emotion engine analyzes the emotion from the user's input (e.g., speech or text) and provides the results to the generative AI means. The generative AI means uses this emotion information to generate sentences that are appropriate to the user's emotion. For example, if the user feels angry, the generative AI means uses that information to generate sentences with a more polite tone.

[0326] "Example 2"

[0327] In another embodiment of the present invention, the emotion engine adjusts the tone of the sentence based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion and determines the tone of the sentence based on the analysis result. For example, if the user feels happy, the emotion engine uses that information to generate a sentence with a lighter tone.

[0328] "Example 3"

[0329] In yet another embodiment of the present invention, the emotion engine determines the destination based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion and determines the destination based on the analysis result. For example, if the user feels angry, the emotion engine uses the information to determine that the email should be sent to a department (e.g., customer service department) that may be able to resolve the issue.

[0330] The processing flow of each embodiment will be described below.

[0331] "Example 1"

[0332] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[0333] Step 2: The emotion engine analyzes the emotion from the user's input. The analysis result indicates the user's emotional state.

[0334] Step 3: The generative AI means receives the analysis results from the emotion engine and generates text based on them, in a tone that matches the user's emotions.

[0335] "Example 2"

[0336] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[0337] Step 2: The emotion engine analyzes the emotion from the user's input and determines the tone of the text based on the results.

[0338] Step 3: The generative AI receives tone information from the emotion engine and generates text based on that information. At this time, the text is generated in a tone that matches the user's emotions.

[0339] "Example 3"

[0340] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[0341] Step 2: The emotion engine analyzes the emotion from the user's input and determines the destination based on the results.

[0342] Step 3: The generative AI means receives the destination information from the emotion engine, generates a sentence based on that information, and sends it to the specified destination.

[0343] Example 1

[0344] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0345] Conventional text generation systems were unable to take the user's emotions into account when generating text based on user input, resulting in generated text that was inappropriate for the user's intentions or emotions. Furthermore, they lacked the functionality to automatically determine the destination of the generated text, requiring users to manually specify the destination. This resulted in reduced work efficiency and a lack of productivity.

[0346] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0347] In this invention, the server includes an input means for receiving input from a user, an analysis means for analyzing data from the input means, a generative AI means for generating text based on the data analyzed by the analysis means, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion analysis means for analyzing the user's emotions, and an emotion response generation means for generating text based on the emotion information analyzed by the emotion analysis means. This makes it possible to generate appropriate text taking the user's emotions into consideration and automatically determine the destination.

[0348] An "input means" is a device or software for receiving input from a user.

[0349] "Analysis means" refers to a device or software for analyzing data received from an input means.

[0350] "Generative AI means" refers to a device or software that uses artificial intelligence technology to generate text based on data analyzed by analytical means.

[0351] "Transmission means" refers to a device or software for transmitting text generated by the generative AI means.

[0352] The "destination determination means" is a device or software for determining the destination based on the content of the sentence generated by the generative AI means.

[0353] "Emotion analysis means" refers to a device or software for analyzing emotions from user input.

[0354] The "emotion correspondence generation means" is a device or software for generating sentences based on the emotion information analyzed by the emotion analysis means.

[0355] MODE FOR CARRYING OUT THE INVENTION

[0356] The present invention relates to a system that receives input from a user, generates appropriate sentences based on the input, and transmits them. A specific embodiment of this system will be described below.

[0357] server

[0358] The server functions as a platform for running generative AI. The server receives input from the user and analyzes it using natural language processing technology. Specifically, the server uses software such as Python and TENSORFLOW (registered trademark) to analyze the text entered by the user and extract its main points. For example, if a user enters, "I would like to create an email about the announcement of a new product," the server extracts the main points and generates a sentence using appropriate honorifics and business terminology.

[0359] Furthermore, the server analyzes the user's emotions using an emotion engine. The emotion engine analyzes emotions from the user's input (e.g., voice or text) and provides the results to the generative AI. The generative AI uses this emotion information to generate sentences that match the user's emotions. For example, if the user feels angry, the generative AI uses that information to generate sentences with a more polite tone.

[0360] Terminal

[0361] The terminal provides an interface for users to input data. When a user inputs text or voice data through the terminal, the data is sent to the server. The terminal converts the data entered by the user into an appropriate format and sends it to the server. For example, if a user inputs "I would like to create an email about the launch of a new product" by voice, the terminal converts the voice data into text and sends it to the server.

[0362] User

[0363] The user inputs text via their device to generate it using the generative AI. For example, if the user inputs "I want to create an email about a new product launch," the input is sent to the server via their device. The user can review the generated text and make corrections as necessary. If the input contains the user's emotions, the emotion engine analyzes them and provides them to the generative AI. For example, if the user feels angry, the generative AI uses that information to generate text with a more polite tone.

[0364] Specific examples

[0365] 1. The user types into the terminal, "I want to create an email about a new product launch."

[0366] 2. The terminal converts the input into text format and sends it to the server.

[0367] 3. The server uses Python and TensorFlow to parse the input and extract key points.

[0368] 4. The server generates the following sentence using appropriate honorifics and business terms:

[0369] "Thank you for your continued support. We would like to inform you about the launch of our new product. Details are as follows."

[0370] Examples of emotion engines

[0371] 1. A user angrily types into their device, "I want to create an email about a new product launch."

[0372] 2. The device converts the speech into text and sends it to the server.

[0373] 3. The server uses an emotion engine to analyze the user's emotions and detects anger.

[0374] 4. The server provides this emotional information to a generative AI, which generates a polite sentence like this:

[0375] "Thank you for your continued support. We would like to inform you about the launch of a new product. Details are as follows. We appreciate your understanding."

[0376] In this way, the system generates appropriate sentences based on the user's input and emotions and provides them to the user.

[0377] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0378] Step 1:

[0379] The user provides input

[0380] A user inputs text or voice data through a terminal. For example, the user inputs "I want to create an email about the launch of a new product." This input may include the user's intentions and emotions. The input data is sent to the terminal in text or voice format.

[0381] Step 2:

[0382] The device receives input and sends it to the server

[0383] The device receives input from the user and converts it into an appropriate format. For example, in the case of voice input, the device converts the voice into text. The converted data is then sent from the device to the server. Specifically, the smartphone's voice recognition function converts the voice into text and sends the text to the server.

[0384] Step 3:

[0385] The server parses the input

[0386] The server analyzes the received input data using natural language processing technology. Specifically, it uses libraries such as Python and TensorFlow to extract the main points of the input text. For example, the server analyzes the text "I would like to create an email about the launch of a new product" and extracts the main points "launching a new product" and "composing an email." The input is text data, and the output is data with the extracted main points.

[0387] Step 4:

[0388] The server analyzes emotions using an emotion engine.

[0389] The server uses an emotion engine to analyze emotions from user input. The emotion engine detects the user's emotions from input text and voice and provides the results to the generative AI. Specifically, the server detects the user's impatience from the text "I want to create an email about the launch of a new product." The input is text data, and the output is emotional information.

[0390] Step 5:

[0391] The server generates text using generative AI

[0392] The server uses generative AI to generate appropriate text based on the analysis results and emotional information. The generative AI uses a pre-trained model to generate text that matches the user's intentions. Specifically, the server generates the following text based on the main point, "I want to write an email about the launch of a new product," and the emotional information, "I'm anxious": "Thank you for your continued support. We're writing to let you know about the launch of our new product. Details are as follows." The input is the main point and emotional information, and the output is the generated text.

[0393] Step 6:

[0394] The server sends the generated text to the terminal.

[0395] The server sends the generated text to the terminal. The terminal displays the received text to the user. Specifically, the server sends the generated text to the smartphone, which then displays the text on its screen. The input is the generated text, and the output is the text displayed on the terminal.

[0396] Step 7:

[0397] The user reviews the generated text and corrects it if necessary.

[0398] The user checks the generated sentence displayed on the device and makes corrections as necessary. Once corrections are complete, the final sentence can be sent. Specifically, the user checks the sentence displayed on the smartphone screen and corrects "The details are as follows" to "The details are as follows." The input is the generated sentence, and the output is the corrected final sentence.

[0399] (Application example 1)

[0400] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0401] In traditional electronic payment services, it can be difficult to provide a prompt and appropriate response when a user inputs a problem or question. Furthermore, a uniform response is given without considering the user's feelings, which can leave the user dissatisfied. This can lead to a poor user experience and a decrease in the rate of continued use of the service.

[0402] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0403] In this invention, the server includes generative AI means for generating text based on input from a user, transmission means for transmitting the text generated by the generative AI means, destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion engine for analyzing the user's emotions, and generative AI means for generating text using emotion information analyzed by the emotion engine. This enables appropriate responses according to the user's emotions, improving the user experience and increasing the rate of continued use of the service.

[0404] "Generative AI methods" refers to artificial intelligence technologies that generate text based on user input.

[0405] "Transmission means" refers to the function for transmitting text generated by the generative AI means.

[0406] "Destination determination means" refers to a function that determines the destination based on the content of the text generated by the generative AI means.

[0407] "Emotion engine" refers to technology for analyzing emotions from user input.

[0408] "Emotional information" refers to data regarding a user's emotions analyzed by the emotion engine.

[0409] As an embodiment of the present invention, an emotion-responsive electronic payment assistant system will be described as an example. This system includes a generative AI means for generating text based on user input, a sending means for sending the generated text, a destination determination means for determining a destination based on the content of the generated text, an emotion engine for analyzing the user's emotions, and a generative AI means for generating text using emotion information.

[0410] When a user inputs a question or problem about electronic payment, the server uses the generative AI means to analyze the content and provide an appropriate answer or solution. The emotion engine analyzes the emotion from the user's input text and provides the result to the generative AI means. The generative AI means uses this emotion information to generate sentences that are appropriate to the user's emotions.

[0411] Specifically, the server uses the following hardware and software. For hardware, a smartphone and server are required. For software, Python, OpenAI API, and TextBlob are used. Python is a programming language, and OpenAI API is an interface for using generative AI models. TextBlob is a natural language processing library used for sentiment analysis.

[0412] If a user types "I'm having trouble with my payment, what should I do?", the emotion engine will use TextBlob to analyze the user's emotions. Based on the analysis results, the generative AI means will generate an appropriate prompt and generate an answer using the OpenAI API. For example, if it is determined that the user is feeling stressed, the generative AI means will generate the following prompt:

[0413] Example prompt sentence:

[0414] "Polite response when a user is very angry: My payment isn't working, what should I do?"

[0415] Example of a generated answer:

[0416] "Dear customer, we apologize for any inconvenience caused. If you are having trouble with your payment, please first check your internet connection. If that doesn't resolve the issue, please contact our customer support and we will assist you promptly."

[0417] In this way, it becomes possible to respond appropriately to the user's emotions, improving the user experience and increasing the rate at which the service is continued to be used.

[0418] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0419] Step 1:

[0420] The user enters a question or problem regarding electronic payment.

[0421] Input: The text of the user's question or problem (e.g., "I'm having trouble with my payment, what should I do?")

[0422] Output: The text entered by the user

[0423] Step 2:

[0424] The server receives the user's input text and performs emotion analysis using an emotion engine.

[0425] Input: User-entered text

[0426] Data processing: Analyze the sentiment of the text using TextBlob and calculate the sentiment score

[0427] Output: Sentiment score (e.g. -0.7)

[0428] Step 3:

[0429] The server generates an appropriate prompt sentence based on the emotion score.

[0430] Input: sentiment score, user input text

[0431] Data calculation: Select prompts based on the sentiment score (e.g., if sentiment score is below -0.5, "Polite response for very angry user: I'm having trouble with my payment, what should I do?")

[0432] Output: prompt statement

[0433] Step 4:

[0434] The server uses a generative AI model to generate an answer based on the prompt.

[0435] Input: prompt statement

[0436] Data Calculation: Generate answers based on prompts using the OpenAI API

[0437] Output: The generated answer (e.g., "Dear customer, we apologize for the inconvenience. If you are having trouble with your payment, please first check your internet connection. If that doesn't work, please contact our customer support, and we will assist you promptly.")

[0438] Step 5:

[0439] The server sends the generated answer to the user.

[0440] Input: Generated answer

[0441] Output: The answer sent to the user

[0442] The above processing steps enable appropriate responses according to the user's emotions, improving the user experience and increasing the rate of continued use of the service.

[0443] Example 2

[0444] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0445] Conventional text generation systems generate text without considering the user's emotions, which can result in text that does not match the user's intentions or emotions. Furthermore, they lack the functionality to automatically determine the destination of the generated text, requiring the user to manually specify the destination, which is inefficient. Furthermore, there is a demand for reducing work hours and improving productivity by sending generated text.

[0446] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0447] In this invention, the server includes a generative AI means for generating text based on user input, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, and an emotion analysis means for analyzing the user's emotions and adjusting the tone of the generated text. This makes it possible to automatically generate text that matches the user's emotions and send it to an appropriate destination. It also reduces work hours and improves productivity.

[0448] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0449] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[0450] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[0451] The "emotion analysis means" is a means for analyzing the user's emotions and adjusting the tone of the generated text.

[0452] The present invention is a system that generates text based on user input, analyzes the user's emotions to adjust the tone of the text, and sends the text to an appropriate destination. Specific embodiments of this system are described below.

[0453] Hardware and software used

[0454] Generative AI model: An AI model that generates sentences (e.g., GPT-3)

[0455] Sentiment analysis engine: An engine that analyzes user emotions and adjusts the tone of the text

[0456] Mail server: The server that sends the generated document to the specified destination (e.g. Postfix)

[0457] System configuration

[0458] 1. The user sends a request to the system to generate a sentence.

[0459] 2. The device receives the user's request and inputs a prompt sentence into the generative AI model.

[0460] 3. The generative AI model generates sentences based on the prompt.

[0461] 4. The sentiment analysis engine analyzes the user's emotions and adjusts the tone of the generated text based on the results.

[0462] 5. The device receives the adjusted text and sends it to the mail server.

[0463] 6. The mail server forwards the received message to the specified recipient's email address.

[0464] Specific examples

[0465] Example prompt: "Write an email introducing our new product."

[0466] User sentiment: Delighted

[0467] Generated text: "Hello! Introducing our new product! We're super excited about this new product! Come try it out!"

[0468] Processing Details

[0469] 1. A user requests, "Please create an email to introduce a new product."

[0470] 2. The device receives this request and inputs the prompt "Please create an introductory email for our new product" into the generative AI model.

[0471] 3. Based on the prompt, the generative AI model generates the sentence, "Hello! Introducing our new product. We're very excited about this new product. Please try it out!"

[0472] 4. The emotion analysis engine analyzes the user's emotions and determines that the user is happy.

[0473] 5. The sentiment analysis engine adjusts the tone of the generated text to be brighter.

[0474] 6. The device sends the adjusted text to the mail server.

[0475] 7. The mail server forwards the received message to the specified recipient's email address.

[0476] This system makes it possible to automatically generate text that matches the user's emotions and send it to the appropriate recipient, thereby reducing work time and improving productivity.

[0477] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0478] Step 1:

[0479] The user submits a request for sentence generation.

[0480] Input: The user types "Please create an introductory email for our new product" through the terminal interface.

[0481] Output: The device receives the user's request.

[0482] Specific operation: The user enters a prompt sentence into the input field of the terminal and presses the send button.

[0483] Step 2:

[0484] The device receives the request and inputs a prompt into the generative AI model.

[0485] Input: User request: "Please create an email to introduce our new product."

[0486] Output: The prompt sentence is input to the generative AI model.

[0487] Specific operation: The device sends the received prompt text to the API of the generative AI model.

[0488] Step 3:

[0489] A generative AI model generates sentences based on the prompt.

[0490] Input: Prompt text "Please create an email introducing our new product."

[0491] Output: Generated sentence: "Hello! Introducing our new product. We're very excited about this new product. Come try it out!"

[0492] Specific behavior: The generative AI model analyzes the prompt sentence and generates an appropriate sentence.

[0493] Step 4:

[0494] The sentiment analysis engine analyzes the user's sentiment.

[0495] Input: User input data (text or voice).

[0496] Output: The user's emotional state (e.g., happy).

[0497] What it does: The sentiment analysis engine analyzes user input data to identify their emotional state.

[0498] Step 5:

[0499] The sentiment analysis engine adjusts the tone of the text based on the analysis results.

[0500] Input: The generated sentence and the user's emotional state.

[0501] Output: The adjusted sentence.

[0502] What it does: The sentiment analysis engine adjusts the tone of the generated text to match the user's emotions.

[0503] Step 6:

[0504] The device sends the adjusted text to the mail server.

[0505] Input: Adjusted text.

[0506] Output: The text sent to the mail server.

[0507] Specific operation: The device passes the adjusted text to the mail server's sending API.

[0508] Step 7:

[0509] The mail server forwards the document to the specified destination.

[0510] Input: The text and recipient information sent to the mail server.

[0511] Output: The email sent to the destination email address.

[0512] Specific operation: The mail server forwards the received text to the specified recipient's email address.

[0513] (Application example 2)

[0514] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0515] Conventional text generation systems using generative AI were unable to generate text in a tone that reflected the user's emotions, making it difficult to communicate appropriately with the user. Furthermore, there was a lack of a way to appropriately determine the recipient of the generated text, making it difficult to achieve efficient information transmission. In particular, online shopping sites are required to send product promotional emails and campaign emails that reflect the user's emotions, but the technology to achieve this was lacking.

[0516] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0517] In this invention, the server includes a generative AI means for generating text based on user input, a sending means for sending the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, and an emotion engine means for analyzing the user's emotions and adjusting the tone of the text based on the emotions, thereby making it possible to generate and send product promotion emails and campaign emails in a tone that corresponds to the user's emotions.

[0518] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0519] The "transmission means" is a means for transmitting the text generated by the generative AI means to a specified destination.

[0520] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[0521] The "emotion engine means" is a means for analyzing the user's emotions and adjusting the tone of the text based on those emotions.

[0522] A "product introduction email" is an email that introduces product information to users.

[0523] "Campaign Email" means an email sent to inform users about a specific campaign or promotion.

[0524] "Tone" refers to the emotional atmosphere and style of expression of a piece of writing.

[0525] To implement this invention, a server, a user terminal, and a generative AI model are used. The server includes generative AI means for generating text based on input from a user, transmission means for transmitting the generated text, destination determination means for determining a destination based on the content of the generated text, and emotion engine means for analyzing the user's emotions and adjusting the tone of the text based on the emotions.

[0526] The user terminal provides an interface for analyzing the user's emotions when the user browses or purchases products. Specifically, a device equipped with a camera and microphone is used to analyze the user's facial expressions and voice. This allows the user's emotional data to be collected and sent to the server.

[0527] The server analyzes the user's emotions using the emotion engine means and determines the tone of the text based on the analysis result. For example, if the emotion engine analyzes that the user is happy, the generative AI means generates text with a bright tone. The generated text is sent to a specified destination using the sending means.

[0528] For example, if a user is browsing an online shopping site on their smartphone and the emotion engine determines that the user is "happy," the generative AI model will generate the following email in a cheerful tone:

[0529] "Hello! The latest smartphone is waiting for you! Equipped with a high-performance camera and long-lasting battery, this model will make your life more fun and convenient. Check it out now!"

[0530] An example of this prompt is:

[0531] User sentiment: happy

[0532] Product information: The latest smartphone, equipped with a high-performance camera and long-lasting battery life. Price: 80,000 yen

[0533] Tone: Bright

[0534] In this way, it is possible to generate and send product promotional emails and campaign emails in a tone that matches the user's emotions, which allows for more personalized communication and is expected to improve customer satisfaction.

[0535] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0536] Step 1:

[0537] The user device collects the user's facial expressions and voice using a camera and microphone, thereby acquiring the user's emotional data. The input is the user's facial expressions and voice data, and the output is emotional data.

[0538] Step 2:

[0539] The user terminal transmits the collected emotion data to the server. The input is emotion data, and the output is the emotion data transmitted to the server.

[0540] Step 3:

[0541] The server analyzes the received emotion data using an emotion engine means to identify the emotion of the user, where the input is the emotion data and the output is the identified emotion of the user (e.g., happy, sad, neutral).

[0542] Step 4:

[0543] The server uses generative AI means to determine the tone of the text based on the user's emotion, where the input is the identified user emotion and the output is the determined tone of the text.

[0544] Step 5:

[0545] The server uses generative AI to generate text for product promotional emails and campaign emails based on product information and the determined tone. The input is the product information and the determined tone, and the output is the generated text.

[0546] Step 6:

[0547] The server uses a destination determination means to determine a destination based on the content of the generated text, with the input being the generated text and the output being the determined destination.

[0548] Step 7:

[0549] The server uses a sending means to send the generated text to the determined destination. The input is the generated text and the determined destination, and the output is the sent email.

[0550] Example 3

[0551] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0552] In conventional systems, users had to manually decide where to send messages, which was inefficient and had a high risk of sending them to the wrong person. Furthermore, the system lacked the ability to automatically determine the appropriate recipient based on the user's emotions, making it difficult to respond appropriately to the user's feelings.

[0553] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a generative AI means for generating a sentence based on an input from a user, a transmission means for transmitting the sentence generated by the generative AI means, a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means, and an emotion analysis means for analyzing the user's emotion and determining a destination based on the result. This makes it possible to automatically generate a sentence based on a prompt sentence input by the user and automatically determine an appropriate destination based on the content of the sentence and the user's emotion.

[0554] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0555] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[0556] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[0557] The "emotion analysis means" is a means for analyzing the user's emotions and determining the destination based on the results.

[0558] This invention is a system that generates a sentence based on an input from a user and automatically determines an appropriate destination depending on the content of the sentence and the user's emotions. A specific embodiment of this system will be described below.

[0559] Hardware and software used

[0560] Hardware: Servers, terminals

[0561] Software: Generative AI models (e.g., GPT-4), sentiment analysis engines

[0562] System configuration

[0563] 1. Generative AI methods: Generate sentences based on user input. Use a generative AI model (e.g., GPT-4) to generate natural language sentences based on user-entered prompts.

[0564] 2. Transmission means: Send the generated text. The server has a means to send the generated text to the appropriate destination.

[0565] 3. Destination determination method: The destination is determined based on the content of the generated text. The server analyzes the generated text and determines the destination based on specific keywords or phrases.

[0566] 4. Sentiment analysis means: Analyze the user's emotions and determine the destination based on the results. A sentiment analysis engine is used to analyze the emotions from the user's input and determine the appropriate destination.

[0567] Specific examples

[0568] The user uses the device interface to enter a prompt for the generative AI model, for example, "Please write a detailed description of the new product launch."

[0569] The device sends this prompt to the server. The server inputs the received prompt into the generative AI model to generate a sentence. Based on the prompt, the generative AI model generates a sentence such as, "We are announcing a new product. This new product has been developed using the latest technology."

[0570] Next, the server analyzes the generated text. Specifically, it detects keywords and phrases within the text. For example, it detects the phrase "announcement of a new product." The server determines the destination based on the analysis results. For example, if the text contains the phrase "announcement of a new product," the server decides to send the text to the marketing department's email address.

[0571] Furthermore, the sentiment analysis engine analyzes the user's emotions. For example, if a user is dissatisfied with customer service, the sentiment analysis engine analyzes that emotion and determines the appropriate destination. For example, in response to the prompt, "Please express your dissatisfaction with customer service," the generative AI model generates the sentence, "I am extremely dissatisfied with the recent customer service experience." The sentiment analysis engine analyzes the user's anger and determines that this sentence should be sent to the customer service department.

[0572] In this way, it is possible to automatically generate a sentence based on the prompt sentence entered by the user, and automatically determine an appropriate destination depending on the content of the sentence and the user's emotions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0573] Step 1:

[0574] The user inputs a prompt sentence. The user uses the terminal interface to input a prompt sentence to the generative AI model. For example, the user might input "Please write a detailed description of the new product launch." The input data is the prompt sentence in text format.

[0575] Step 2:

[0576] The terminal sends the prompt text to the server. The terminal uses an HTTP request to send the prompt text to the server. Specifically, it uses a POST request to send the prompt text to the server. The input data is the prompt text entered by the user, and the output data is the prompt text sent to the server.

[0577] Step 3:

[0578] The server generates a sentence using a generative AI model. The server inputs the received prompt sentence into a generative AI model (e.g., GPT-4) to generate a sentence. The generative AI model generates a sentence in natural language based on the prompt sentence. The input data is the prompt sentence, and the output data is the generated sentence. For example, the generated sentence is, "Our company is announcing a new product. This new product has been developed using the latest technology."

[0579] Step 4:

[0580] The server analyzes the generated text. The server inputs the generated text into a text analysis engine to extract keywords and phrases. Specifically, it uses regular expressions and natural language processing libraries to detect the phrase "new product launch." The input data is the generated text, and the output data is the extracted keywords and phrases.

[0581] Step 5:

[0582] The server determines the destination. Based on the analysis results, the server runs a destination determination algorithm. For example, if the phrase "new product launch" is included, the email address of the marketing department is selected. The input data are the extracted keywords and phrases, and the output data are the determined destination.

[0583] Step 6:

[0584] The server sends the text to the determined destination. The server uses the SMTP protocol to send an email to the determined destination. For example, an email is sent to the marketing department's email address saying, "We are announcing a new product. This new product has been developed using the latest technology." The input data is the generated text and the determined destination, and the output data is the email that was sent.

[0585] Step 7:

[0586] The server analyzes the user's emotions. The server uses an emotion analysis engine to analyze emotions from the user's input. For example, if a user is dissatisfied with customer service, the emotion analysis engine analyzes that emotion. The input data is the user's input, and the output data is the analyzed emotion.

[0587] Step 8:

[0588] The server determines the appropriate destination based on the emotion analysis results. For example, if the user is angry, send it to the customer service department. The input data is the analyzed emotion, and the output data is the determined destination.

[0589] Step 9:

[0590] The server sends the text to the determined destination. The server uses the SMTP protocol to send an email to the determined destination. For example, an email can be sent to the customer service department saying, "I'm very unhappy with your recent customer service experience." The input data is the generated text and the determined destination, and the output data is the email sent.

[0591] (Application example 3)

[0592] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0593] Conventional self-driving vehicles have the problem that it is difficult to improve passenger satisfaction because they do not have a system that can respond appropriately based on passenger emotions and comments. In addition, there is a lack of means to quickly respond when passengers are dissatisfied, which can result in a decline in service quality.

[0594] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0595] In this invention, the server includes a generative AI means for generating text based on user input, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion analysis means for analyzing the user's emotion, and an emotion-based destination determination means for determining a destination based on the emotion analyzed by the emotion analysis means. This makes it possible to take appropriate action based on the passenger's emotion and the content of their comments, thereby improving passenger satisfaction. Furthermore, it is possible to quickly respond to passenger dissatisfaction, thereby improving service quality.

[0596] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0597] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[0598] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[0599] "Emotion analysis means" is a means for analyzing the user's emotions.

[0600] The "emotion-based destination determination means" is a means for determining a destination based on the emotion analyzed by the emotion analysis means.

[0601] The system for implementing this invention uses the following hardware and software: the hardware uses an in-car camera and microphone, and the software uses Python, the EmotionRecognizer library, the AI ​​Text Generator library, and smtplib (for sending emails).

[0602] The server first acquires passenger data from the in-car camera and microphone. Then, it analyzes the passenger's emotions using the EmotionRecognizer library. The analyzed emotional data is used as input data to generate text using the AI ​​Text Generator library. The generated text is then sent to the appropriate destination via a transmission means.

[0603] As a specific example, the following prompt sentence could be input into a generative AI model:

[0604] If a passenger is talking about a new product in the car:

[0605] "We look forward to the unveiling of our new self-driving vehicle."

[0606] If a passenger complains on board:

[0607] "The air conditioning in this car isn't working, can you do something about it?"

[0608] When these prompts are entered, the generative AI model generates a response and sends an email to the appropriate department, such as the marketing department if the response contains the phrase "new product launch," or the customer service department if the response indicates the passenger is angry.

[0609] This system makes it possible to respond appropriately based on passengers' emotions and comments, thereby improving passenger satisfaction. It also makes it possible to respond quickly when passengers are dissatisfied, thereby improving service quality.

[0610] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0611] Step 1:

[0612] The server collects passenger data from cameras and microphones inside the vehicle.

[0613] Input: Video and audio data from the camera and microphone

[0614] Output: Passenger video and audio data

[0615] Specific operation: Records passengers' facial expressions and comments in real time via camera and microphone.

[0616] Step 2:

[0617] The server uses the EmotionRecognizer library to analyze emotions from the acquired passenger data.

[0618] Input: Passenger video and audio data

[0619] Output: Parsed emotion data (e.g., joy, anger, sadness, etc.)

[0620] Specific operation: Analyzes facial expressions from video data and tone of voice and content of words from audio data to identify emotions.

[0621] Step 3:

[0622] The server uses the AI ​​Text Generator library to generate sentences based on emotion and voice data.

[0623] Input: Parsed emotion data and speech data

[0624] Output: Generated sentence

[0625] Specific operation: Emotional data and voice data are input into the AI ​​model as prompts to generate appropriate sentences.

[0626] Step 4:

[0627] The server determines the destination based on the content of the generated text.

[0628] Input: Generated sentence

[0629] Output: Destination email address

[0630] What it does: Analyzes the generated text, detects keywords such as "new product launch," and identifies the appropriate department (e.g., marketing, customer service).

[0631] Step 5:

[0632] The server uses the transmission means to transmit the generated text to the determined destination.

[0633] Input: Generated text and destination email address

[0634] Output: Email sent

[0635] Specific operation: Uses smtplib to send an email containing the generated text to the specified recipient.

[0636] The above processing steps enable appropriate responses to be taken based on the passenger's emotions and comments, thereby improving passenger satisfaction. In addition, if a passenger becomes dissatisfied, a prompt response can be made, thereby improving service quality.

[0637] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0638] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0639] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0640] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0641] [Second embodiment]

[0642] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0643] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0644] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0645] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0646] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0647] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0648] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0649] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0650] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0651] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0652] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0653] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0654] "Example 1"

[0655] In one embodiment of the present invention, the generative AI uses natural language processing technology to analyze user input and generate sentences based on that. Specifically, if a user inputs, "I would like to create an email about a new product launch," the generative AI extracts the key points and generates sentences using appropriate honorifics and business terms.

[0656] "Example 2"

[0657] The sending means sends the generated text to the specified destination. Specifically, the generative AI sends the generated text to an email server, which then forwards it to the destination email address.

[0658] "Example 3"

[0659] Furthermore, the destination determination means determines the destination based on the content of the generated text. Specifically, if the text generated by the generative AI contains the phrase "announcement of a new product," the destination determination means determines to send it to the email address of the marketing department.

[0660] The processing flow of each embodiment will be described below.

[0661] "Example 1"

[0662] Step 1: A user enters a request into the system: "I want to create an email about a new product launch."

[0663] Step 2: The generative AI uses natural language processing techniques to analyze the user input and extract the key points.

[0664] Step 3: The generative AI generates sentences using appropriate honorifics and business terms based on the extracted key points.

[0665] "Example 2"

[0666] Step 1: The text generated by the generative AI is passed to the sending means.

[0667] Step 2: The sending means sends the generated text to the mail server.

[0668] Step 3: The email server forwards the generated document to the specified recipient's email address.

[0669] "Example 3"

[0670] Step 1: The text generated by the generative AI is passed to the destination determination means.

[0671] Step 2: The destination determination means determines the destination based on the content of the generated text.

[0672] Step 3: Specifically, if the phrase "announcement of new product" is included, the destination determining means determines that it should be sent to the email address of the marketing department.

[0673] Example 1

[0674] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0675] In conventional text generation systems, the process of properly analyzing user input, generating prompts, and generating text is complicated and difficult to perform efficiently. Furthermore, there was a lack of functionality to automatically determine the destination of the generated text, which increased the user's workload. Furthermore, there was a need to reduce work time and improve productivity by sending the generated text.

[0676] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0677] In this invention, the server includes an input means for receiving input from a user, a prompt generation means for analyzing the input from the input means and generating a prompt sentence, a generative AI means for generating a sentence using the prompt sentence generated by the prompt generation means, a transmission means for transmitting the sentence generated by the generative AI means, and a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means. This makes it possible to efficiently analyze the user's input and generate an appropriate prompt sentence to generate the sentence, and further to automatically determine the destination of the generated sentence, thereby reducing the user's effort, shortening work hours, and improving productivity.

[0678] An "input means" is a device or software for receiving input from a user.

[0679] A "prompt generation means" is a device or software that analyzes the user's input received from the input means and generates a prompt sentence to be passed to the generative AI means.

[0680] "Generative AI means" refers to a device or software that uses artificial intelligence technology to generate sentences using prompt sentences generated by a prompt generation means.

[0681] "Transmission means" refers to a device or software for transmitting text generated by the generative AI means.

[0682] The "destination determination means" is a device or software that determines the destination based on the content of the text generated by the generative AI means.

[0683] The present invention relates to a system that receives input from a user, generates a sentence based on the input, and transmits the sentence. A specific embodiment of this system will be described below.

[0684] The server has an input means for receiving input from a user. The user inputs text into an input field through a terminal. For example, the user inputs "I want to create an email about the launch of a new product."

[0685] The device sends the user's input to the server. The server analyzes the received input and generates a prompt sentence using a prompt generation means. This prompt generation means analyzes the input using natural language processing technology and generates a prompt sentence to be passed to a generative AI model (e.g., GPT-4).

[0686] An example of a generated prompt is as follows:

[0687] Write an email about a new product launch. Include the following key points: new product features, release date, price, and how to purchase. Use appropriate honorifics and business terminology.

[0688] The server passes this prompt to the generative AI means, which analyzes the prompt and generates appropriate sentences based on the user's request using natural language processing techniques such as tokenization, part-of-speech tagging, and dependency analysis.

[0689] An example of a generated sentence is as follows:

[0690] Subject: New product announcement

[0691] Dear Customers,

[0692] We would like to express our sincere gratitude for your continued patronage. We are pleased to announce our new product, "XX." This product utilizes the latest technology and aims to provide a more comfortable user experience.

[0693] The release date is XX / XX, and the price is XX yen. You can purchase it on our website or at a retailer near you.

[0694] We sincerely hope for your continued patronage.

[0695] Sincerely,

[0696] The server uses a transmission means to send the generated text to the terminal. The terminal displays the received text to the user. The user can check the displayed text and make corrections or additions as necessary.

[0697] This system can efficiently analyze user input, generate appropriate prompts, and generate sentences. Furthermore, by automatically determining the destination of the generated sentences, it reduces user effort, shortens work time, and improves productivity.

[0698] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0699] Step 1:

[0700] The user provides input through the terminal.

[0701] The user inputs "I want to create an email about the launch of a new product" into the input field of the terminal. This input is written in natural language. The input data is in text format, and the terminal receives this input.

[0702] Step 2:

[0703] The device sends input to the server.

[0704] The terminal sends the user's input as an HTTP request to the server. The input data is in text format, and the server receives this request.

[0705] Step 3:

[0706] The server receives the input and generates a prompt.

[0707] The server analyzes the received input and generates a prompt using a prompt generation method. Specifically, it uses natural language processing technology to tokenize the input text and extract important keywords and phrases. Based on this, it generates a prompt to be passed to the generative AI model. For example, it generates a prompt such as, "Write an email about the launch of a new product. Include the following key points: the new product's features, release date, price, and how to purchase. Use appropriate honorifics and business terminology."

[0708] Step 4:

[0709] The server passes the prompt sentence to the generative AI model, which analyzes it and generates the sentence.

[0710] The server passes the generated prompt sentence to a generative AI model (e.g., GPT-4). The generative AI model analyzes the prompt sentence and generates an appropriate sentence based on the user's request. This analysis uses natural language processing techniques such as tokenization, part-of-speech tagging, and dependency analysis. The generated sentence is returned to the server in text format.

[0711] Step 5:

[0712] The server receives the generated text and sends it to the terminal.

[0713] The server receives the sentences generated by the generative AI model and sends them as an HTTP response to the terminal. The output data is in text format, and the terminal receives this response.

[0714] Step 6:

[0715] The terminal displays the generated text to the user.

[0716] The terminal displays the generated text received from the server to the user. The user can check the displayed text and make corrections or additions as necessary. The output data is in text format and is displayed in a format that the user can visually check.

[0717] (Application example 1)

[0718] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0719] The traditional ad copy creation process was often manual, requiring time and effort, resulting in inefficiency. Additionally, the quality of the ad copy depended on the skill of the person creating it, making it difficult to create consistent, high-quality ad copy.

[0720] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0721] In this invention, the server includes a generative AI means for generating text based on user input, a sending means for sending the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an input means for inputting information for automatically generating advertising copy, and a generation means for analyzing the information input by the input means and generating advertising copy. This automates the process of creating advertising copy, significantly reducing time and labor. It also enables consistent, high-quality advertising copy to be generated quickly.

[0722] "Generative AI methods" are artificial intelligence techniques that generate text based on user input.

[0723] "Transmission means" is a function for transmitting text generated by the generative AI means.

[0724] The "destination determination means" is a function for determining the destination based on the content of the text generated by the generative AI means.

[0725] The "input means" is a function for inputting information for automatically generating advertising copy.

[0726] The "generation means" is a function for analyzing information input by the input means and generating advertising copy.

[0727] A system for carrying out this invention is for automatically generating advertising copy based on input from a user. The system includes a generation AI means, a sending means, a destination determination means, an input means, and a generation means.

[0728] The server uses OpenAI's API as a generative AI tool. Users input information such as the purpose of the ad copy, target audience, and product features via their smartphone or computer. The input tool receives this information and generates prompt text.

[0729] The generating means transmits the generated prompt text to the OpenAI API to generate advertising copy. The generated advertising copy is transmitted to the user by the transmitting means. The destination determining means determines an appropriate destination based on the content of the generated advertising copy.

[0730] As a concrete example, consider the case of generating ad copy for a new smartphone. The user enters the following information:

[0731] Product Name: New Smartphone

[0732] Target audience: Young people

[0733] Features: High-resolution camera, long battery life, stylish design

[0734] An example of a prompt generated based on this information is as follows:

[0735] Product Name: New Smartphone

[0736] Target audience: Young people

[0737] Features: High-resolution camera, long battery life, stylish design

[0738] Use this information to generate effective ad copy.

[0739] The server sends this prompt text to OpenAI's API to obtain the generated ad copy. The obtained ad copy is then sent to the user via a sending method. This automates the ad copy creation process, significantly reducing time and effort. It also enables consistent, high-quality ad copy to be generated quickly.

[0740] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0741] Step 1:

[0742] The user uses a smartphone or computer to input information such as the purpose of the ad copy, the target audience, and the product's features. The input information is sent to the server. The input data includes the product name, target audience, and features.

[0743] Step 2:

[0744] The server analyzes the received input data and generates a prompt. Specifically, it creates a prompt for generating advertising copy based on the input product name, target audience, and features. The generated prompt will have the following format:

[0745] Product Name: New Smartphone

[0746] Target audience: Young people

[0747] Features: High-resolution camera, long battery life, stylish design

[0748] Use this information to generate effective ad copy.

[0749] Step 3:

[0750] The server sends the generated prompt text to OpenAI's API, which generates ad copy based on the prompt text. The input data is the prompt text, and the output data is the generated ad copy.

[0751] Step 4:

[0752] The server receives the ad copy returned from the OpenAI API. The received ad copy is temporarily stored on the server.

[0753] Step 5:

[0754] The server determines the destination based on the content of the generated advertisement copy. The destination determination means analyzes the content of the advertisement copy and selects an appropriate destination. For example, if the advertisement copy is aimed at young people, a platform that is frequently used by young people is selected.

[0755] Step 6:

[0756] The server sends the generated advertising copy to the determined destination. The sending means converts the advertising copy into an appropriate format and sends it to the selected destination, so that the advertising copy reaches the target audience.

[0757] Step 7:

[0758] The user can check the sent ad copy and make corrections or regenerate it as necessary. If the user makes corrections, the process will be repeated from step 1.

[0759] Example 2

[0760] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0761] Conventional text generation systems require users to manually send the text they generate, which reduces work efficiency. Furthermore, the process of determining recipients and sending emails is cumbersome, placing a heavy burden on users. This creates challenges in terms of reducing work time and improving productivity.

[0762] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0763] In this invention, the server includes a generative AI means for generating text based on input from a user, a transmission means for transmitting the generated text, a means for transmitting the generated text to the server, a means for transferring the text received by the server to a mail server, and a means for the mail server to send the text to a specified destination. This allows text to be automatically generated based on a prompt text entered by a user and sent to a specified destination, thereby improving work efficiency and reducing the burden on the user.

[0764] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0765] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[0766] The "means for transmitting to the server" refers to a means for transmitting the text generated by the generative AI means to the server.

[0767] A "server" is a computer system that processes text received from a generative AI means and forwards it to a mail server.

[0768] "Means for transferring to the mail server" refers to the means by which the server transfers the received text to the mail server.

[0769] A "mail server" is a server that sends documents transferred from the server to a specified destination.

[0770] "Means for sending to the specified destination" refers to the means by which the mail server sends the text to the specified destination.

[0771] A "prompt" is an instruction that a user inputs to a generative AI means.

[0772] The present invention is a system that generates a sentence based on a prompt sentence entered by a user and automatically sends the sentence to a specified destination. A specific embodiment of this system will be described below.

[0773] First, the user inputs a prompt through the terminal interface, for example, "Please write an email introducing our new product." This prompt is an instruction for the generative AI model and determines the content of the text to be generated.

[0774] Next, the device receives the user's input and sends a prompt to the generative AI model. At this time, the device accesses the API of the generative AI model via the Internet. For example, OpenAI's GPT-4 can be used as the generative AI model.

[0775] The generative AI model analyzes the received prompt and generates an appropriate sentence, such as, "Hello, we'd like to introduce our new product. This product utilizes the latest technology and will make your daily life more convenient. Please give it a try."

[0776] The generated text is sent from the terminal to the server. The terminal sends data to the server using an HTTP request. The server connects to the mail server using the SMTP protocol to transfer the received text to the mail server and sends the text.

[0777] The mail server sends the received text to the specified destination email address. For example, if the destination is "example@example.com", the mail server will send an email containing the generated text to this address.

[0778] This system allows users to easily use generative AI models to generate text and send it to a specified destination, improving work efficiency and reducing the burden on users.

[0779] Examples of specific prompts include:

[0780] "Please create an email to introduce a new product."

[0781] Please prepare the minutes of the meeting.

[0782] Write a thank you letter to your customers.

[0783] In this way, users can create and quickly send texts that meet a variety of needs.

[0784] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0785] Step 1:

[0786] The user enters a prompt sentence through the terminal interface.

[0787] Specifically, the user opens a web browser on the device and enters "Please create an introductory email for our new product" into a dedicated input form.

[0788] Input: Prompt sentence (e.g. "Please create an email introducing our new product")

[0789] Output: The prompt statement is typed into the terminal.

[0790] Step 2:

[0791] The device receives user input and sends prompts to the generative AI model.

[0792] Specifically, the device sends an HTTP POST request to the API endpoint of the generative AI model over the Internet, which includes a prompt.

[0793] Input: prompt statement

[0794] Output: The prompt sentence is sent to the generative AI model.

[0795] Step 3:

[0796] A generative AI model analyzes the prompt and generates an appropriate sentence.

[0797] Specifically, the generative AI model analyzes the prompt and generates the sentence, "Hello, we'd like to introduce our new product. This product utilizes the latest technology and will make your daily life more convenient. Please give it a try."

[0798] Input: prompt statement

[0799] Output: Generated sentence

[0800] Step 4:

[0801] The terminal receives the generated text and sends it to the server.

[0802] Specifically, the device receives the generated text and sends an HTTP POST request to the server. This request includes the generated text.

[0803] Input: Generated sentence

[0804] Output: The generated text is sent to the server.

[0805] Step 5:

[0806] The server forwards the received text to the mail server.

[0807] Specifically, the server connects to a mail server using the SMTP protocol and sends the generated text.

[0808] Input: Generated sentence

[0809] Output: The generated text is sent to the mail server.

[0810] Step 6:

[0811] The mail server sends the message to the specified address.

[0812] Specifically, the mail server sends the received text to the specified destination email address. For example, if the destination is "example@example.com", the mail server will send an email containing the generated text to this address.

[0813] Input: Generated text, recipient's email address

[0814] Output: The generated text is sent to the specified destination.

[0815] (Application example 2)

[0816] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0817] Conventional security systems often lack the means to respond quickly and appropriately when an anomaly is detected. Furthermore, responses after an anomaly is often performed manually, which can lead to delays and human error. This reduces the reliability of security and reduces its effectiveness in situations where a rapid response is required.

[0818] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0819] In this invention, the server includes generative AI means for generating sentences based on input from a user, transmission means for transmitting the sentences generated by the generative AI means, destination determination means for determining a destination based on the content of the sentences generated by the generative AI means, anomaly detection means for acquiring data from a sensor and detecting anomalies, and warning message generation means for generating a warning message when an anomaly is detected. This makes it possible to automatically generate a warning message when an anomaly is detected and quickly send it to an appropriate destination.

[0820] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0821] The "transmission means" is a means for transmitting the text generated by the generative AI means to a specified destination.

[0822] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[0823] The "abnormality detection means" is a means for acquiring data from the sensor and detecting abnormalities.

[0824] The "warning message generating means" is a means for generating a warning message when an abnormality is detected.

[0825] A system for implementing this invention includes a generative AI means for generating text based on input from a user, a transmission means for transmitting the generated text, a destination determination means for determining a destination based on the content of the generated text, anomaly detection means for acquiring data from a sensor and detecting anomalies, and a warning message generation means for generating a warning message when an anomaly is detected.

[0826] Hardware and software used

[0827] Hardware: smartphones, security cameras, sensors

[0828] Software: Python, smtplib (email sending library), generative AI model, module for acquiring data from sensors

[0829] Data processing and calculation

[0830] 1. Data acquisition from sensors: Acquiring data in real time from sensors, for example, security cameras capturing video data.

[0831] 2. Anomaly detection: The acquired data is analyzed using anomaly detection means, and if an anomaly is detected, a flag is raised.

[0832] 3. Warning message generation: If an abnormality is detected, a warning message is generated using generative AI methods. For example, a message such as "A suspicious person has been detected. Please check immediately" can be generated.

[0833] 4. Determining destination: Based on the content of the generated warning message, the destination determination means determines the appropriate destination.

[0834] 5. Send email: The generated warning message is sent by email to the determined recipient using a sending means.

[0835] Specific examples

[0836] For example, if a security camera detects a suspicious person, the video data will be analyzed and the generative AI will generate a warning message stating, "A suspicious person has been detected. Please check immediately," and send it to a specified email address.

[0837] Prompt Sentence Examples

[0838] Analyze security camera footage and generate alert messages to be sent if a suspicious person is detected.

[0839] In this way, the present invention provides a system for quickly and appropriately responding when an abnormality is detected, thereby improving the reliability of security.

[0840] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0841] Step 1:

[0842] Acquiring data from sensors

[0843] The server receives data from sensors in real time. The input is raw data from the sensors, and the output is data converted into an analyzable format. Specifically, a security camera captures video data and sends it to the server.

[0844] Step 2:

[0845] Anomaly detection

[0846] The server analyzes the acquired data using anomaly detection means and sets a flag if an anomaly is detected. The input is the data acquired in step 1, and the output is the result of the anomaly detection (whether an anomaly was detected or not). Specifically, it analyzes the video data and detects suspicious individuals or abnormal behavior.

[0847] Step 3:

[0848] Warning message generation

[0849] If an anomaly is detected, the server generates a warning message using generative AI means. The input is the anomaly detection result and data from the sensor, and the output is the generated warning message. Specifically, it generates a message saying, "A suspicious person has been detected. Please check immediately."

[0850] Step 4:

[0851] Determining destination

[0852] The server's destination determination means determines the appropriate destination based on the content of the generated warning message. The input is the generated warning message, and the output is the determined destination address. Specifically, the content of the warning message is analyzed, and the email address of the appropriate person in charge is selected.

[0853] Step 5:

[0854] Send email

[0855] The server sends the generated warning message to the determined destination by email using a sending means. The input is the determined destination address and the generated warning message, and the output is the status of transmission completion. The specific operation is to send the email using an SMTP server.

[0856] Example 3

[0857] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0858] In conventional systems, when generating text based on information entered by a user, it was difficult to automatically determine the appropriate destination based on the content of the generated text. Furthermore, the destination of the generated text had to be determined manually, resulting in a decrease in work efficiency. Furthermore, the system lacked the functionality to automatically determine the appropriate destination when specific phrases were included, making it difficult to improve work productivity.

[0859] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0860] In this invention, the server includes a generation AI means for generating a sentence based on an input from a user, a transmission means for transmitting the sentence generated by the generation AI means, and a destination determination means for determining a destination based on the content of the sentence generated by the generation AI means. This makes it possible to automatically determine an appropriate destination based on the content of the generated sentence, thereby improving business efficiency. Furthermore, by automatically determining a destination when a specific phrase is included, business productivity can be improved.

[0861] "Generative AI means" is an artificial intelligence function that generates sentences based on input from the user.

[0862] The "transmission means" is a function for transmitting the text generated by the generation AI means.

[0863] The "destination determination means" is a function that determines the destination based on the content of the text generated by the generation AI means.

[0864] A "user" is a user who inputs a prompt sentence to the system.

[0865] A "prompt sentence" is an instruction sentence that the user inputs to the generation AI means.

[0866] The "particular phrase" is a keyword or expression that is important when analyzed by the destination determination means.

[0867] "Working time" is the time an employee spends performing work.

[0868] "Productivity" is an indicator that shows the efficiency and results of work.

[0869] This invention is a system that generates a sentence based on a prompt sentence entered by a user and automatically determines an appropriate destination depending on the content of the sentence. A specific embodiment of this system will be described below.

[0870] System configuration

[0871] The system consists of the following main components:

[0872] 1. Generation AI means

[0873] 2. Transmission Method

[0874] 3. How to determine the destination

[0875] Generation AI means

[0876] The generative AI means has the function of generating sentences based on input from the user. This function is realized using a generative AI model such as OpenAI's GPT-3. When the user inputs a prompt sentence, the generative AI means generates an appropriate sentence based on the prompt sentence.

[0877] Transmission method

[0878] The sending means is a function for sending the text generated by the generating AI means. This function is realized using an email system or a messaging system. The generated text is sent to the destination determined by the destination determination means.

[0879] Destination determination method

[0880] The destination determination means has a function of analyzing the content of the text generated by the generation AI means and determining an appropriate destination. This function uses natural language processing technology to analyze the text and check whether it contains a specific phrase. For example, if the phrase "announcement of a new product" is included, the destination determination means determines that the text should be sent to the email address of the marketing department.

[0881] Specific examples

[0882] Below are some examples of prompts and their results:

[0883] Prompt Sentence Examples

[0884] "Please explain the features of your new smartphone."

[0885] Processing results

[0886] 1. The user enters a prompt statement.

[0887] 2. The generative AI means generates a sentence based on the prompt, such as:

[0888] "We're announcing a new product. The new smartphone features a modern processor, improved battery life, and a significantly improved camera."

[0889] 3. The generated text is passed to the destination determination means.

[0890] 4. The destination determination means analyzes the sentence and determines that it contains the phrase "new product announcement."

[0891] 5. The destination determination means determines that the email should be sent to the marketing department's email address.

[0892] 6. The text is sent to the destination determined by the sending method.

[0893] This system automatically sends a message generated based on a prompt entered by a user to an appropriate destination, thereby improving work efficiency and productivity. The flow of the specific process in the third embodiment will be described with reference to FIG.

[0894] Step 1:

[0895] The user enters a prompt statement.

[0896] The user accesses the system's web interface, enters "Please describe the features of your new smartphone" in the text box, and clicks the submit button.

[0897] Input: prompt statement

[0898] Output: Prompt for user input

[0899] Step 2:

[0900] The server generates sentences using a generative AI model.

[0901] The server receives the prompt sentence entered by the user and passes it to a generative AI model (e.g., GPT-3). The generative AI model generates an appropriate sentence based on the prompt sentence and returns it to the server.

[0902] Input: prompt statement

[0903] Output: Generated sentence

[0904] Step 3:

[0905] The server passes the generated text to the destination determination means.

[0906] The server receives the generated text and passes it to the destination determination means, which executes an algorithm to analyze the content of the text.

[0907] Input: Generated sentence

[0908] Output: The sentence to be analyzed

[0909] Step 4:

[0910] The destination determining means analyzes the text.

[0911] The destination determination means analyzes the generated text and checks whether it contains the phrase "new product announcement." For example, it uses natural language processing technology to tokenize the text and search for specific keywords.

[0912] Input: Text to be analyzed

[0913] Output: Analysis results (presence or absence of specific phrases)

[0914] Step 5:

[0915] The destination determination means determines the destination.

[0916] The destination determination means determines the destination based on the analysis result. For example, if the phrase "announcement of a new product" is included, the destination determination means selects the email address of the marketing department.

[0917] Input: Analysis results

[0918] Output: Determined destination

[0919] Step 6:

[0920] The server sends the text to the determined destination.

[0921] The server sends the text to the destination determined by the destination determination means, for example, to the marketing department's email address.

[0922] Input: Determined destination, generated text

[0923] Output: Email sent

[0924] (Application example 3)

[0925] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0926] In conventional text generation systems using generative AI, it is difficult to appropriately determine the destination of the generated text, and there is a lack of means to send the generated text quickly and efficiently. This has led to issues such as insufficient improvements in work efficiency and productivity.

[0927] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a generative AI means for generating a sentence based on an input from a user, a sending means for sending the sentence generated by the generative AI means, a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means, and an email sending means for sending the generated sentence by email. This makes it possible to automatically determine an appropriate destination based on the content of the generated sentence and send it by email quickly and efficiently.

[0928] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[0929] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[0930] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[0931] The "email sending means" is a means for sending the generated text by email.

[0932] A system for implementing this invention includes a generative AI means for generating text based on input from a user, a sending means for sending the generated text, a destination determination means for determining a destination based on the content of the generated text, and an email sending means for sending the generated text by email.

[0933] The server uses OpenAI's GPT-3 as a generative AI method. GPT-3 generates the content of an advertising campaign based on a prompt entered by the user. For example, if a user enters the prompt "Please generate advertising copy for a new product launch," GPT-3 will generate advertising copy for the new product launch.

[0934] The generated text is temporarily stored by the sending means. Thereafter, the destination determining means analyzes the content of the generated text and determines an appropriate destination. For example, if the generated text contains the phrase "announcement of a new product," the destination determining means determines the email address of the marketing department as the destination.

[0935] The email sending means sends the generated text to the determined recipient by email using the Python smtplib library. The server connects to the SMTP server and sends the email using the appropriate authentication information.

[0936] As a concrete example, the following prompt sentence is input to the generative AI model:

[0937] "Generate advertising copy for a new product launch."

[0938] By inputting this prompt, the generative AI method can generate advertising copy for the new product launch, determine appropriate recipients based on the content of the copy, and distribute it via email, thereby enabling the content of advertising campaigns to be distributed quickly and efficiently.

[0939] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0940] Step 1:

[0941] The user inputs a prompt using a terminal. Specifically, the user inputs the prompt "Please generate advertising copy for the launch of a new product." This input is sent to the system.

[0942] Step 2:

[0943] The server uses a generative AI tool (OpenAI's GPT-3) to generate a sentence based on the prompt from the user. The input prompt is sent to GPT-3, and the generated ad copy is received. This ad copy is then passed on to the next processing step.

[0944] Step 3:

[0945] The server temporarily stores the generated copy of the advertisement by a transmission means. Specifically, the server stores the generated copy of the advertisement in a database or memory. The stored copy of the advertisement is passed to the next processing step.

[0946] Step 4:

[0947] The server uses the destination determination means to analyze the content of the generated advertisement copy and determine the appropriate destination. Specifically, it checks whether the advertisement copy contains the phrase "announcement of new product," and if so, determines the email address of the marketing department as the destination. This determined destination is passed to the next processing step.

[0948] Step 5:

[0949] The server uses the email sending mechanism to send the generated ad copy to the determined recipients by email. Specifically, it uses Python's smtplib library to connect to an SMTP server and sends the email using the appropriate authentication information. This process sends the ad copy to the marketing department.

[0950] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0951] "Example 1"

[0952] In one embodiment of the present invention, the generative AI means includes an emotion engine that recognizes a user's emotion. The emotion engine analyzes the emotion from the user's input (e.g., speech or text) and provides the results to the generative AI means. The generative AI means uses this emotion information to generate sentences that are appropriate to the user's emotion. For example, if the user feels angry, the generative AI means uses that information to generate sentences with a more polite tone.

[0953] "Example 2"

[0954] In another embodiment of the present invention, the emotion engine adjusts the tone of the sentence based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion and determines the tone of the sentence based on the analysis result. For example, if the user feels happy, the emotion engine uses that information to generate a sentence with a lighter tone.

[0955] "Example 3"

[0956] In yet another embodiment of the present invention, the emotion engine determines the destination based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion and determines the destination based on the analysis result. For example, if the user feels angry, the emotion engine uses the information to determine that the email should be sent to a department (e.g., customer service department) that may be able to resolve the issue.

[0957] The processing flow of each embodiment will be described below.

[0958] "Example 1"

[0959] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[0960] Step 2: The emotion engine analyzes the emotion from the user's input. The analysis result indicates the user's emotional state.

[0961] Step 3: The generative AI means receives the analysis results from the emotion engine and generates text based on them, in a tone that matches the user's emotions.

[0962] "Example 2"

[0963] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[0964] Step 2: The emotion engine analyzes the emotion from the user's input and determines the tone of the text based on the results.

[0965] Step 3: The generative AI receives tone information from the emotion engine and generates text based on that information. At this time, the text is generated in a tone that matches the user's emotions.

[0966] "Example 3"

[0967] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[0968] Step 2: The emotion engine analyzes the emotion from the user's input and determines the destination based on the results.

[0969] Step 3: The generative AI means receives the destination information from the emotion engine, generates a sentence based on that information, and sends it to the specified destination.

[0970] Example 1

[0971] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0972] Conventional text generation systems were unable to take the user's emotions into account when generating text based on user input, resulting in generated text that was inappropriate for the user's intentions or emotions. Furthermore, they lacked the functionality to automatically determine the destination of the generated text, requiring users to manually specify the destination. This resulted in reduced work efficiency and a lack of productivity.

[0973] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0974] In this invention, the server includes an input means for receiving input from a user, an analysis means for analyzing data from the input means, a generative AI means for generating text based on the data analyzed by the analysis means, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion analysis means for analyzing the user's emotions, and an emotion response generation means for generating text based on the emotion information analyzed by the emotion analysis means. This makes it possible to generate appropriate text taking the user's emotions into consideration and automatically determine the destination.

[0975] An "input means" is a device or software for receiving input from a user.

[0976] "Analysis means" refers to a device or software for analyzing data received from an input means.

[0977] "Generative AI means" refers to a device or software that uses artificial intelligence technology to generate text based on data analyzed by analytical means.

[0978] "Transmission means" refers to a device or software for transmitting text generated by the generative AI means.

[0979] The "destination determination means" is a device or software for determining the destination based on the content of the sentence generated by the generative AI means.

[0980] "Emotion analysis means" refers to a device or software for analyzing emotions from user input.

[0981] The "emotion correspondence generation means" is a device or software for generating sentences based on the emotion information analyzed by the emotion analysis means.

[0982] MODE FOR CARRYING OUT THE INVENTION

[0983] The present invention relates to a system that receives input from a user, generates appropriate sentences based on the input, and transmits them. A specific embodiment of this system will be described below.

[0984] server

[0985] The server functions as a platform for running generative AI. It receives input from users and analyzes it using natural language processing technology. Specifically, the server uses software such as Python and TensorFlow to analyze the text entered by the user and extract its key points. For example, if a user enters, "I would like to create an email about the launch of a new product," the server extracts the key points and generates a sentence using appropriate honorifics and business terminology.

[0986] Furthermore, the server analyzes the user's emotions using an emotion engine. The emotion engine analyzes emotions from the user's input (e.g., voice or text) and provides the results to the generative AI. The generative AI uses this emotion information to generate sentences that match the user's emotions. For example, if the user feels angry, the generative AI uses that information to generate sentences with a more polite tone.

[0987] Terminal

[0988] The terminal provides an interface for users to input data. When a user inputs text or voice data through the terminal, the data is sent to the server. The terminal converts the data entered by the user into an appropriate format and sends it to the server. For example, if a user inputs "I would like to create an email about the launch of a new product" by voice, the terminal converts the voice data into text and sends it to the server.

[0989] User

[0990] The user inputs text via their device to generate it using the generative AI. For example, if the user inputs "I want to create an email about a new product launch," the input is sent to the server via their device. The user can review the generated text and make corrections as necessary. If the input contains the user's emotions, the emotion engine analyzes them and provides them to the generative AI. For example, if the user feels angry, the generative AI uses that information to generate text with a more polite tone.

[0991] Specific examples

[0992] 1. The user types into the terminal, "I want to create an email about a new product launch."

[0993] 2. The terminal converts the input into text format and sends it to the server.

[0994] 3. The server uses Python and TensorFlow to parse the input and extract key points.

[0995] 4. The server generates the following sentence using appropriate honorifics and business terms:

[0996] "Thank you for your continued support. We would like to inform you about the launch of our new product. Details are as follows."

[0997] Examples of emotion engines

[0998] 1. A user angrily types into their device, "I want to create an email about a new product launch."

[0999] 2. The device converts the speech into text and sends it to the server.

[1000] 3. The server uses an emotion engine to analyze the user's emotions and detects anger.

[1001] 4. The server provides this emotional information to a generative AI, which generates a polite sentence like this:

[1002] "Thank you for your continued support. We would like to inform you about the launch of a new product. Details are as follows. We appreciate your understanding."

[1003] In this way, the system generates appropriate sentences based on the user's input and emotions and provides them to the user.

[1004] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1005] Step 1:

[1006] The user provides input

[1007] A user inputs text or voice data through a terminal. For example, the user inputs "I want to create an email about the launch of a new product." This input may include the user's intentions and emotions. The input data is sent to the terminal in text or voice format.

[1008] Step 2:

[1009] The device receives input and sends it to the server

[1010] The device receives input from the user and converts it into an appropriate format. For example, in the case of voice input, the device converts the voice into text. The converted data is then sent from the device to the server. Specifically, the smartphone's voice recognition function converts the voice into text and sends the text to the server.

[1011] Step 3:

[1012] The server parses the input

[1013] The server analyzes the received input data using natural language processing technology. Specifically, it uses libraries such as Python and TensorFlow to extract the main points of the input text. For example, the server analyzes the text "I would like to create an email about the launch of a new product" and extracts the main points "launching a new product" and "composing an email." The input is text data, and the output is data with the extracted main points.

[1014] Step 4:

[1015] The server analyzes emotions using an emotion engine.

[1016] The server uses an emotion engine to analyze emotions from user input. The emotion engine detects the user's emotions from input text and voice and provides the results to the generative AI. Specifically, the server detects the user's impatience from the text "I want to create an email about the launch of a new product." The input is text data, and the output is emotional information.

[1017] Step 5:

[1018] The server generates text using generative AI

[1019] The server uses generative AI to generate appropriate text based on the analysis results and emotional information. The generative AI uses a pre-trained model to generate text that matches the user's intentions. Specifically, the server generates the following text based on the main point, "I want to write an email about the launch of a new product," and the emotional information, "I'm anxious": "Thank you for your continued support. We're writing to let you know about the launch of our new product. Details are as follows." The input is the main point and emotional information, and the output is the generated text.

[1020] Step 6:

[1021] The server sends the generated text to the terminal.

[1022] The server sends the generated text to the terminal. The terminal displays the received text to the user. Specifically, the server sends the generated text to the smartphone, which then displays the text on its screen. The input is the generated text, and the output is the text displayed on the terminal.

[1023] Step 7:

[1024] The user reviews the generated text and corrects it if necessary.

[1025] The user checks the generated sentence displayed on the device and makes corrections as necessary. Once corrections are complete, the final sentence can be sent. Specifically, the user checks the sentence displayed on the smartphone screen and corrects "The details are as follows" to "The details are as follows." The input is the generated sentence, and the output is the corrected final sentence.

[1026] (Application example 1)

[1027] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1028] In traditional electronic payment services, it can be difficult to provide a prompt and appropriate response when a user inputs a problem or question. Furthermore, a uniform response is given without considering the user's feelings, which can leave the user dissatisfied. This can lead to a poor user experience and a decrease in the rate of continued use of the service.

[1029] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1030] In this invention, the server includes generative AI means for generating text based on input from a user, transmission means for transmitting the text generated by the generative AI means, destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion engine for analyzing the user's emotions, and generative AI means for generating text using emotion information analyzed by the emotion engine. This enables appropriate responses according to the user's emotions, improving the user experience and increasing the rate of continued use of the service.

[1031] "Generative AI methods" refers to artificial intelligence technologies that generate text based on user input.

[1032] "Transmission means" refers to the function for transmitting text generated by the generative AI means.

[1033] "Destination determination means" refers to a function that determines the destination based on the content of the text generated by the generative AI means.

[1034] "Emotion engine" refers to technology for analyzing emotions from user input.

[1035] "Emotional information" refers to data regarding a user's emotions analyzed by the emotion engine.

[1036] As an embodiment of the present invention, an emotion-responsive electronic payment assistant system will be described as an example. This system includes a generative AI means for generating text based on user input, a sending means for sending the generated text, a destination determination means for determining a destination based on the content of the generated text, an emotion engine for analyzing the user's emotions, and a generative AI means for generating text using emotion information.

[1037] When a user inputs a question or problem about electronic payment, the server uses the generative AI means to analyze the content and provide an appropriate answer or solution. The emotion engine analyzes the emotion from the user's input text and provides the result to the generative AI means. The generative AI means uses this emotion information to generate sentences that are appropriate to the user's emotions.

[1038] Specifically, the server uses the following hardware and software. For hardware, a smartphone and server are required. For software, Python, OpenAI API, and TextBlob are used. Python is a programming language, and OpenAI API is an interface for using generative AI models. TextBlob is a natural language processing library used for sentiment analysis.

[1039] If a user types "I'm having trouble with my payment, what should I do?", the emotion engine will use TextBlob to analyze the user's emotions. Based on the analysis results, the generative AI means will generate an appropriate prompt and generate an answer using the OpenAI API. For example, if it is determined that the user is feeling stressed, the generative AI means will generate the following prompt:

[1040] Example prompt sentence:

[1041] "Polite response when a user is very angry: My payment isn't working, what should I do?"

[1042] Example of a generated answer:

[1043] "Dear customer, we apologize for any inconvenience caused. If you are having trouble with your payment, please first check your internet connection. If that doesn't resolve the issue, please contact our customer support and we will assist you promptly."

[1044] In this way, it becomes possible to respond appropriately to the user's emotions, improving the user experience and increasing the rate at which the service is continued to be used.

[1045] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1046] Step 1:

[1047] The user enters a question or problem regarding electronic payment.

[1048] Input: The text of the user's question or problem (e.g., "I'm having trouble with my payment, what should I do?")

[1049] Output: The text entered by the user

[1050] Step 2:

[1051] The server receives the user's input text and performs emotion analysis using an emotion engine.

[1052] Input: User-entered text

[1053] Data processing: Analyze the sentiment of the text using TextBlob and calculate the sentiment score

[1054] Output: Sentiment score (e.g. -0.7)

[1055] Step 3:

[1056] The server generates an appropriate prompt sentence based on the emotion score.

[1057] Input: sentiment score, user input text

[1058] Data calculation: Select prompts based on the sentiment score (e.g., if sentiment score is below -0.5, "Polite response for very angry user: I'm having trouble with my payment, what should I do?")

[1059] Output: prompt statement

[1060] Step 4:

[1061] The server uses a generative AI model to generate an answer based on the prompt.

[1062] Input: prompt statement

[1063] Data Calculation: Generate answers based on prompts using the OpenAI API

[1064] Output: The generated answer (e.g., "Dear customer, we apologize for the inconvenience. If you are having trouble with your payment, please first check your internet connection. If that doesn't work, please contact our customer support, and we will assist you promptly.")

[1065] Step 5:

[1066] The server sends the generated answer to the user.

[1067] Input: Generated answer

[1068] Output: The answer sent to the user

[1069] The above processing steps enable appropriate responses according to the user's emotions, improving the user experience and increasing the rate of continued use of the service.

[1070] Example 2

[1071] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1072] Conventional text generation systems generate text without considering the user's emotions, which can result in text that does not match the user's intentions or emotions. Furthermore, they lack the functionality to automatically determine the destination of the generated text, requiring the user to manually specify the destination, which is inefficient. Furthermore, there is a demand for reducing work hours and improving productivity by sending generated text.

[1073] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1074] In this invention, the server includes a generative AI means for generating text based on user input, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, and an emotion analysis means for analyzing the user's emotions and adjusting the tone of the generated text. This makes it possible to automatically generate text that matches the user's emotions and send it to an appropriate destination. It also reduces work hours and improves productivity.

[1075] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1076] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[1077] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1078] The "emotion analysis means" is a means for analyzing the user's emotions and adjusting the tone of the generated text.

[1079] The present invention is a system that generates text based on user input, analyzes the user's emotions to adjust the tone of the text, and sends the text to an appropriate destination. Specific embodiments of this system are described below.

[1080] Hardware and software used

[1081] Generative AI model: An AI model that generates sentences (e.g., GPT-3)

[1082] Sentiment analysis engine: An engine that analyzes user emotions and adjusts the tone of the text

[1083] Mail server: The server that sends the generated document to the specified destination (e.g. Postfix)

[1084] System configuration

[1085] 1. The user sends a request to the system to generate a sentence.

[1086] 2. The device receives the user's request and inputs a prompt sentence into the generative AI model.

[1087] 3. The generative AI model generates sentences based on the prompt.

[1088] 4. The sentiment analysis engine analyzes the user's emotions and adjusts the tone of the generated text based on the results.

[1089] 5. The device receives the adjusted text and sends it to the mail server.

[1090] 6. The mail server forwards the received message to the specified recipient's email address.

[1091] Specific examples

[1092] Example prompt: "Write an email introducing our new product."

[1093] User sentiment: Delighted

[1094] Generated text: "Hello! Introducing our new product! We're super excited about this new product! Come try it out!"

[1095] Processing Details

[1096] 1. A user requests, "Please create an email to introduce a new product."

[1097] 2. The device receives this request and inputs the prompt "Please create an introductory email for our new product" into the generative AI model.

[1098] 3. Based on the prompt, the generative AI model generates the sentence, "Hello! Introducing our new product. We're very excited about this new product. Please try it out!"

[1099] 4. The emotion analysis engine analyzes the user's emotions and determines that the user is happy.

[1100] 5. The sentiment analysis engine adjusts the tone of the generated text to be brighter.

[1101] 6. The device sends the adjusted text to the mail server.

[1102] 7. The mail server forwards the received message to the specified recipient's email address.

[1103] This system makes it possible to automatically generate text that matches the user's emotions and send it to the appropriate recipient, thereby reducing work time and improving productivity.

[1104] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1105] Step 1:

[1106] The user submits a request for sentence generation.

[1107] Input: The user types "Please create an introductory email for our new product" through the terminal interface.

[1108] Output: The device receives the user's request.

[1109] Specific operation: The user enters a prompt sentence into the input field of the terminal and presses the send button.

[1110] Step 2:

[1111] The device receives the request and inputs a prompt into the generative AI model.

[1112] Input: User request: "Please create an email to introduce our new product."

[1113] Output: The prompt sentence is input to the generative AI model.

[1114] Specific operation: The device sends the received prompt text to the API of the generative AI model.

[1115] Step 3:

[1116] A generative AI model generates sentences based on the prompt.

[1117] Input: Prompt text "Please create an email introducing our new product."

[1118] Output: Generated sentence: "Hello! Introducing our new product. We're very excited about this new product. Come try it out!"

[1119] Specific behavior: The generative AI model analyzes the prompt sentence and generates an appropriate sentence.

[1120] Step 4:

[1121] The sentiment analysis engine analyzes the user's sentiment.

[1122] Input: User input data (text or voice).

[1123] Output: The user's emotional state (e.g., happy).

[1124] What it does: The sentiment analysis engine analyzes user input data to identify their emotional state.

[1125] Step 5:

[1126] The sentiment analysis engine adjusts the tone of the text based on the analysis results.

[1127] Input: The generated sentence and the user's emotional state.

[1128] Output: The adjusted sentence.

[1129] What it does: The sentiment analysis engine adjusts the tone of the generated text to match the user's emotions.

[1130] Step 6:

[1131] The device sends the adjusted text to the mail server.

[1132] Input: Adjusted text.

[1133] Output: The text sent to the mail server.

[1134] Specific operation: The device passes the adjusted text to the mail server's sending API.

[1135] Step 7:

[1136] The mail server forwards the document to the specified destination.

[1137] Input: The text and recipient information sent to the mail server.

[1138] Output: The email sent to the destination email address.

[1139] Specific operation: The mail server forwards the received text to the specified recipient's email address.

[1140] (Application example 2)

[1141] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1142] Conventional text generation systems using generative AI were unable to generate text in a tone that reflected the user's emotions, making it difficult to communicate appropriately with the user. Furthermore, there was a lack of a way to appropriately determine the recipient of the generated text, making it difficult to achieve efficient information transmission. In particular, online shopping sites are required to send product promotional emails and campaign emails that reflect the user's emotions, but the technology to achieve this was lacking.

[1143] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1144] In this invention, the server includes a generative AI means for generating text based on user input, a sending means for sending the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, and an emotion engine means for analyzing the user's emotions and adjusting the tone of the text based on the emotions, thereby making it possible to generate and send product promotion emails and campaign emails in a tone that corresponds to the user's emotions.

[1145] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1146] The "transmission means" is a means for transmitting the text generated by the generative AI means to a specified destination.

[1147] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1148] The "emotion engine means" is a means for analyzing the user's emotions and adjusting the tone of the text based on those emotions.

[1149] A "product introduction email" is an email that introduces product information to users.

[1150] "Campaign Email" means an email sent to inform users about a specific campaign or promotion.

[1151] "Tone" refers to the emotional atmosphere and style of expression of a piece of writing.

[1152] To implement this invention, a server, a user terminal, and a generative AI model are used. The server includes generative AI means for generating text based on input from a user, transmission means for transmitting the generated text, destination determination means for determining a destination based on the content of the generated text, and emotion engine means for analyzing the user's emotions and adjusting the tone of the text based on the emotions.

[1153] The user terminal provides an interface for analyzing the user's emotions when the user browses or purchases products. Specifically, a device equipped with a camera and microphone is used to analyze the user's facial expressions and voice. This allows the user's emotional data to be collected and sent to the server.

[1154] The server analyzes the user's emotions using the emotion engine means and determines the tone of the text based on the analysis result. For example, if the emotion engine analyzes that the user is happy, the generative AI means generates text with a bright tone. The generated text is sent to a specified destination using the sending means.

[1155] For example, if a user is browsing an online shopping site on their smartphone and the emotion engine determines that the user is "happy," the generative AI model will generate the following email in a cheerful tone:

[1156] "Hello! The latest smartphone is waiting for you! Equipped with a high-performance camera and long-lasting battery, this model will make your life more fun and convenient. Check it out now!"

[1157] An example of this prompt is:

[1158] User sentiment: happy

[1159] Product information: The latest smartphone, equipped with a high-performance camera and long-lasting battery life. Price: 80,000 yen

[1160] Tone: Bright

[1161] In this way, it is possible to generate and send product promotional emails and campaign emails in a tone that matches the user's emotions, which allows for more personalized communication and is expected to improve customer satisfaction.

[1162] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1163] Step 1:

[1164] The user device collects the user's facial expressions and voice using a camera and microphone, thereby acquiring the user's emotional data. The input is the user's facial expressions and voice data, and the output is emotional data.

[1165] Step 2:

[1166] The user terminal transmits the collected emotion data to the server. The input is emotion data, and the output is the emotion data transmitted to the server.

[1167] Step 3:

[1168] The server analyzes the received emotion data using an emotion engine means to identify the emotion of the user, where the input is the emotion data and the output is the identified emotion of the user (e.g., happy, sad, neutral).

[1169] Step 4:

[1170] The server uses generative AI means to determine the tone of the text based on the user's emotion, where the input is the identified user emotion and the output is the determined tone of the text.

[1171] Step 5:

[1172] The server uses generative AI to generate text for product promotional emails and campaign emails based on product information and the determined tone. The input is the product information and the determined tone, and the output is the generated text.

[1173] Step 6:

[1174] The server uses a destination determination means to determine a destination based on the content of the generated text, with the input being the generated text and the output being the determined destination.

[1175] Step 7:

[1176] The server uses a sending means to send the generated text to the determined destination. The input is the generated text and the determined destination, and the output is the sent email.

[1177] Example 3

[1178] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1179] In conventional systems, users had to manually decide where to send messages, which was inefficient and had a high risk of sending them to the wrong person. Furthermore, the system lacked the ability to automatically determine the appropriate recipient based on the user's emotions, making it difficult to respond appropriately to the user's feelings.

[1180] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a generative AI means for generating a sentence based on an input from a user, a transmission means for transmitting the sentence generated by the generative AI means, a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means, and an emotion analysis means for analyzing the user's emotion and determining a destination based on the result. This makes it possible to automatically generate a sentence based on a prompt sentence input by the user and automatically determine an appropriate destination based on the content of the sentence and the user's emotion.

[1181] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1182] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[1183] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1184] The "emotion analysis means" is a means for analyzing the user's emotions and determining the destination based on the results.

[1185] This invention is a system that generates a sentence based on an input from a user and automatically determines an appropriate destination depending on the content of the sentence and the user's emotions. A specific embodiment of this system will be described below.

[1186] Hardware and software used

[1187] Hardware: Servers, terminals

[1188] Software: Generative AI models (e.g., GPT-4), sentiment analysis engines

[1189] System configuration

[1190] 1. Generative AI methods: Generate sentences based on user input. Use a generative AI model (e.g., GPT-4) to generate natural language sentences based on user-entered prompts.

[1191] 2. Transmission means: Send the generated text. The server has a means to send the generated text to the appropriate destination.

[1192] 3. Destination determination method: The destination is determined based on the content of the generated text. The server analyzes the generated text and determines the destination based on specific keywords or phrases.

[1193] 4. Sentiment analysis means: Analyze the user's emotions and determine the destination based on the results. A sentiment analysis engine is used to analyze the emotions from the user's input and determine the appropriate destination.

[1194] Specific examples

[1195] The user uses the device interface to enter a prompt for the generative AI model, for example, "Please write a detailed description of the new product launch."

[1196] The device sends this prompt to the server. The server inputs the received prompt into the generative AI model to generate a sentence. Based on the prompt, the generative AI model generates a sentence such as, "We are announcing a new product. This new product has been developed using the latest technology."

[1197] Next, the server analyzes the generated text. Specifically, it detects keywords and phrases within the text. For example, it detects the phrase "announcement of a new product." The server determines the destination based on the analysis results. For example, if the text contains the phrase "announcement of a new product," the server decides to send the text to the marketing department's email address.

[1198] Furthermore, the sentiment analysis engine analyzes the user's emotions. For example, if a user is dissatisfied with customer service, the sentiment analysis engine analyzes that emotion and determines the appropriate destination. For example, in response to the prompt, "Please express your dissatisfaction with customer service," the generative AI model generates the sentence, "I am extremely dissatisfied with the recent customer service experience." The sentiment analysis engine analyzes the user's anger and determines that this sentence should be sent to the customer service department.

[1199] In this way, it is possible to automatically generate a sentence based on the prompt sentence entered by the user, and automatically determine an appropriate destination depending on the content of the sentence and the user's emotions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1200] Step 1:

[1201] The user inputs a prompt sentence. The user uses the terminal interface to input a prompt sentence to the generative AI model. For example, the user might input "Please write a detailed description of the new product launch." The input data is the prompt sentence in text format.

[1202] Step 2:

[1203] The terminal sends the prompt text to the server. The terminal uses an HTTP request to send the prompt text to the server. Specifically, it uses a POST request to send the prompt text to the server. The input data is the prompt text entered by the user, and the output data is the prompt text sent to the server.

[1204] Step 3:

[1205] The server generates a sentence using a generative AI model. The server inputs the received prompt sentence into a generative AI model (e.g., GPT-4) to generate a sentence. The generative AI model generates a sentence in natural language based on the prompt sentence. The input data is the prompt sentence, and the output data is the generated sentence. For example, the generated sentence is, "Our company is announcing a new product. This new product has been developed using the latest technology."

[1206] Step 4:

[1207] The server analyzes the generated text. The server inputs the generated text into a text analysis engine to extract keywords and phrases. Specifically, it uses regular expressions and natural language processing libraries to detect the phrase "new product launch." The input data is the generated text, and the output data is the extracted keywords and phrases.

[1208] Step 5:

[1209] The server determines the destination. Based on the analysis results, the server runs a destination determination algorithm. For example, if the phrase "new product launch" is included, the email address of the marketing department is selected. The input data are the extracted keywords and phrases, and the output data are the determined destination.

[1210] Step 6:

[1211] The server sends the text to the determined destination. The server uses the SMTP protocol to send an email to the determined destination. For example, an email is sent to the marketing department's email address saying, "We are announcing a new product. This new product has been developed using the latest technology." The input data is the generated text and the determined destination, and the output data is the email that was sent.

[1212] Step 7:

[1213] The server analyzes the user's emotions. The server uses an emotion analysis engine to analyze emotions from the user's input. For example, if a user is dissatisfied with customer service, the emotion analysis engine analyzes that emotion. The input data is the user's input, and the output data is the analyzed emotion.

[1214] Step 8:

[1215] The server determines the appropriate destination based on the emotion analysis results. For example, if the user is angry, send it to the customer service department. The input data is the analyzed emotion, and the output data is the determined destination.

[1216] Step 9:

[1217] The server sends the text to the determined destination. The server uses the SMTP protocol to send an email to the determined destination. For example, an email can be sent to the customer service department saying, "I'm very unhappy with your recent customer service experience." The input data is the generated text and the determined destination, and the output data is the email sent.

[1218] (Application example 3)

[1219] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1220] Conventional self-driving vehicles have the problem that it is difficult to improve passenger satisfaction because they do not have a system that can respond appropriately based on passenger emotions and comments. In addition, there is a lack of means to quickly respond when passengers are dissatisfied, which can result in a decline in service quality.

[1221] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1222] In this invention, the server includes a generative AI means for generating text based on user input, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion analysis means for analyzing the user's emotion, and an emotion-based destination determination means for determining a destination based on the emotion analyzed by the emotion analysis means. This makes it possible to take appropriate action based on the passenger's emotion and the content of their comments, thereby improving passenger satisfaction. Furthermore, it is possible to quickly respond to passenger dissatisfaction, thereby improving service quality.

[1223] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1224] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[1225] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1226] "Emotion analysis means" is a means for analyzing the user's emotions.

[1227] The "emotion-based destination determination means" is a means for determining a destination based on the emotion analyzed by the emotion analysis means.

[1228] The system for implementing this invention uses the following hardware and software: the hardware uses an in-car camera and microphone, and the software uses Python, the EmotionRecognizer library, the AI ​​Text Generator library, and smtplib (for sending emails).

[1229] The server first acquires passenger data from the in-car camera and microphone. Then, it analyzes the passenger's emotions using the EmotionRecognizer library. The analyzed emotional data is used as input data to generate text using the AI ​​Text Generator library. The generated text is then sent to the appropriate destination via a transmission means.

[1230] As a specific example, the following prompt sentence could be input into a generative AI model:

[1231] If a passenger is talking about a new product in the car:

[1232] "We look forward to the unveiling of our new self-driving vehicle."

[1233] If a passenger complains on board:

[1234] "The air conditioning in this car isn't working, can you do something about it?"

[1235] When these prompts are entered, the generative AI model generates a response and sends an email to the appropriate department, such as the marketing department if the response contains the phrase "new product launch," or the customer service department if the response indicates the passenger is angry.

[1236] This system makes it possible to respond appropriately based on passengers' emotions and comments, thereby improving passenger satisfaction. It also makes it possible to respond quickly when passengers are dissatisfied, thereby improving service quality.

[1237] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1238] Step 1:

[1239] The server collects passenger data from cameras and microphones inside the vehicle.

[1240] Input: Video and audio data from the camera and microphone

[1241] Output: Passenger video and audio data

[1242] Specific operation: Records passengers' facial expressions and comments in real time via camera and microphone.

[1243] Step 2:

[1244] The server uses the EmotionRecognizer library to analyze emotions from the acquired passenger data.

[1245] Input: Passenger video and audio data

[1246] Output: Parsed emotion data (e.g., joy, anger, sadness, etc.)

[1247] Specific operation: Analyzes facial expressions from video data and tone of voice and content of words from audio data to identify emotions.

[1248] Step 3:

[1249] The server uses the AI ​​Text Generator library to generate sentences based on emotion and voice data.

[1250] Input: Parsed emotion data and speech data

[1251] Output: Generated sentence

[1252] Specific operation: Emotional data and voice data are input into the AI ​​model as prompts to generate appropriate sentences.

[1253] Step 4:

[1254] The server determines the destination based on the content of the generated text.

[1255] Input: Generated sentence

[1256] Output: Destination email address

[1257] What it does: Analyzes the generated text, detects keywords such as "new product launch," and identifies the appropriate department (e.g., marketing, customer service).

[1258] Step 5:

[1259] The server uses the transmission means to transmit the generated text to the determined destination.

[1260] Input: Generated text and destination email address

[1261] Output: Email sent

[1262] Specific operation: Uses smtplib to send an email containing the generated text to the specified recipient.

[1263] The above processing steps enable appropriate responses to be taken based on the passenger's emotions and comments, thereby improving passenger satisfaction. In addition, if a passenger becomes dissatisfied, a prompt response can be made, thereby improving service quality.

[1264] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1265] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1266] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1267] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1268] [Third embodiment]

[1269] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1270] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1271] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1272] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1273] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1274] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1275] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1276] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1277] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1278] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1279] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1280] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1281] "Example 1"

[1282] In one embodiment of the present invention, the generative AI uses natural language processing technology to analyze user input and generate sentences based on that. Specifically, if a user inputs, "I would like to create an email about a new product launch," the generative AI extracts the key points and generates sentences using appropriate honorifics and business terms.

[1283] "Example 2"

[1284] The sending means sends the generated text to the specified destination. Specifically, the generative AI sends the generated text to an email server, which then forwards it to the destination email address.

[1285] "Example 3"

[1286] Furthermore, the destination determination means determines the destination based on the content of the generated text. Specifically, if the text generated by the generative AI contains the phrase "announcement of a new product," the destination determination means determines to send it to the email address of the marketing department.

[1287] The processing flow of each embodiment will be described below.

[1288] "Example 1"

[1289] Step 1: A user enters a request into the system: "I want to create an email about a new product launch."

[1290] Step 2: The generative AI uses natural language processing techniques to analyze the user input and extract the key points.

[1291] Step 3: The generative AI generates sentences using appropriate honorifics and business terms based on the extracted key points.

[1292] "Example 2"

[1293] Step 1: The text generated by the generative AI is passed to the sending means.

[1294] Step 2: The sending means sends the generated text to the mail server.

[1295] Step 3: The email server forwards the generated document to the specified recipient's email address.

[1296] "Example 3"

[1297] Step 1: The text generated by the generative AI is passed to the destination determination means.

[1298] Step 2: The destination determination means determines the destination based on the content of the generated text.

[1299] Step 3: Specifically, if the phrase "announcement of new product" is included, the destination determining means determines that it should be sent to the email address of the marketing department.

[1300] Example 1

[1301] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1302] In conventional text generation systems, the process of properly analyzing user input, generating prompts, and generating text is complicated and difficult to perform efficiently. Furthermore, there was a lack of functionality to automatically determine the destination of the generated text, which increased the user's workload. Furthermore, there was a need to reduce work time and improve productivity by sending the generated text.

[1303] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1304] In this invention, the server includes an input means for receiving input from a user, a prompt generation means for analyzing the input from the input means and generating a prompt sentence, a generative AI means for generating a sentence using the prompt sentence generated by the prompt generation means, a transmission means for transmitting the sentence generated by the generative AI means, and a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means. This makes it possible to efficiently analyze the user's input and generate an appropriate prompt sentence to generate the sentence, and further to automatically determine the destination of the generated sentence, thereby reducing the user's effort, shortening work hours, and improving productivity.

[1305] An "input means" is a device or software for receiving input from a user.

[1306] A "prompt generation means" is a device or software that analyzes the user's input received from the input means and generates a prompt sentence to be passed to the generative AI means.

[1307] "Generative AI means" refers to a device or software that uses artificial intelligence technology to generate sentences using prompt sentences generated by a prompt generation means.

[1308] "Transmission means" refers to a device or software for transmitting text generated by the generative AI means.

[1309] The "destination determination means" is a device or software that determines the destination based on the content of the text generated by the generative AI means.

[1310] The present invention relates to a system that receives input from a user, generates a sentence based on the input, and transmits the sentence. A specific embodiment of this system will be described below.

[1311] The server has an input means for receiving input from a user. The user inputs text into an input field through a terminal. For example, the user inputs "I want to create an email about the launch of a new product."

[1312] The device sends the user's input to the server. The server analyzes the received input and generates a prompt sentence using a prompt generation means. This prompt generation means analyzes the input using natural language processing technology and generates a prompt sentence to be passed to a generative AI model (e.g., GPT-4).

[1313] An example of a generated prompt is as follows:

[1314] Write an email about a new product launch. Include the following key points: new product features, release date, price, and how to purchase. Use appropriate honorifics and business terminology.

[1315] The server passes this prompt to the generative AI means, which analyzes the prompt and generates appropriate sentences based on the user's request using natural language processing techniques such as tokenization, part-of-speech tagging, and dependency analysis.

[1316] An example of a generated sentence is as follows:

[1317] Subject: New product announcement

[1318] Dear Customers,

[1319] We would like to express our sincere gratitude for your continued patronage. We are pleased to announce our new product, "XX." This product utilizes the latest technology and aims to provide a more comfortable user experience.

[1320] The release date is XX / XX, and the price is XX yen. You can purchase it on our website or at a retailer near you.

[1321] We sincerely hope for your continued patronage.

[1322] Sincerely,

[1323] The server uses a transmission means to send the generated text to the terminal. The terminal displays the received text to the user. The user can check the displayed text and make corrections or additions as necessary.

[1324] This system can efficiently analyze user input, generate appropriate prompts, and generate sentences. Furthermore, by automatically determining the destination of the generated sentences, it reduces user effort, shortens work time, and improves productivity.

[1325] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1326] Step 1:

[1327] The user provides input through the terminal.

[1328] The user inputs "I want to create an email about the launch of a new product" into the input field of the terminal. This input is written in natural language. The input data is in text format, and the terminal receives this input.

[1329] Step 2:

[1330] The device sends input to the server.

[1331] The terminal sends the user's input as an HTTP request to the server. The input data is in text format, and the server receives this request.

[1332] Step 3:

[1333] The server receives the input and generates a prompt.

[1334] The server analyzes the received input and generates a prompt using a prompt generation method. Specifically, it uses natural language processing technology to tokenize the input text and extract important keywords and phrases. Based on this, it generates a prompt to be passed to the generative AI model. For example, it generates a prompt such as, "Write an email about the launch of a new product. Include the following key points: the new product's features, release date, price, and how to purchase. Use appropriate honorifics and business terminology."

[1335] Step 4:

[1336] The server passes the prompt sentence to the generative AI model, which analyzes it and generates the sentence.

[1337] The server passes the generated prompt sentence to a generative AI model (e.g., GPT-4). The generative AI model analyzes the prompt sentence and generates an appropriate sentence based on the user's request. This analysis uses natural language processing techniques such as tokenization, part-of-speech tagging, and dependency analysis. The generated sentence is returned to the server in text format.

[1338] Step 5:

[1339] The server receives the generated text and sends it to the terminal.

[1340] The server receives the sentences generated by the generative AI model and sends them as an HTTP response to the terminal. The output data is in text format, and the terminal receives this response.

[1341] Step 6:

[1342] The terminal displays the generated text to the user.

[1343] The terminal displays the generated text received from the server to the user. The user can check the displayed text and make corrections or additions as necessary. The output data is in text format and is displayed in a format that the user can visually check.

[1344] (Application example 1)

[1345] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1346] The traditional ad copy creation process was often manual, requiring time and effort, resulting in inefficiency. Additionally, the quality of the ad copy depended on the skill of the person creating it, making it difficult to create consistent, high-quality ad copy.

[1347] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1348] In this invention, the server includes a generative AI means for generating text based on user input, a sending means for sending the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an input means for inputting information for automatically generating advertising copy, and a generation means for analyzing the information input by the input means and generating advertising copy. This automates the process of creating advertising copy, significantly reducing time and labor. It also enables consistent, high-quality advertising copy to be generated quickly.

[1349] "Generative AI methods" are artificial intelligence techniques that generate text based on user input.

[1350] "Transmission means" is a function for transmitting text generated by the generative AI means.

[1351] The "destination determination means" is a function for determining the destination based on the content of the text generated by the generative AI means.

[1352] The "input means" is a function for inputting information for automatically generating advertising copy.

[1353] The "generation means" is a function for analyzing information input by the input means and generating advertising copy.

[1354] A system for carrying out this invention is for automatically generating advertising copy based on input from a user. The system includes a generation AI means, a sending means, a destination determination means, an input means, and a generation means.

[1355] The server uses OpenAI's API as a generative AI tool. Users input information such as the purpose of the ad copy, target audience, and product features via their smartphone or computer. The input tool receives this information and generates prompt text.

[1356] The generating means transmits the generated prompt text to the OpenAI API to generate advertising copy. The generated advertising copy is transmitted to the user by the transmitting means. The destination determining means determines an appropriate destination based on the content of the generated advertising copy.

[1357] As a concrete example, consider the case of generating ad copy for a new smartphone. The user enters the following information:

[1358] Product Name: New Smartphone

[1359] Target audience: Young people

[1360] Features: High-resolution camera, long battery life, stylish design

[1361] An example of a prompt generated based on this information is as follows:

[1362] Product Name: New Smartphone

[1363] Target audience: Young people

[1364] Features: High-resolution camera, long battery life, stylish design

[1365] Use this information to generate effective ad copy.

[1366] The server sends this prompt text to OpenAI's API to obtain the generated ad copy. The obtained ad copy is then sent to the user via a sending method. This automates the ad copy creation process, significantly reducing time and effort. It also enables consistent, high-quality ad copy to be generated quickly.

[1367] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1368] Step 1:

[1369] The user uses a smartphone or computer to input information such as the purpose of the ad copy, the target audience, and the product's features. The input information is sent to the server. The input data includes the product name, target audience, and features.

[1370] Step 2:

[1371] The server analyzes the received input data and generates a prompt. Specifically, it creates a prompt for generating advertising copy based on the input product name, target audience, and features. The generated prompt will have the following format:

[1372] Product Name: New Smartphone

[1373] Target audience: Young people

[1374] Features: High-resolution camera, long battery life, stylish design

[1375] Use this information to generate effective ad copy.

[1376] Step 3:

[1377] The server sends the generated prompt text to OpenAI's API, which generates ad copy based on the prompt text. The input data is the prompt text, and the output data is the generated ad copy.

[1378] Step 4:

[1379] The server receives the ad copy returned from the OpenAI API. The received ad copy is temporarily stored on the server.

[1380] Step 5:

[1381] The server determines the destination based on the content of the generated advertisement copy. The destination determination means analyzes the content of the advertisement copy and selects an appropriate destination. For example, if the advertisement copy is aimed at young people, a platform that is frequently used by young people is selected.

[1382] Step 6:

[1383] The server sends the generated advertising copy to the determined destination. The sending means converts the advertising copy into an appropriate format and sends it to the selected destination, so that the advertising copy reaches the target audience.

[1384] Step 7:

[1385] The user can check the sent ad copy and make corrections or regenerate it as necessary. If the user makes corrections, the process will be repeated from step 1.

[1386] Example 2

[1387] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1388] Conventional text generation systems require users to manually send the text they generate, which reduces work efficiency. Furthermore, the process of determining recipients and sending emails is cumbersome, placing a heavy burden on users. This creates challenges in terms of reducing work time and improving productivity.

[1389] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1390] In this invention, the server includes a generative AI means for generating text based on input from a user, a transmission means for transmitting the generated text, a means for transmitting the generated text to the server, a means for transferring the text received by the server to a mail server, and a means for the mail server to send the text to a specified destination. This allows text to be automatically generated based on a prompt text entered by a user and sent to a specified destination, thereby improving work efficiency and reducing the burden on the user.

[1391] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1392] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[1393] The "means for transmitting to the server" refers to a means for transmitting the text generated by the generative AI means to the server.

[1394] A "server" is a computer system that processes text received from a generative AI means and forwards it to a mail server.

[1395] "Means for transferring to the mail server" refers to the means by which the server transfers the received text to the mail server.

[1396] A "mail server" is a server that sends documents transferred from the server to a specified destination.

[1397] "Means for sending to the specified destination" refers to the means by which the mail server sends the text to the specified destination.

[1398] A "prompt" is an instruction that a user inputs to a generative AI means.

[1399] The present invention is a system that generates a sentence based on a prompt sentence entered by a user and automatically sends the sentence to a specified destination. A specific embodiment of this system will be described below.

[1400] First, the user inputs a prompt through the terminal interface, for example, "Please write an email introducing our new product." This prompt is an instruction for the generative AI model and determines the content of the text to be generated.

[1401] Next, the device receives the user's input and sends a prompt to the generative AI model. At this time, the device accesses the API of the generative AI model via the Internet. For example, OpenAI's GPT-4 can be used as the generative AI model.

[1402] The generative AI model analyzes the received prompt and generates an appropriate sentence, such as, "Hello, we'd like to introduce our new product. This product utilizes the latest technology and will make your daily life more convenient. Please give it a try."

[1403] The generated text is sent from the terminal to the server. The terminal sends data to the server using an HTTP request. The server connects to the mail server using the SMTP protocol to transfer the received text to the mail server and sends the text.

[1404] The mail server sends the received text to the specified destination email address. For example, if the destination is "example@example.com", the mail server will send an email containing the generated text to this address.

[1405] This system allows users to easily use generative AI models to generate text and send it to a specified destination, improving work efficiency and reducing the burden on users.

[1406] Examples of specific prompts include:

[1407] "Please create an email to introduce a new product."

[1408] Please prepare the minutes of the meeting.

[1409] Write a thank you letter to your customers.

[1410] In this way, users can create and quickly send texts that meet a variety of needs.

[1411] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1412] Step 1:

[1413] The user enters a prompt sentence through the terminal interface.

[1414] Specifically, the user opens a web browser on the device and enters "Please create an introductory email for our new product" into a dedicated input form.

[1415] Input: Prompt sentence (e.g. "Please create an email introducing our new product")

[1416] Output: The prompt statement is typed into the terminal.

[1417] Step 2:

[1418] The device receives user input and sends prompts to the generative AI model.

[1419] Specifically, the device sends an HTTP POST request to the API endpoint of the generative AI model over the Internet, which includes a prompt.

[1420] Input: prompt statement

[1421] Output: The prompt sentence is sent to the generative AI model.

[1422] Step 3:

[1423] A generative AI model analyzes the prompt and generates an appropriate sentence.

[1424] Specifically, the generative AI model analyzes the prompt and generates the sentence, "Hello, we'd like to introduce our new product. This product utilizes the latest technology and will make your daily life more convenient. Please give it a try."

[1425] Input: prompt statement

[1426] Output: Generated sentence

[1427] Step 4:

[1428] The terminal receives the generated text and sends it to the server.

[1429] Specifically, the device receives the generated text and sends an HTTP POST request to the server. This request includes the generated text.

[1430] Input: Generated sentence

[1431] Output: The generated text is sent to the server.

[1432] Step 5:

[1433] The server forwards the received text to the mail server.

[1434] Specifically, the server connects to a mail server using the SMTP protocol and sends the generated text.

[1435] Input: Generated sentence

[1436] Output: The generated text is sent to the mail server.

[1437] Step 6:

[1438] The mail server sends the message to the specified address.

[1439] Specifically, the mail server sends the received text to the specified destination email address. For example, if the destination is "example@example.com", the mail server will send an email containing the generated text to this address.

[1440] Input: Generated text, recipient's email address

[1441] Output: The generated text is sent to the specified destination.

[1442] (Application example 2)

[1443] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1444] Conventional security systems often lack the means to respond quickly and appropriately when an anomaly is detected. Furthermore, responses after an anomaly is often performed manually, which can lead to delays and human error. This reduces the reliability of security and reduces its effectiveness in situations where a rapid response is required.

[1445] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1446] In this invention, the server includes generative AI means for generating sentences based on input from a user, transmission means for transmitting the sentences generated by the generative AI means, destination determination means for determining a destination based on the content of the sentences generated by the generative AI means, anomaly detection means for acquiring data from a sensor and detecting anomalies, and warning message generation means for generating a warning message when an anomaly is detected. This makes it possible to automatically generate a warning message when an anomaly is detected and quickly send it to an appropriate destination.

[1447] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1448] The "transmission means" is a means for transmitting the text generated by the generative AI means to a specified destination.

[1449] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1450] The "abnormality detection means" is a means for acquiring data from the sensor and detecting abnormalities.

[1451] The "warning message generating means" is a means for generating a warning message when an abnormality is detected.

[1452] A system for implementing this invention includes a generative AI means for generating text based on input from a user, a transmission means for transmitting the generated text, a destination determination means for determining a destination based on the content of the generated text, anomaly detection means for acquiring data from a sensor and detecting anomalies, and a warning message generation means for generating a warning message when an anomaly is detected.

[1453] Hardware and software used

[1454] Hardware: smartphones, security cameras, sensors

[1455] Software: Python, smtplib (email sending library), generative AI model, module for acquiring data from sensors

[1456] Data processing and calculation

[1457] 1. Data acquisition from sensors: Acquiring data in real time from sensors, for example, security cameras capturing video data.

[1458] 2. Anomaly detection: The acquired data is analyzed using anomaly detection means, and if an anomaly is detected, a flag is raised.

[1459] 3. Warning message generation: If an abnormality is detected, a warning message is generated using generative AI methods. For example, a message such as "A suspicious person has been detected. Please check immediately" can be generated.

[1460] 4. Determining destination: Based on the content of the generated warning message, the destination determination means determines the appropriate destination.

[1461] 5. Send email: The generated warning message is sent by email to the determined recipient using a sending means.

[1462] Specific examples

[1463] For example, if a security camera detects a suspicious person, the video data will be analyzed and the generative AI will generate a warning message stating, "A suspicious person has been detected. Please check immediately," and send it to a specified email address.

[1464] Prompt Sentence Examples

[1465] Analyze security camera footage and generate alert messages to be sent if a suspicious person is detected.

[1466] In this way, the present invention provides a system for quickly and appropriately responding when an abnormality is detected, thereby improving the reliability of security.

[1467] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1468] Step 1:

[1469] Acquiring data from sensors

[1470] The server receives data from sensors in real time. The input is raw data from the sensors, and the output is data converted into an analyzable format. Specifically, a security camera captures video data and sends it to the server.

[1471] Step 2:

[1472] Anomaly detection

[1473] The server analyzes the acquired data using anomaly detection means and sets a flag if an anomaly is detected. The input is the data acquired in step 1, and the output is the result of the anomaly detection (whether an anomaly was detected or not). Specifically, it analyzes the video data and detects suspicious individuals or abnormal behavior.

[1474] Step 3:

[1475] Warning message generation

[1476] If an anomaly is detected, the server generates a warning message using generative AI means. The input is the anomaly detection result and data from the sensor, and the output is the generated warning message. Specifically, it generates a message saying, "A suspicious person has been detected. Please check immediately."

[1477] Step 4:

[1478] Determining destination

[1479] The server's destination determination means determines the appropriate destination based on the content of the generated warning message. The input is the generated warning message, and the output is the determined destination address. Specifically, the content of the warning message is analyzed, and the email address of the appropriate person in charge is selected.

[1480] Step 5:

[1481] Send email

[1482] The server sends the generated warning message to the determined destination by email using a sending means. The input is the determined destination address and the generated warning message, and the output is the status of transmission completion. The specific operation is to send the email using an SMTP server.

[1483] Example 3

[1484] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1485] In conventional systems, when generating text based on information entered by a user, it was difficult to automatically determine the appropriate destination based on the content of the generated text. Furthermore, the destination of the generated text had to be determined manually, resulting in a decrease in work efficiency. Furthermore, the system lacked the functionality to automatically determine the appropriate destination when specific phrases were included, making it difficult to improve work productivity.

[1486] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1487] In this invention, the server includes a generation AI means for generating a sentence based on an input from a user, a transmission means for transmitting the sentence generated by the generation AI means, and a destination determination means for determining a destination based on the content of the sentence generated by the generation AI means. This makes it possible to automatically determine an appropriate destination based on the content of the generated sentence, thereby improving business efficiency. Furthermore, by automatically determining a destination when a specific phrase is included, business productivity can be improved.

[1488] "Generative AI means" is an artificial intelligence function that generates sentences based on input from the user.

[1489] The "transmission means" is a function for transmitting the text generated by the generation AI means.

[1490] The "destination determination means" is a function that determines the destination based on the content of the text generated by the generation AI means.

[1491] A "user" is a user who inputs a prompt sentence to the system.

[1492] A "prompt sentence" is an instruction sentence that the user inputs to the generation AI means.

[1493] The "particular phrase" is a keyword or expression that is important when analyzed by the destination determination means.

[1494] "Working time" is the time an employee spends performing work.

[1495] "Productivity" is an indicator that shows the efficiency and results of work.

[1496] This invention is a system that generates a sentence based on a prompt sentence entered by a user and automatically determines an appropriate destination depending on the content of the sentence. A specific embodiment of this system will be described below.

[1497] System configuration

[1498] The system consists of the following main components:

[1499] 1. Generation AI means

[1500] 2. Transmission Method

[1501] 3. How to determine the destination

[1502] Generation AI means

[1503] The generative AI means has the function of generating sentences based on input from the user. This function is realized using a generative AI model such as OpenAI's GPT-3. When the user inputs a prompt sentence, the generative AI means generates an appropriate sentence based on the prompt sentence.

[1504] Transmission method

[1505] The sending means is a function for sending the text generated by the generating AI means. This function is realized using an email system or a messaging system. The generated text is sent to the destination determined by the destination determination means.

[1506] Destination determination method

[1507] The destination determination means has a function of analyzing the content of the text generated by the generation AI means and determining an appropriate destination. This function uses natural language processing technology to analyze the text and check whether it contains a specific phrase. For example, if the phrase "announcement of a new product" is included, the destination determination means determines that the text should be sent to the email address of the marketing department.

[1508] Specific examples

[1509] Below are some examples of prompts and their results:

[1510] Prompt Sentence Examples

[1511] "Please explain the features of your new smartphone."

[1512] Processing results

[1513] 1. The user enters a prompt statement.

[1514] 2. The generative AI means generates a sentence based on the prompt, such as:

[1515] "We're announcing a new product. The new smartphone features a modern processor, improved battery life, and a significantly improved camera."

[1516] 3. The generated text is passed to the destination determination means.

[1517] 4. The destination determination means analyzes the sentence and determines that it contains the phrase "new product announcement."

[1518] 5. The destination determination means determines that the email should be sent to the marketing department's email address.

[1519] 6. The text is sent to the destination determined by the sending method.

[1520] This system automatically sends a message generated based on a prompt entered by a user to an appropriate destination, thereby improving work efficiency and productivity. The flow of the specific process in the third embodiment will be described with reference to FIG.

[1521] Step 1:

[1522] The user enters a prompt statement.

[1523] The user accesses the system's web interface, enters "Please describe the features of your new smartphone" in the text box, and clicks the submit button.

[1524] Input: prompt statement

[1525] Output: Prompt for user input

[1526] Step 2:

[1527] The server generates sentences using a generative AI model.

[1528] The server receives the prompt sentence entered by the user and passes it to a generative AI model (e.g., GPT-3). The generative AI model generates an appropriate sentence based on the prompt sentence and returns it to the server.

[1529] Input: prompt statement

[1530] Output: Generated sentence

[1531] Step 3:

[1532] The server passes the generated text to the destination determination means.

[1533] The server receives the generated text and passes it to the destination determination means, which executes an algorithm to analyze the content of the text.

[1534] Input: Generated sentence

[1535] Output: The sentence to be analyzed

[1536] Step 4:

[1537] The destination determining means analyzes the text.

[1538] The destination determination means analyzes the generated text and checks whether it contains the phrase "new product announcement." For example, it uses natural language processing technology to tokenize the text and search for specific keywords.

[1539] Input: Text to be analyzed

[1540] Output: Analysis results (presence or absence of specific phrases)

[1541] Step 5:

[1542] The destination determination means determines the destination.

[1543] The destination determination means determines the destination based on the analysis result. For example, if the phrase "announcement of a new product" is included, the destination determination means selects the email address of the marketing department.

[1544] Input: Analysis results

[1545] Output: Determined destination

[1546] Step 6:

[1547] The server sends the text to the determined destination.

[1548] The server sends the text to the destination determined by the destination determination means, for example, to the marketing department's email address.

[1549] Input: Determined destination, generated text

[1550] Output: Email sent

[1551] (Application example 3)

[1552] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1553] In conventional text generation systems using generative AI, it is difficult to appropriately determine the destination of the generated text, and there is a lack of means to send the generated text quickly and efficiently. This has led to issues such as insufficient improvements in work efficiency and productivity.

[1554] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a generative AI means for generating a sentence based on an input from a user, a sending means for sending the sentence generated by the generative AI means, a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means, and an email sending means for sending the generated sentence by email. This makes it possible to automatically determine an appropriate destination based on the content of the generated sentence and send it by email quickly and efficiently.

[1555] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1556] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[1557] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1558] The "email sending means" is a means for sending the generated text by email.

[1559] A system for implementing this invention includes a generative AI means for generating text based on input from a user, a sending means for sending the generated text, a destination determination means for determining a destination based on the content of the generated text, and an email sending means for sending the generated text by email.

[1560] The server uses OpenAI's GPT-3 as a generative AI method. GPT-3 generates the content of an advertising campaign based on a prompt entered by the user. For example, if a user enters the prompt "Please generate advertising copy for a new product launch," GPT-3 will generate advertising copy for the new product launch.

[1561] The generated text is temporarily stored by the sending means. Thereafter, the destination determining means analyzes the content of the generated text and determines an appropriate destination. For example, if the generated text contains the phrase "announcement of a new product," the destination determining means determines the email address of the marketing department as the destination.

[1562] The email sending means sends the generated text to the determined recipient by email using the Python smtplib library. The server connects to the SMTP server and sends the email using the appropriate authentication information.

[1563] As a concrete example, the following prompt sentence is input to the generative AI model:

[1564] "Generate advertising copy for a new product launch."

[1565] By inputting this prompt, the generative AI method can generate advertising copy for the new product launch, determine appropriate recipients based on the content of the copy, and distribute it via email, thereby enabling the content of advertising campaigns to be distributed quickly and efficiently.

[1566] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1567] Step 1:

[1568] The user inputs a prompt using a terminal. Specifically, the user inputs the prompt "Please generate advertising copy for the launch of a new product." This input is sent to the system.

[1569] Step 2:

[1570] The server uses a generative AI tool (OpenAI's GPT-3) to generate a sentence based on the prompt from the user. The input prompt is sent to GPT-3, and the generated ad copy is received. This ad copy is then passed on to the next processing step.

[1571] Step 3:

[1572] The server temporarily stores the generated copy of the advertisement by a transmission means. Specifically, the server stores the generated copy of the advertisement in a database or memory. The stored copy of the advertisement is passed to the next processing step.

[1573] Step 4:

[1574] The server uses the destination determination means to analyze the content of the generated advertisement copy and determine the appropriate destination. Specifically, it checks whether the advertisement copy contains the phrase "announcement of new product," and if so, determines the email address of the marketing department as the destination. This determined destination is passed to the next processing step.

[1575] Step 5:

[1576] The server uses the email sending mechanism to send the generated ad copy to the determined recipients by email. Specifically, it uses Python's smtplib library to connect to an SMTP server and sends the email using the appropriate authentication information. This process sends the ad copy to the marketing department.

[1577] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1578] "Example 1"

[1579] In one embodiment of the present invention, the generative AI means includes an emotion engine that recognizes a user's emotion. The emotion engine analyzes the emotion from the user's input (e.g., speech or text) and provides the results to the generative AI means. The generative AI means uses this emotion information to generate sentences that are appropriate to the user's emotion. For example, if the user feels angry, the generative AI means uses that information to generate sentences with a more polite tone.

[1580] "Example 2"

[1581] In another embodiment of the present invention, the emotion engine adjusts the tone of the sentence based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion and determines the tone of the sentence based on the analysis result. For example, if the user feels happy, the emotion engine uses that information to generate a sentence with a lighter tone.

[1582] "Example 3"

[1583] In yet another embodiment of the present invention, the emotion engine determines the destination based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion and determines the destination based on the analysis result. For example, if the user feels angry, the emotion engine uses the information to determine that the email should be sent to a department (e.g., customer service department) that may be able to resolve the issue.

[1584] The processing flow of each embodiment will be described below.

[1585] "Example 1"

[1586] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[1587] Step 2: The emotion engine analyzes the emotion from the user's input. The analysis result indicates the user's emotional state.

[1588] Step 3: The generative AI means receives the analysis results from the emotion engine and generates text based on them, in a tone that matches the user's emotions.

[1589] "Example 2"

[1590] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[1591] Step 2: The emotion engine analyzes the emotion from the user's input and determines the tone of the text based on the results.

[1592] Step 3: The generative AI receives tone information from the emotion engine and generates text based on that information. At this time, the text is generated in a tone that matches the user's emotions.

[1593] "Example 3"

[1594] Step 1: The user provides input to the system. This input can be voice or text, and reflects the user's emotions.

[1595] Step 2: The emotion engine analyzes the emotion from the user's input and determines the destination based on the results.

[1596] Step 3: The generative AI means receives the destination information from the emotion engine, generates a sentence based on that information, and sends it to the specified destination.

[1597] Example 1

[1598] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1599] Conventional text generation systems were unable to take the user's emotions into account when generating text based on user input, resulting in generated text that was inappropriate for the user's intentions or emotions. Furthermore, they lacked the functionality to automatically determine the destination of the generated text, requiring users to manually specify the destination. This resulted in reduced work efficiency and a lack of productivity.

[1600] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1601] In this invention, the server includes an input means for receiving input from a user, an analysis means for analyzing data from the input means, a generative AI means for generating text based on the data analyzed by the analysis means, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion analysis means for analyzing the user's emotions, and an emotion response generation means for generating text based on the emotion information analyzed by the emotion analysis means. This makes it possible to generate appropriate text taking the user's emotions into consideration and automatically determine the destination.

[1602] An "input means" is a device or software for receiving input from a user.

[1603] "Analysis means" refers to a device or software for analyzing data received from an input means.

[1604] "Generative AI means" refers to a device or software that uses artificial intelligence technology to generate text based on data analyzed by analytical means.

[1605] "Transmission means" refers to a device or software for transmitting text generated by the generative AI means.

[1606] The "destination determination means" is a device or software for determining the destination based on the content of the sentence generated by the generative AI means.

[1607] "Emotion analysis means" refers to a device or software for analyzing emotions from user input.

[1608] The "emotion correspondence generation means" is a device or software for generating sentences based on the emotion information analyzed by the emotion analysis means.

[1609] MODE FOR CARRYING OUT THE INVENTION

[1610] The present invention relates to a system that receives input from a user, generates appropriate sentences based on the input, and transmits them. A specific embodiment of this system will be described below.

[1611] server

[1612] The server functions as a platform for running generative AI. It receives input from users and analyzes it using natural language processing technology. Specifically, the server uses software such as Python and TensorFlow to analyze the text entered by the user and extract its key points. For example, if a user enters, "I would like to create an email about the launch of a new product," the server extracts the key points and generates a sentence using appropriate honorifics and business terminology.

[1613] Furthermore, the server analyzes the user's emotions using an emotion engine. The emotion engine analyzes emotions from the user's input (e.g., voice or text) and provides the results to the generative AI. The generative AI uses this emotion information to generate sentences that match the user's emotions. For example, if the user feels angry, the generative AI uses that information to generate sentences with a more polite tone.

[1614] Terminal

[1615] The terminal provides an interface for users to input data. When a user inputs text or voice data through the terminal, the data is sent to the server. The terminal converts the data entered by the user into an appropriate format and sends it to the server. For example, if a user inputs "I would like to create an email about the launch of a new product" by voice, the terminal converts the voice data into text and sends it to the server.

[1616] User

[1617] The user inputs text via their device to generate it using the generative AI. For example, if the user inputs "I want to create an email about a new product launch," the input is sent to the server via their device. The user can review the generated text and make corrections as necessary. If the input contains the user's emotions, the emotion engine analyzes them and provides them to the generative AI. For example, if the user feels angry, the generative AI uses that information to generate text with a more polite tone.

[1618] Specific examples

[1619] 1. The user types into the terminal, "I want to create an email about a new product launch."

[1620] 2. The terminal converts the input into text format and sends it to the server.

[1621] 3. The server uses Python and TensorFlow to parse the input and extract key points.

[1622] 4. The server generates the following sentence using appropriate honorifics and business terms:

[1623] "Thank you for your continued support. We would like to inform you about the launch of our new product. Details are as follows."

[1624] Examples of emotion engines

[1625] 1. A user angrily types into their device, "I want to create an email about a new product launch."

[1626] 2. The device converts the speech into text and sends it to the server.

[1627] 3. The server uses an emotion engine to analyze the user's emotions and detects anger.

[1628] 4. The server provides this emotional information to a generative AI, which generates a polite sentence like this:

[1629] "Thank you for your continued support. We would like to inform you about the launch of a new product. Details are as follows. We appreciate your understanding."

[1630] In this way, the system generates appropriate sentences based on the user's input and emotions and provides them to the user.

[1631] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1632] Step 1:

[1633] The user provides input

[1634] A user inputs text or voice data through a terminal. For example, the user inputs "I want to create an email about the launch of a new product." This input may include the user's intentions and emotions. The input data is sent to the terminal in text or voice format.

[1635] Step 2:

[1636] The device receives input and sends it to the server

[1637] The device receives input from the user and converts it into an appropriate format. For example, in the case of voice input, the device converts the voice into text. The converted data is then sent from the device to the server. Specifically, the smartphone's voice recognition function converts the voice into text and sends the text to the server.

[1638] Step 3:

[1639] The server parses the input

[1640] The server analyzes the received input data using natural language processing technology. Specifically, it uses libraries such as Python and TensorFlow to extract the main points of the input text. For example, the server analyzes the text "I would like to create an email about the launch of a new product" and extracts the main points "launching a new product" and "composing an email." The input is text data, and the output is data with the extracted main points.

[1641] Step 4:

[1642] The server analyzes emotions using an emotion engine.

[1643] The server uses an emotion engine to analyze emotions from user input. The emotion engine detects the user's emotions from input text and voice and provides the results to the generative AI. Specifically, the server detects the user's impatience from the text "I want to create an email about the launch of a new product." The input is text data, and the output is emotional information.

[1644] Step 5:

[1645] The server generates text using generative AI

[1646] The server uses generative AI to generate appropriate text based on the analysis results and emotional information. The generative AI uses a pre-trained model to generate text that matches the user's intentions. Specifically, the server generates the following text based on the main point, "I want to write an email about the launch of a new product," and the emotional information, "I'm anxious": "Thank you for your continued support. We're writing to let you know about the launch of our new product. Details are as follows." The input is the main point and emotional information, and the output is the generated text.

[1647] Step 6:

[1648] The server sends the generated text to the terminal.

[1649] The server sends the generated text to the terminal. The terminal displays the received text to the user. Specifically, the server sends the generated text to the smartphone, which then displays the text on its screen. The input is the generated text, and the output is the text displayed on the terminal.

[1650] Step 7:

[1651] The user reviews the generated text and corrects it if necessary.

[1652] The user checks the generated sentence displayed on the device and makes corrections as necessary. Once corrections are complete, the final sentence can be sent. Specifically, the user checks the sentence displayed on the smartphone screen and corrects "The details are as follows" to "The details are as follows." The input is the generated sentence, and the output is the corrected final sentence.

[1653] (Application example 1)

[1654] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1655] In traditional electronic payment services, it can be difficult to provide a prompt and appropriate response when a user inputs a problem or question. Furthermore, a uniform response is given without considering the user's feelings, which can leave the user dissatisfied. This can lead to a poor user experience and a decrease in the rate of continued use of the service.

[1656] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1657] In this invention, the server includes generative AI means for generating text based on input from a user, transmission means for transmitting the text generated by the generative AI means, destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion engine for analyzing the user's emotions, and generative AI means for generating text using emotion information analyzed by the emotion engine. This enables appropriate responses according to the user's emotions, improving the user experience and increasing the rate of continued use of the service.

[1658] "Generative AI methods" refers to artificial intelligence technologies that generate text based on user input.

[1659] "Transmission means" refers to the function for transmitting text generated by the generative AI means.

[1660] "Destination determination means" refers to a function that determines the destination based on the content of the text generated by the generative AI means.

[1661] "Emotion engine" refers to technology for analyzing emotions from user input.

[1662] "Emotional information" refers to data regarding a user's emotions analyzed by the emotion engine.

[1663] As an embodiment of the present invention, an emotion-responsive electronic payment assistant system will be described as an example. This system includes a generative AI means for generating text based on user input, a sending means for sending the generated text, a destination determination means for determining a destination based on the content of the generated text, an emotion engine for analyzing the user's emotions, and a generative AI means for generating text using emotion information.

[1664] When a user inputs a question or problem about electronic payment, the server uses the generative AI means to analyze the content and provide an appropriate answer or solution. The emotion engine analyzes the emotion from the user's input text and provides the result to the generative AI means. The generative AI means uses this emotion information to generate sentences that are appropriate to the user's emotions.

[1665] Specifically, the server uses the following hardware and software. For hardware, a smartphone and server are required. For software, Python, OpenAI API, and TextBlob are used. Python is a programming language, and OpenAI API is an interface for using generative AI models. TextBlob is a natural language processing library used for sentiment analysis.

[1666] If a user types "I'm having trouble with my payment, what should I do?", the emotion engine will use TextBlob to analyze the user's emotions. Based on the analysis results, the generative AI means will generate an appropriate prompt and generate an answer using the OpenAI API. For example, if it is determined that the user is feeling stressed, the generative AI means will generate the following prompt:

[1667] Example prompt sentence:

[1668] "Polite response when a user is very angry: My payment isn't working, what should I do?"

[1669] Example of a generated answer:

[1670] "Dear customer, we apologize for any inconvenience caused. If you are having trouble with your payment, please first check your internet connection. If that doesn't resolve the issue, please contact our customer support and we will assist you promptly."

[1671] In this way, it becomes possible to respond appropriately to the user's emotions, improving the user experience and increasing the rate at which the service is continued to be used.

[1672] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1673] Step 1:

[1674] The user enters a question or problem regarding electronic payment.

[1675] Input: The text of the user's question or problem (e.g., "I'm having trouble with my payment, what should I do?")

[1676] Output: The text entered by the user

[1677] Step 2:

[1678] The server receives the user's input text and performs emotion analysis using an emotion engine.

[1679] Input: User-entered text

[1680] Data processing: Analyze the sentiment of the text using TextBlob and calculate the sentiment score

[1681] Output: Sentiment score (e.g. -0.7)

[1682] Step 3:

[1683] The server generates an appropriate prompt sentence based on the emotion score.

[1684] Input: sentiment score, user input text

[1685] Data calculation: Select prompts based on the sentiment score (e.g., if sentiment score is below -0.5, "Polite response for very angry user: I'm having trouble with my payment, what should I do?")

[1686] Output: prompt statement

[1687] Step 4:

[1688] The server uses a generative AI model to generate an answer based on the prompt.

[1689] Input: prompt statement

[1690] Data Calculation: Generate answers based on prompts using the OpenAI API

[1691] Output: The generated answer (e.g., "Dear customer, we apologize for the inconvenience. If you are having trouble with your payment, please first check your internet connection. If that doesn't work, please contact our customer support, and we will assist you promptly.")

[1692] Step 5:

[1693] The server sends the generated answer to the user.

[1694] Input: Generated answer

[1695] Output: The answer sent to the user

[1696] The above processing steps enable appropriate responses according to the user's emotions, improving the user experience and increasing the rate of continued use of the service.

[1697] Example 2

[1698] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1699] Conventional text generation systems generate text without considering the user's emotions, which can result in text that does not match the user's intentions or emotions. Furthermore, they lack the functionality to automatically determine the destination of the generated text, requiring the user to manually specify the destination, which is inefficient. Furthermore, there is a demand for reducing work hours and improving productivity by sending generated text.

[1700] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1701] In this invention, the server includes a generative AI means for generating text based on user input, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, and an emotion analysis means for analyzing the user's emotions and adjusting the tone of the generated text. This makes it possible to automatically generate text that matches the user's emotions and send it to an appropriate destination. It also reduces work hours and improves productivity.

[1702] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1703] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[1704] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1705] The "emotion analysis means" is a means for analyzing the user's emotions and adjusting the tone of the generated text.

[1706] The present invention is a system that generates text based on user input, analyzes the user's emotions to adjust the tone of the text, and sends the text to an appropriate destination. Specific embodiments of this system are described below.

[1707] Hardware and software used

[1708] Generative AI model: An AI model that generates sentences (e.g., GPT-3)

[1709] Sentiment analysis engine: An engine that analyzes user emotions and adjusts the tone of the text

[1710] Mail server: The server that sends the generated document to the specified destination (e.g. Postfix)

[1711] System configuration

[1712] 1. The user sends a request to the system to generate a sentence.

[1713] 2. The device receives the user's request and inputs a prompt sentence into the generative AI model.

[1714] 3. The generative AI model generates sentences based on the prompt.

[1715] 4. The sentiment analysis engine analyzes the user's emotions and adjusts the tone of the generated text based on the results.

[1716] 5. The device receives the adjusted text and sends it to the mail server.

[1717] 6. The mail server forwards the received message to the specified recipient's email address.

[1718] Specific examples

[1719] Example prompt: "Write an email introducing our new product."

[1720] User sentiment: Delighted

[1721] Generated text: "Hello! Introducing our new product! We're super excited about this new product! Come try it out!"

[1722] Processing Details

[1723] 1. A user requests, "Please create an email to introduce a new product."

[1724] 2. The device receives this request and inputs the prompt "Please create an introductory email for our new product" into the generative AI model.

[1725] 3. Based on the prompt, the generative AI model generates the sentence, "Hello! Introducing our new product. We're very excited about this new product. Please try it out!"

[1726] 4. The emotion analysis engine analyzes the user's emotions and determines that the user is happy.

[1727] 5. The sentiment analysis engine adjusts the tone of the generated text to be brighter.

[1728] 6. The device sends the adjusted text to the mail server.

[1729] 7. The mail server forwards the received message to the specified recipient's email address.

[1730] This system makes it possible to automatically generate text that matches the user's emotions and send it to the appropriate recipient, thereby reducing work time and improving productivity.

[1731] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1732] Step 1:

[1733] The user submits a request for sentence generation.

[1734] Input: The user types "Please create an introductory email for our new product" through the terminal interface.

[1735] Output: The device receives the user's request.

[1736] Specific operation: The user enters a prompt sentence into the input field of the terminal and presses the send button.

[1737] Step 2:

[1738] The device receives the request and inputs a prompt into the generative AI model.

[1739] Input: User request: "Please create an email to introduce our new product."

[1740] Output: The prompt sentence is input to the generative AI model.

[1741] Specific operation: The device sends the received prompt text to the API of the generative AI model.

[1742] Step 3:

[1743] A generative AI model generates sentences based on the prompt.

[1744] Input: Prompt text "Please create an email introducing our new product."

[1745] Output: Generated sentence: "Hello! Introducing our new product. We're very excited about this new product. Come try it out!"

[1746] Specific behavior: The generative AI model analyzes the prompt sentence and generates an appropriate sentence.

[1747] Step 4:

[1748] The sentiment analysis engine analyzes the user's sentiment.

[1749] Input: User input data (text or voice).

[1750] Output: The user's emotional state (e.g., happy).

[1751] What it does: The sentiment analysis engine analyzes user input data to identify their emotional state.

[1752] Step 5:

[1753] The sentiment analysis engine adjusts the tone of the text based on the analysis results.

[1754] Input: The generated sentence and the user's emotional state.

[1755] Output: The adjusted sentence.

[1756] What it does: The sentiment analysis engine adjusts the tone of the generated text to match the user's emotions.

[1757] Step 6:

[1758] The device sends the adjusted text to the mail server.

[1759] Input: Adjusted text.

[1760] Output: The text sent to the mail server.

[1761] Specific operation: The device passes the adjusted text to the mail server's sending API.

[1762] Step 7:

[1763] The mail server forwards the document to the specified destination.

[1764] Input: The text and recipient information sent to the mail server.

[1765] Output: The email sent to the destination email address.

[1766] Specific operation: The mail server forwards the received text to the specified recipient's email address.

[1767] (Application example 2)

[1768] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1769] Conventional text generation systems using generative AI were unable to generate text in a tone that reflected the user's emotions, making it difficult to communicate appropriately with the user. Furthermore, there was a lack of a way to appropriately determine the recipient of the generated text, making it difficult to achieve efficient information transmission. In particular, online shopping sites are required to send product promotional emails and campaign emails that reflect the user's emotions, but the technology to achieve this was lacking.

[1770] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1771] In this invention, the server includes a generative AI means for generating text based on user input, a sending means for sending the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, and an emotion engine means for analyzing the user's emotions and adjusting the tone of the text based on the emotions, thereby making it possible to generate and send product promotion emails and campaign emails in a tone that corresponds to the user's emotions.

[1772] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1773] The "transmission means" is a means for transmitting the text generated by the generative AI means to a specified destination.

[1774] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1775] The "emotion engine means" is a means for analyzing the user's emotions and adjusting the tone of the text based on those emotions.

[1776] A "product introduction email" is an email that introduces product information to users.

[1777] "Campaign Email" means an email sent to inform users about a specific campaign or promotion.

[1778] "Tone" refers to the emotional atmosphere and style of expression of a piece of writing.

[1779] To implement this invention, a server, a user terminal, and a generative AI model are used. The server includes generative AI means for generating text based on input from a user, transmission means for transmitting the generated text, destination determination means for determining a destination based on the content of the generated text, and emotion engine means for analyzing the user's emotions and adjusting the tone of the text based on the emotions.

[1780] The user terminal provides an interface for analyzing the user's emotions when the user browses or purchases products. Specifically, a device equipped with a camera and microphone is used to analyze the user's facial expressions and voice. This allows the user's emotional data to be collected and sent to the server.

[1781] The server analyzes the user's emotions using the emotion engine means and determines the tone of the text based on the analysis result. For example, if the emotion engine analyzes that the user is happy, the generative AI means generates text with a bright tone. The generated text is sent to a specified destination using the sending means.

[1782] For example, if a user is browsing an online shopping site on their smartphone and the emotion engine determines that the user is "happy," the generative AI model will generate the following email in a cheerful tone:

[1783] "Hello! The latest smartphone is waiting for you! Equipped with a high-performance camera and long-lasting battery, this model will make your life more fun and convenient. Check it out now!"

[1784] An example of this prompt is:

[1785] User sentiment: happy

[1786] Product information: The latest smartphone, equipped with a high-performance camera and long-lasting battery life. Price: 80,000 yen

[1787] Tone: Bright

[1788] In this way, it is possible to generate and send product promotional emails and campaign emails in a tone that matches the user's emotions, which allows for more personalized communication and is expected to improve customer satisfaction.

[1789] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1790] Step 1:

[1791] The user device collects the user's facial expressions and voice using a camera and microphone, thereby acquiring the user's emotional data. The input is the user's facial expressions and voice data, and the output is emotional data.

[1792] Step 2:

[1793] The user terminal transmits the collected emotion data to the server. The input is emotion data, and the output is the emotion data transmitted to the server.

[1794] Step 3:

[1795] The server analyzes the received emotion data using an emotion engine means to identify the emotion of the user, where the input is the emotion data and the output is the identified emotion of the user (e.g., happy, sad, neutral).

[1796] Step 4:

[1797] The server uses generative AI means to determine the tone of the text based on the user's emotion, where the input is the identified user emotion and the output is the determined tone of the text.

[1798] Step 5:

[1799] The server uses generative AI to generate text for product promotional emails and campaign emails based on product information and the determined tone. The input is the product information and the determined tone, and the output is the generated text.

[1800] Step 6:

[1801] The server uses a destination determination means to determine a destination based on the content of the generated text, with the input being the generated text and the output being the determined destination.

[1802] Step 7:

[1803] The server uses a sending means to send the generated text to the determined destination. The input is the generated text and the determined destination, and the output is the sent email.

[1804] Example 3

[1805] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1806] In conventional systems, users had to manually decide where to send messages, which was inefficient and had a high risk of sending them to the wrong person. Furthermore, the system lacked the ability to automatically determine the appropriate recipient based on the user's emotions, making it difficult to respond appropriately to the user's feelings.

[1807] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a generative AI means for generating a sentence based on an input from a user, a transmission means for transmitting the sentence generated by the generative AI means, a destination determination means for determining a destination based on the content of the sentence generated by the generative AI means, and an emotion analysis means for analyzing the user's emotion and determining a destination based on the result. This makes it possible to automatically generate a sentence based on a prompt sentence input by the user and automatically determine an appropriate destination based on the content of the sentence and the user's emotion.

[1808] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1809] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[1810] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1811] The "emotion analysis means" is a means for analyzing the user's emotions and determining the destination based on the results.

[1812] This invention is a system that generates a sentence based on an input from a user and automatically determines an appropriate destination depending on the content of the sentence and the user's emotions. A specific embodiment of this system will be described below.

[1813] Hardware and software used

[1814] Hardware: Servers, terminals

[1815] Software: Generative AI models (e.g., GPT-4), sentiment analysis engines

[1816] System configuration

[1817] 1. Generative AI methods: Generate sentences based on user input. Use a generative AI model (e.g., GPT-4) to generate natural language sentences based on user-entered prompts.

[1818] 2. Transmission means: Send the generated text. The server has a means to send the generated text to the appropriate destination.

[1819] 3. Destination determination method: The destination is determined based on the content of the generated text. The server analyzes the generated text and determines the destination based on specific keywords or phrases.

[1820] 4. Sentiment analysis means: Analyze the user's emotions and determine the destination based on the results. A sentiment analysis engine is used to analyze the emotions from the user's input and determine the appropriate destination.

[1821] Specific examples

[1822] The user uses the device interface to enter a prompt for the generative AI model, for example, "Please write a detailed description of the new product launch."

[1823] The device sends this prompt to the server. The server inputs the received prompt into the generative AI model to generate a sentence. Based on the prompt, the generative AI model generates a sentence such as, "We are announcing a new product. This new product has been developed using the latest technology."

[1824] Next, the server analyzes the generated text. Specifically, it detects keywords and phrases within the text. For example, it detects the phrase "announcement of a new product." The server determines the destination based on the analysis results. For example, if the text contains the phrase "announcement of a new product," the server decides to send the text to the marketing department's email address.

[1825] Furthermore, the sentiment analysis engine analyzes the user's emotions. For example, if a user is dissatisfied with customer service, the sentiment analysis engine analyzes that emotion and determines the appropriate destination. For example, in response to the prompt, "Please express your dissatisfaction with customer service," the generative AI model generates the sentence, "I am extremely dissatisfied with the recent customer service experience." The sentiment analysis engine analyzes the user's anger and determines that this sentence should be sent to the customer service department.

[1826] In this way, it is possible to automatically generate a sentence based on the prompt sentence entered by the user, and automatically determine an appropriate destination depending on the content of the sentence and the user's emotions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1827] Step 1:

[1828] The user inputs a prompt sentence. The user uses the terminal interface to input a prompt sentence to the generative AI model. For example, the user might input "Please write a detailed description of the new product launch." The input data is the prompt sentence in text format.

[1829] Step 2:

[1830] The terminal sends the prompt text to the server. The terminal uses an HTTP request to send the prompt text to the server. Specifically, it uses a POST request to send the prompt text to the server. The input data is the prompt text entered by the user, and the output data is the prompt text sent to the server.

[1831] Step 3:

[1832] The server generates a sentence using a generative AI model. The server inputs the received prompt sentence into a generative AI model (e.g., GPT-4) to generate a sentence. The generative AI model generates a sentence in natural language based on the prompt sentence. The input data is the prompt sentence, and the output data is the generated sentence. For example, the generated sentence is, "Our company is announcing a new product. This new product has been developed using the latest technology."

[1833] Step 4:

[1834] The server analyzes the generated text. The server inputs the generated text into a text analysis engine to extract keywords and phrases. Specifically, it uses regular expressions and natural language processing libraries to detect the phrase "new product launch." The input data is the generated text, and the output data is the extracted keywords and phrases.

[1835] Step 5:

[1836] The server determines the destination. Based on the analysis results, the server runs a destination determination algorithm. For example, if the phrase "new product launch" is included, the email address of the marketing department is selected. The input data are the extracted keywords and phrases, and the output data are the determined destination.

[1837] Step 6:

[1838] The server sends the text to the determined destination. The server uses the SMTP protocol to send an email to the determined destination. For example, an email is sent to the marketing department's email address saying, "We are announcing a new product. This new product has been developed using the latest technology." The input data is the generated text and the determined destination, and the output data is the email that was sent.

[1839] Step 7:

[1840] The server analyzes the user's emotions. The server uses an emotion analysis engine to analyze emotions from the user's input. For example, if a user is dissatisfied with customer service, the emotion analysis engine analyzes that emotion. The input data is the user's input, and the output data is the analyzed emotion.

[1841] Step 8:

[1842] The server determines the appropriate destination based on the emotion analysis results. For example, if the user is angry, send it to the customer service department. The input data is the analyzed emotion, and the output data is the determined destination.

[1843] Step 9:

[1844] The server sends the text to the determined destination. The server uses the SMTP protocol to send an email to the determined destination. For example, an email can be sent to the customer service department saying, "I'm very unhappy with your recent customer service experience." The input data is the generated text and the determined destination, and the output data is the email sent.

[1845] (Application example 3)

[1846] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1847] Conventional self-driving vehicles have the problem that it is difficult to improve passenger satisfaction because they do not have a system that can respond appropriately based on passenger emotions and comments. In addition, there is a lack of means to quickly respond when passengers are dissatisfied, which can result in a decline in service quality.

[1848] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1849] In this invention, the server includes a generative AI means for generating text based on user input, a transmission means for transmitting the text generated by the generative AI means, a destination determination means for determining a destination based on the content of the text generated by the generative AI means, an emotion analysis means for analyzing the user's emotion, and an emotion-based destination determination means for determining a destination based on the emotion analyzed by the emotion analysis means. This makes it possible to take appropriate action based on the passenger's emotion and the content of their comments, thereby improving passenger satisfaction. Furthermore, it is possible to quickly respond to passenger dissatisfaction, thereby improving service quality.

[1850] A "generative AI method" is an artificial intelligence method that generates text based on user input.

[1851] "Transmission means" refers to a means for transmitting text generated by the generative AI means.

[1852] The "destination determination means" is a means for determining a destination based on the content of the text generated by the generative AI means.

[1853] "Emotion analysis means" is a means for analyzing the user's emotions.

[1854] The "emotion-based destination determination means" is a means for determining a destination based on the emotion analyzed by the emotion analysis means.

[1855] The system for implementing this invention uses the following hardware and software: the hardware uses an in-car camera and microphone, and the software uses Python, the EmotionRecognizer library, the AI ​​Text Generator library, and smtplib (for sending emails).

[1856] The server first acquires passenger data from the in-car camera and microphone. Then, it analyzes the passenger's emotions using the EmotionRecognizer library. The analyzed emotional data is used as input data to generate text using the AI ​​Text Generator library. The generated text is then sent to the appropriate destination via a transmission means.

[1857] As a specific example, the following prompt sentence could be input into a generative AI model:

[1858] If a passenger is talking about a new product in the car:

[1859] "We look forward to the unveiling of our new self-driving vehicle."

[1860] If a passenger complains on board:

[1861] "The air conditioning in this car isn't working, can you do something about it?"

[1862] When these prompts are entered, the generative AI model generates a response and sends an email to the appropriate department, such as the marketing department if the response contains the phrase "new product launch," or the customer service department if the response indicates the passenger is angry.

[1863] This system makes it possible to respond appropriately based on passengers' emotions and comments, thereby improving passenger satisfaction. It also makes it possible to respond quickly when passengers are dissatisfied, thereby improving service quality.

[1864] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1865] Step 1:

[1866] The server collects passenger data from cameras and microphones inside the vehicle.

[1867] Input: Video and audio data from the camera and microphone

[1868] Output: Passenger video and audio data

[1869] Specific operation: Records passengers' facial expressions and comments in real time via camera and microphone.

[1870] Step 2:

[1871] The server uses the EmotionRecognizer library to analyze emotions from the acquired passenger data.

[1872] Input: Passenger video and audio data

[1873] Output: Parsed emotion data (e.g., joy, anger, sadness, etc.)

[1874] Specific operation: Analyzes facial expressions from video data and tone of voice and content of words from audio data to identify emotions.

[1875] Step 3:

[1876] The server uses the AI ​​Text Generator library to generate sentences based on emotion and voice data.

[1877] Input: Parsed emotion data and speech data

[1878] Output: Generated sentence

[1879] Specific operation: Emotional data and voice data are input into the AI ​​model as prompts to generate appropriate sentences.

[1880] Step 4:

[1881] The server determines the destination based on the content of the generated text.

[1882] Input: Generated sentence

[1883] Output: Destination email address

[1884] What it does: Analyzes the generated text, detects keywords such as "new product launch," and identifies the appropriate department (e.g., marketing, customer service).

[1885] Step 5:

[1886] The server uses the transmission means to transmit the generated text to the determined destination.

[1887] Input: Generated text and destination email address

[1888] Output: Email sent

[1889] Specific operation: Uses smtplib to send an email containing the generated text to the specified recipient.

[1890] The above processing steps enable appropriate responses to be taken based on the passenger's emotions and comments, thereby improving passenger satisfaction. In addition, if a passenger becomes dissatisfied, a prompt response can be made, thereby improving service quality.

[1891] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1892] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1893] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google...

Claims

1. A means for generating a prompt sentence for instructing the generation of a sentence based on an input from a user; A means for generating a sentence using the generated prompt sentence and a generative AI model; A determination means for determining a destination of the generated text based on the content of the text; means for determining an emotional state of a user using an emotion engine; means for generating a prompt sentence instructing adjustment of the tone of the generated sentence based on the generated sentence and an emotional state of the user; A means for adjusting the tone of a sentence using the generated prompt sentence and a generative AI model; and a transmitting means for transmitting the adjusted text to a determined destination.

2. The system according to claim 1, wherein the generated text is a product promotion email and / or a campaign email, and the means for adjusting the tone of the text adjusts the tone of the product promotion email and / or campaign email based on the emotions of a sending user who generates and sends the text.

3. The system according to claim 1, wherein the generated text is a product promotion email and / or a campaign email, and the means for adjusting the tone of the text adjusts the tone of the product promotion email and / or campaign email based on the emotions of a recipient user who is the destination of the text.

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