system

Abstract

Provide a system. A method for inputting text from a user interface is provided. a terminal means for receiving text input to a user interface, converting the text into a data format, and transmitting the data to a server; a summarization algorithm means for summarizing the received text; a translation algorithm means for translating the summarized text; means for transmitting the translated summary to a terminal; means for displaying the translation results sent to the terminal to the user; A system including:

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] The amount of information available today is enormous, making it difficult for users to quickly obtain the information they need. Furthermore, information is often provided in multiple languages, and translating it into a specific language requires time and effort. Therefore, there is a need for an effective system that can simultaneously summarize and translate information. The present invention aims to solve the problem of making information acquisition more efficient for users by providing a system that automatically summarizes information and translates the summary into a specified language. [Means for solving the problem]

[0005] The present invention provides a system including: means for providing a user interface for a user to input text; terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to a server; summarization algorithm means for summarizing the received text; translation algorithm means for translating the summarized text; means for transmitting the translated summary to the terminal; and means for displaying the translation result transmitted to the terminal to the user. The translation algorithm means uses an external translation API, and the summarization algorithm means uses a specific statistical or machine learning algorithm, thereby enabling information to be summarized and translated quickly and effectively.

[0006] A "user interface" is an interactive element such as an input screen or form that allows a user to input text into a system.

[0007] "Terminal means" refers to a device or software that has the function of receiving text entered into a user interface, converting it into a data format, and sending it to a server.

[0008] The "summarization algorithm means" is an algorithm that has the function of analyzing received text data, extracting important points and content, and shortening the data.

[0009] A "translation algorithm means" is an algorithm capable of translating the summarized text into a different specified language.

[0010] A "translation API" is a program interface for using translation functions through an interface provided by an external service.

[0011] An "HTTP request" is a request based on a protocol (communication procedure) used when transmitting data over the Internet.

[0012] The "JSON format" is a lightweight data exchange format for structuring, storing, and sending data.

[0013] "Memory" is a storage device that allows the server to temporarily store data.

[0014] The above are definitions of important terms included in the claims. [Brief explanation of the drawings]

[0015] [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. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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, a 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), and an APU (Accelerated Processing Unit).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. 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."

[0036] As an embodiment of the present invention, a system for automatically providing summaries and translations is constructed. The program processing of this system and a specific example of its operation will be described below.

[0037] The system consists of a user interface, a terminal, a server, a summarization algorithm, a translation algorithm, and a translation API. Users access the system through a browser or an application and input text to be summarized and translated.

[0038] System processing flow

[0039] 1. User text input

[0040] The user inputs the text they want to summarize and translate using an interface (e.g., a text input field) provided by the system. For example, the user inputs the English sentence, "The quick brown fox jumps over the lazy dog."

[0041] 2. Sending text from the device to the server

[0042] When the user completes the input and presses the send button, the terminal sends this text to the server in JSON format, specifically via an HTTP request.

[0043] 3. Server-generated text summarization

[0044] The server processes the text data received from the device using a summarization algorithm. The main points of the text are extracted and a short summary is generated. For example, the received text "The quick brown fox jumps over the lazy dog." is processed by the summarization algorithm and summarized as "The fox jumps over the dog."

[0045] 4. Japanese translation of the summary

[0046] The summarized text "The fox jumps over the dog." is then translated into Japanese by means of a translation algorithm. Using a translation API, a translation request is sent to an external service. The translation result is "The fox jumps over the dog."

[0047] 5. Send the translation results to your device

[0048] The translated summary is sent back to the device from the server, where it is again formatted in JSON and sent as an HTTP response.

[0049] 6. Displaying results to the user

[0050] The terminal receives the translation result from the server and displays it to the user. The user can view the translated summary through a browser or application interface.

[0051] In this way, the system of the present invention efficiently executes a series of processes from user text input, to summary generation, translation into Japanese, and final display, enabling users to quickly grasp vast amounts of information and significantly reduce the time and effort required to obtain the information they need.

[0052] Specific examples

[0053] 1. User Input

[0054] User types: "The quick brown fox jumps over the lazy dog."

[0055] 2. Summary of results

[0056] Summary by server's summarization algorithm: "The fox jumps over the dog."

[0057] 3. Translation results

[0058] Japanese translation by translation algorithm: "The fox jumps over the dog."

[0059] This allows users to easily obtain summaries and their translation results.By optimizing and automating this process, the system significantly reduces time and effort.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] User enters text: The user enters the text they want summarized and translated into a text input field in their browser or app.

[0063] Step 2:

[0064] The terminal receives the user's input. When the user presses the Send button, the terminal receives the entered text.

[0065] Step 3:

[0066] The device sends text to the server. The device converts the received text into an appropriate data format (e.g., JSON) and sends it to the server using an HTTP request.

[0067] Step 4:

[0068] The server receives the request. The server receives the HTTP request sent from the terminal and extracts the text data.

[0069] Step 5:

[0070] The server applies the summarization algorithm: The server invokes the summarization algorithm, passing the received text as input. The algorithm extracts important sentences and keywords and generates a shortened summary.

[0071] Step 6:

[0072] The server stores the summary results. The server temporarily stores the generated summary results in memory.

[0073] Step 7:

[0074] The server invokes the translation algorithm, and passes the stored summary text to another translation algorithm or an external translation API (e.g., translation API) to translate it into Japanese.

[0075] Step 8:

[0076] The server receives the translation results, receives the Japanese summary results sent from the translation API, and formats them as necessary.

[0077] Step 9:

[0078] The server formats the results in JSON. The server formats a response containing the translated summary results in JSON.

[0079] Step 10:

[0080] The server sends the response to the terminal. The formatted data is sent to the terminal as an HTTP response.

[0081] Step 11:

[0082] The terminal receives the response. The terminal receives the response from the server and analyzes the data.

[0083] Step 12:

[0084] The terminal displays the results to the user. The terminal displays a summary of the analyzed Japanese text on the screen and informs the user of the results.

[0085] Example 1

[0086] Next, a description will be given of 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."

[0087] Conventional information processing systems have had difficulty efficiently summarizing large amounts of text data and translating it into different languages. In particular, the quality of summarization and translation is low, making it difficult to provide users with the fast and accurate information they require.

[0088] 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.

[0089] In this invention, the server includes a means for providing a user interface, a terminal means for receiving text data, converting it into a data format, and transmitting the data to the server, a summarization algorithm means, a translation algorithm means, a means for transmitting a translated summary to the terminal, and a means for displaying the translated summary to the user. This makes it possible to efficiently summarize large amounts of text data and quickly provide highly accurate translations.

[0090] "User interface" means an interface through which a user accesses a system and inputs or receives information.

[0091] "Terminal means" refers to a device or software for transmitting data entered by a user to a server.

[0092] The "summarization algorithm means" is an algorithm that processes input text data, extracts its main information, and generates a short summary.

[0093] A "translation algorithm means" is an algorithm for translating the summarized text into a different language.

[0094] "Translation API" means an application programming interface for accessing an external translation service, sending requests for translation of text, and receiving the results.

[0095] A "generative AI model" is an algorithm that processes data (summarizes and translates) based on machine learning and artificial intelligence.

[0096] "Data format" refers to the format for structuring and sending data, and specifically includes JSON and XML.

[0097] A "server" is a computer system that processes text data received from a user, summarizes and translates it, and returns the results.

[0098] MODE FOR CARRYING OUT THE INVENTION

[0099] The present invention is a system for automatically providing summarization and translation of text by a user, which is composed of a user interface, a terminal means, a server, a summarization algorithm means, a translation algorithm means, and a translation API.

[0100] System configuration

[0101] 1. User Interface

[0102] The user interface is the browser or application interface through which the user enters text, allowing the user to easily enter the text they wish to have summarized and translated.

[0103] 2. Terminal means

[0104] The terminal means is a device or software for transmitting text data entered by a user to a server. HTTP is used as the communication protocol, and JSON is used as the data format.

[0105] 3. Server

[0106] The server is a central processing unit that processes the text data received from the terminals, and uses a summarization algorithm means and a translation algorithm means to summarize and translate the text.

[0107] 4. Summarization Algorithm

[0108] The summarization algorithm is an algorithm that uses a generative AI model to summarize text data. It automatically extracts the main points of the received text and generates a short summary.

[0109] 5. Translation Algorithm Means

[0110] The translation algorithm means is an algorithm for translating the summarized text into a different language, in particular using an external translation API (e.g., Google® translation API).

[0111] 6. Translation API

[0112] A translation API is an application programming interface for accessing external services to perform translations.

[0113] 7. Displaying results to the user

[0114] The translated summary is sent back to the terminal and displayed to the user through a user interface.

[0115] Specific examples

[0116] 1. User Input

[0117] User: Enters the sentence "The quick brown fox jumps over the lazy dog." into the interface.

[0118] 2. Summary of results

[0119] Server: Generates a summary sentence "The fox jumps over the dog." using a summarization algorithm.

[0120] 3. Translation results

[0121] Server: Using the translation API, translate this summary into Japanese as "The fox jumps over the dog."

[0122] Prompt Sentence Examples

[0123] An example of a prompt when using a generative AI model is as follows:

[0124] English summary

[0125] "Please summarize the following text: The quick brown fox jumps over the lazy dog."

[0126] Summary English translation

[0127] "Please translate the following text to Japanese: The fox jumps over the dog."

[0128] In this way, the system of the present invention efficiently executes a series of processes from user text input, to summary generation, translation into Japanese, and final display, allowing users to quickly grasp vast amounts of information and significantly reduce the time and effort required to obtain the information they need.

[0129] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0130] Step 1:

[0131] The user inputs the text they want summarized and translated using the interface provided by the system (a text input field in a browser or application). The input text is an English sentence such as "The quick brown fox jumps over the lazy dog."

[0132] Input: The text the user types into the input field

[0133] Output: Text data entered by the user

[0134] Specific behavior:

[0135] A user opens a browser or application interface, enters text into an input field, and then presses a submit button.

[0136] Step 2:

[0137] The terminal converts the text entered in the user interface into a data format (JSON) and sends it to the server using an HTTP request.

[0138] Input: Text data entered by the user

[0139] Output: JSON format text data

[0140] Specific behavior:

[0141] The terminal converts the text received from the user interface into the following JSON format:

[0142] json

[0143] {

[0144] "text": "The quick brown fox jumps over the lazy dog."

[0145] }

[0146] This JSON data is sent to the server as an HTTP request.

[0147] Step 3:

[0148] The server analyzes the text data received from the device and passes it to a summarization algorithm means to generate a summary, which uses a generative AI model.

[0149] Input: JSON format text data

[0150] Output: Summarized text

[0151] Specific behavior:

[0152] The server extracts the value of the "text" field from the received JSON data and summarizes the sentence using a generative AI model. For example, it summarizes "The quick brown fox jumps over the lazy dog." to "The fox jumps over the dog."

[0153] Step 4:

[0154] The server passes the summarized text "The fox jumps over the dog." to a translation algorithm means, which translates it into Japanese using a translation API.

[0155] Input: Summarized text

[0156] Output: The translated text

[0157] Specific behavior:

[0158] The server sends a request to the translation API, asking it to translate the summary sentence, "The fox jumps over the dog." The translation API receives the request and returns the translation result, "The fox jumps over the dog."

[0159] Step 5:

[0160] The server formats the translated text in JSON format and sends it to the terminal as an HTTP response.

[0161] Input: Translated text

[0162] Output: Translation result data in JSON format

[0163] Specific behavior:

[0164] The server formats the translated text "The fox jumps over the dog." in the following JSON format:

[0165] json

[0166] {

[0167] "summary": "The fox jumps over the dog.",

[0168] "translation": "The fox jumps over the dog."

[0169] }

[0170] This data is sent to the terminal as an HTTP response.

[0171] Step 6:

[0172] The terminal displays the translation results received from the server on a user interface.

[0173] Input: Translation result data in JSON format

[0174] Output: The translation result displayed in the user interface

[0175] Specific behavior:

[0176] The device extracts the value of the "translation" field from the received JSON data and displays "The fox jumps over the dog" on the user interface, allowing the user to view the translated summary.

[0177] (Application example 1)

[0178] Next, a description will be given of Application 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."

[0179] At logistics centers, staff are required to efficiently understand lengthy logistics information written in multiple languages. However, manual summarization and translation takes time and effort, reducing work efficiency. To solve this issue and improve work efficiency, it is necessary to quickly and accurately summarize and translate information and provide it in a format that is easy for on-site staff to understand.

[0180] 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.

[0181] In this invention, the server includes means for providing a user interface for a user to input text, terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to the server, summarization algorithm means for summarizing the received text, translation algorithm means for translating the summarized text, means for transmitting the translated summary to the terminal, means for displaying the translation result transmitted to the terminal to the user, and means for displaying the summary and translated text to warehouse staff for logistics information. This enables logistics center staff to efficiently summarize and translate lengthy logistics information written in multiple languages ​​and quickly understand it.

[0182] A "user interface" is a screen or input device that allows a user to perform operations or input data to a system.

[0183] The "terminal means" is a device that has the function of receiving data input to a user interface, converting it into an appropriate data format, and transmitting it to a server.

[0184] A "summarization algorithm" is a program or process that extracts the main points from input text and generates a shortened summary.

[0185] A "translation algorithmic means" is a program or process for converting text written in one language into another language.

[0186] A "translation API" is an application program interface that provides translation functionality by accessing external translation services.

[0187] "Logistics information" refers to information managed by a logistics center, such as arrival information and shipping information.

[0188] "Warehouse staff" refers to workers and managers engaged in operations at logistics centers.

[0189] The "system" refers to a collection of a user interface, a terminal means, a summarization algorithm means, a translation algorithm means, and a server and a network for linking these together to operate.

[0190] "Multilingual" means two or more different languages.

[0191] A "long text" is a text that contains a large amount of information and is made up of multiple sentences or paragraphs.

[0192] A "server" is a computer system that provides information and processing power over a network.

[0193] A "data format" is a set of rules or formats for structuring and storing data.

[0194] The present invention aims to realize a system that efficiently summarizes long multilingual logistics information at a logistics center and provides the translated information to warehouse staff. This system is configured as follows.

[0195] First, a user uses a device such as a smartphone or tablet to input long multilingual text from a user interface, such as detailed information about incoming shipments or shipping status.

[0196] The terminal receives data entered by the user, converts it into a data format, and sends it to the server. JSON is a suitable data format for this purpose. An HTTP request is used to send data from the terminal to the server.

[0197] The server processes the received text data with a summarization algorithm means. The summarization algorithm means uses a specific statistical or machine learning algorithm to extract the main points of the text and generate a short summary. For example, the text "The shipment of 100 boxes of electronics has been delayed due to unexpected customs clearance issues, and will arrive by the end of next week." is summarized as the main information "The shipment of electronics has been delayed."

[0198] Next, the summarized text is translated into a desired language by a translation algorithm means. The translation algorithm means uses an external translation API to translate the summarized text into, for example, Japanese. For example, the translation API used is "https: / / api.translation.example.com / v1 / translate". The translation result is "Shipments of electronic devices are delayed."

[0199] The server then sends the translated summary back to the terminal in JSON format. The terminal then displays the translation results received from the server to the user through a user interface. Warehouse staff can quickly understand the translated summary and efficiently carry out their required tasks.

[0200] A concrete example would be the following scenario: Warehouse staff can input lengthy incoming goods information on their own devices, and receive a summary and translation of the information in a short time, enabling them to take appropriate action promptly.

[0201] Examples of prompts to be input to a generative AI model include:

[0202] Language used: Python

[0203] Objective: Write a program to summarize and translate lengthy logistics information for warehouse staff.

[0204] Assume that the summarized text is to be translated into Japanese.

[0205] In this way, the system of the present invention can efficiently summarize lengthy logistics information in multiple languages ​​and provide translated information, thereby significantly improving the operational efficiency of logistics centers.

[0206] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0207] Step 1:

[0208] Users use a smartphone or tablet device to input long multilingual text into the user interface. This input text is treated as the system's initial data. For example, specific text such as "The shipment of 100 boxes of electronics has been delayed due to unexpected customs clearance issues, and will arrive by the end of next week." is input.

[0209] Step 2:

[0210] The terminal receives text data entered by the user and converts it into a data format, for example, JSON format. In this process, the text data is structured as a JSON object, making it a format that can be sent to the next processing step. This converted data is then sent to the server using an HTTP request.

[0211] Step 3:

[0212] The server processes the text data received from the device using a summarization algorithm. Specifically, it uses machine learning or statistical algorithms to extract key points and generate a short summary. It analyzes the input long text and outputs a summary sentence, such as "The shipment of electronics has been delayed."

[0213] Step 4:

[0214] The server then translates the summary generated by the summarization algorithm into the desired language using a translation algorithm. This translation uses an external translation API, and the summary is sent to the API to obtain the translation result. The translation API translates the input summary into the corresponding language, and outputs a translation result such as "Shipments of electronic devices are delayed."

[0215] Step 5:

[0216] The server restructures the translated summary and formats it again in JSON format. This JSON data is sent to the terminal as an HTTP response. Here, the translation result text is properly formatted and provided as a response to the terminal.

[0217] Step 6:

[0218] The terminal displays the translation results received from the server to the user through a user interface. Warehouse staff visually check the displayed translation results and perform the necessary tasks quickly and efficiently. In this step, the process of displaying the specific data received on the screen is carried out.

[0219] 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.

[0220] As an embodiment of the present invention, a system is constructed that automatically provides summarization, translation, and user emotion recognition. Below, the program processing of this system and a specific example of its operation will be described.

[0221] The system consists of a user interface, a terminal, a server, a summarization algorithm, a translation algorithm, a translation API, and an emotion engine. Users access the system through a browser or an application and input text to be summarized and translated. At the same time, the emotion engine recognizes the user's emotions and provides the optimal summary and translation based on those emotions.

[0222] System processing flow

[0223] 1. User text input

[0224] The user inputs the text they want to summarize and translate using an interface (e.g., a text input field) provided by the system. For example, the user inputs the English sentence, "The quick brown fox jumps over the lazy dog."

[0225] 2. Sending text from the device to the server

[0226] When the user completes the input and presses the send button, the terminal sends this text to the server in JSON format, specifically via an HTTP request.

[0227] 3. Emotion Recognition by the Server

[0228] The server analyzes the received text data with an emotion engine to identify the user's emotion (positive, negative, neutral). For example, in the case of the text "I am very happy with the service," a positive emotion is recognized.

[0229] 4. Server-generated text summarization

[0230] The server processes the text using a summarization algorithm to extract key points and generate a short summary. For example, the received text "The quick brown fox jumps over the lazy dog." is processed by the summarization algorithm and summarized as "The fox jumps over the dog."

[0231] 5. Japanese translation of the summary

[0232] The summarized text "The fox jumps over the dog." is translated into Japanese by means of a translation algorithm. Using a translation API, a translation request is sent to an external service. The translation result is "The fox jumps over the dog."

[0233] 6. Sending translation results to your device

[0234] The translated summary is sent back to the device from the server, where it is again formatted in JSON and sent as an HTTP response.

[0235] 7. Displaying results to the user

[0236] The terminal receives the translation result from the server and displays it to the user. The user can view the translated summary through a browser or application interface.

[0237] Specific examples

[0238] 1. User Input

[0239] User types: "The quick brown fox jumps over the lazy dog."

[0240] 2. Emotion recognition

[0241] The server's emotion engine analyzes the text and determines the user's emotion as "neutral."

[0242] 3. Summary of results

[0243] Summary by server's summarization algorithm: "The fox jumps over the dog."

[0244] 4. Translation Results

[0245] Japanese translation by translation algorithm: "The fox jumps over the dog."

[0246] This allows users to easily obtain summaries and translation results that correspond to their emotions. By optimizing and automating this process, the system significantly reduces time and effort. The addition of an emotion engine makes it possible to provide optimal information according to the user's emotional state.

[0247] The processing flow will be explained below.

[0248] Step 1:

[0249] User enters text. In a text input field in a browser or app, the user enters the text they want summarized and translated. For example, they enter the sentence "The quick brown fox jumps over the lazy dog."

[0250] Step 2:

[0251] The terminal receives the user's input. When the user presses the "Send" button, the terminal receives the entered text and prepares to send this data to the server.

[0252] Step 3:

[0253] The device sends text to the server. The device converts the received text into an appropriate data format (e.g., JSON) and sends it to the server using an HTTP request.

[0254] Step 4:

[0255] The server receives the request. When the server receives the HTTP request sent from the terminal, it extracts the text data.

[0256] Step 5:

[0257] The server calls the emotion engine to analyze the text. The server passes the received text to the emotion engine, which analyzes the emotion (positive, negative, neutral) expressed by the text. For example, if the sentence says "I am very happy with the service," the emotion engine will recognize the positive emotion.

[0258] Step 6:

[0259] The server applies a summarization algorithm. Based on the sentiment analysis results, the server uses a summarization algorithm to summarize the received text. For example, the input "The quick brown fox jumps over the lazy dog." is summarized as "The fox jumps over the dog."

[0260] Step 7:

[0261] The server invokes the translation algorithm. The server passes the summarized text to the translation algorithm or an external translation API to translate it into the specified language. For example, translating the English summary sentence "The fox jumps over the dog." into Japanese.

[0262] Step 8:

[0263] The server receives the translation result. The server receives the Japanese summary result "The fox jumps over the dog." returned from the translation API and formats it as necessary.

[0264] Step 9:

[0265] The server formats the results in JSON format and sends the response to the device. The server then formats the response containing the translated summary results in JSON format and sends it to the device as an HTTP response.

[0266] Step 10:

[0267] The device receives the response and displays the result to the user. The device analyzes the response received from the server and displays the translated summary on the screen. The user can see the translation result, "The fox jumps over the dog," on the browser or application screen.

[0268] This processing step realizes a system that efficiently provides summaries and translation results to users and presents optimal information based on the user's emotions.

[0269] Example 2

[0270] Next, a description will be given of 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."

[0271] In modern digital communication, users are seeking efficient ways to summarize and translate large amounts of text. However, conventional systems generate uniform summaries and translations without considering the user's feelings, making it impossible to provide appropriate information that meets the user's needs. Furthermore, even when communicating between different languages, manual translation and summarization is time-consuming and labor-intensive.

[0272] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for providing a user interface for a user to input text, terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to the server, emotion engine means for recognizing the emotion of the received text, summarization algorithm means for summarizing the received text, translation algorithm means for translating the summarized text, means for transmitting the translated summary to the terminal, and means for displaying the translation result transmitted to the terminal to the user. This enables appropriate summaries and translations that take the user's emotions into consideration to be automatically provided, significantly reducing time and effort.

[0273] A "user" is an entity that uses the system to input text and receive results such as summaries and translations.

[0274] An "interface" is a structure on a system that contains the means by which a user inputs text and the elements used to validate that input.

[0275] "Terminal means" refers to a device or software that has the function of receiving text entered by a user, converting it into a data format, and sending it to a server.

[0276] An "emotion engine means" is an algorithm or software that analyzes received text and recognizes the user's emotions.

[0277] A "summarization algorithm" is a technique or algorithm that processes input text, extracts important information, and generates a short summary.

[0278] A "translation algorithm means" is a technique or algorithm for translating the summarized text into another language.

[0279] "Translation API" means an application programming interface for connecting to an external translation service to translate text.

[0280] "Data format" refers to the structure or format of data used when a terminal means communicates with a server, and includes, for example, JSON and XML.

[0281] An "HTTP request" is a communication protocol used to send text and other data between a device and a server.

[0282] An "HTTP response" is response data that the server sends to the terminal, and specifically includes the translation and summary results of the input text.

[0283] This invention is a system that efficiently summarizes and translates text entered by a user. It is particularly characterized by its ability to provide more appropriate summarization and translation results by taking into account the user's emotional state. This system is comprised of a user interface, a terminal device, a server, an emotion engine, a summarization algorithm, a translation algorithm, and a translation API.

[0284] The user accesses the system using a browser or application and enters the text they want to summarize and translate in the text input field. The entered text is temporarily stored on the device and sent to the server in JSON format when the submit button is pressed.

[0285] The server receives the text sent from the device and analyzes the sentiment of the text using an emotion engine. The emotion engine uses a natural language processing algorithm to identify the most appropriate emotion from three emotion categories: positive, negative, and neutral. The received text is then summarized by a summarization algorithm. The summarization algorithm uses statistical methods and machine learning algorithms to extract key information and generate a short summary.

[0286] Next, the generated summary is translated into another language (e.g., Japanese) using a translation algorithm. A translation API is used to send a request to an external service, such as the Google Translate API. The server receives the response from the translation API and obtains the translation result. After obtaining the translation result, the server sends it to the terminal in JSON format.

[0287] The device then displays the translation results received from the server in the browser or application, allowing the user to view a summary of the text they entered and the translation results.

[0288] For example, consider the following prompt:

[0289] If the English sentence "The quick brown fox jumps over the lazy dog" is input into the system, the emotion engine will analyze the sentence as neutral, and the summarization algorithm will generate the summary "The fox jumps over the dog." This will then be translated into Japanese by the translation algorithm, resulting in the result "The fox jumps over the dog." Finally, the user can view this translation result in their browser or application.

[0290] By incorporating sentiment analysis, this system not only provides appropriate information according to the user's emotional state, but also enables efficient communication across multiple languages, thereby saving users a great deal of time and effort.

[0291] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0292] Step 1:

[0293] User:

[0294] A user accesses the system using a browser or application and enters the text they want summarized and translated into the text input field. An example of the text entered is "The quick brown fox jumps over the lazy dog." The system recognizes the entered text.

[0295] Step 2:

[0296] Device:

[0297] When the user presses the send button, the terminal temporarily saves the entered text, converts it to JSON format, and generates an HTTP POST request. This request contains the entered text data. The terminal then sends this to the server. The input is the user's text, and the output is an HTTP request in JSON format.

[0298] Step 3:

[0299] server:

[0300] The server receives JSON-formatted text sent from the terminal. The received data is parsed as raw text data. The input is the JSON data sent from the terminal, and the output is parseable text data.

[0301] Step 4:

[0302] server:

[0303] The server calls the emotion engine to analyze the emotion of the received text. The emotion engine uses natural language processing algorithms to classify the text as positive, negative, or neutral. For example, if the text is "I am very happy with the service," the emotion engine will recognize it as a positive emotion. The input is the parseable text data, and the output is the emotion category.

[0304] Step 5:

[0305] server:

[0306] After emotion recognition is complete, the server invokes a summarization algorithm to summarize the text. The summarization algorithm uses statistical methods and machine learning algorithms to extract important information and generate a short summary. For example, "The quick brown fox jumps over the lazy dog." can be summarized as "The fox jumps over the dog." The input is the text data after emotion recognition, and the output is the summary.

[0307] Step 6:

[0308] server:

[0309] The generated summary is then translated into another language (e.g., Japanese) by a translation algorithm. The translation algorithm sends a request to an external translation API (e.g., Google Translate API) to obtain the translation result. For example, the summary "The fox jumps over the dog." is translated to "The fox jumps over the dog." The input is the summary, and the output is the translation result.

[0310] Step 7:

[0311] server:

[0312] The server repackages the translation results in JSON format and sends them to the terminal as an HTTP response. The input is the translation results, and the output is the JSON-formatted HTTP response.

[0313] Step 8:

[0314] Device:

[0315] The terminal receives the HTTP response from the server and parses the data again. The parsed translation result is displayed on the user interface. The input is the JSON data received from the server, and the output is the display to the user.

[0316] Step 9:

[0317] User:

[0318] The user checks the translation results displayed on the screen of the terminal, allowing them to visually check the summary of the input text and its translation results.

[0319] (Application example 2)

[0320] Next, a description will be given of Application 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."

[0321] In today's advertising industry, there is a demand for fast and accurate delivery of advertisements that match user emotions. However, conventional ad generation methods have difficulty customizing advertisements that take user emotions into account, resulting in ineffective ad presentation. Furthermore, there is no system that can automatically summarize and translate user-provided text at the same time, which leads to a poor user experience.

[0322] 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.

[0323] In this invention, the server includes emotion recognition means for recognizing the emotion of the received text, summarization algorithm means for summarizing the received text based on the emotion information obtained by the emotion recognition means, and translation algorithm means for translating the summarized text, thereby enabling the automatic generation of customized advertisements based on the user's emotions, as well as the summarization and translation of the advertisements, thereby enabling effective advertisement presentation and an improved user experience.

[0324] A "user interface" is an input means by which a user enters text and interacts with a system.

[0325] "Terminal means" refers to a device or software for receiving text entered at a user interface, converting it into a data format, and transmitting it to a server.

[0326] An "emotion recognizer" is an algorithm or engine for analyzing a user's emotions from received text and identifying positive, negative, or neutral emotions.

[0327] The "summarization algorithm means" is an algorithm for extracting important points of the text and generating a concise summary based on the received text and its sentiment information.

[0328] "Translation algorithm means" is an algorithm for translating the summarized text into a different language, which may use an external translation API.

[0329] A "translation API" is a program interface for translating text into a specified language using a translation function provided as an external service.

[0330] The "means for transmitting to the terminal" is a communication means for transmitting the translated summary from the server to the terminal.

[0331] The "display means" refers to a display device or display software for visually presenting the translation results on the user's terminal.

[0332] This invention is a system that generates advertisements based on user emotions and automatically summarizes and translates them. Specific embodiments for implementing this system will be described in detail below.

[0333] System Overview

[0334] This system is composed of a user, a terminal, and a server, and includes a user interface, emotion recognition, a summarization algorithm, a translation algorithm, and means for displaying results.

[0335] Hardware and software used

[0336] Hardware: Smartphones, servers

[0337] Software: Python, textblob library (emotion recognition), googletrans library (translation)

[0338] Data processing and calculation methods

[0339] 1. Providing a user interface

[0340] The device provides a user interface that allows the user to input text, which can be achieved through a smartphone application or a web browser.

[0341] 2. Entering and Receiving Text

[0342] The user inputs text, the device receives the input text, and sends it to the server, using JSON as the data format.

[0343] 3. Emotion recognition

[0344] The server analyzes the received text using an emotion recognition means (textblob library) to identify positive, negative, or neutral emotions.

[0345] 4. Summary Generation

[0346] Based on the sentiment information, the server uses a summarization algorithm to extract key points of the text and generate a summary.

[0347] 5. Translation of Abstracts

[0348] The summarized text is translated into the specified language by means of a translation algorithm (googletrans library), possibly using an external translation API.

[0349] 6. Results transmission and display

[0350] The translated summary is sent from the server to the terminal and displayed to the user through a user interface.

[0351] Specific examples

[0352] 1. User Input

[0353] The user enters the text "I love the new features in this product!"

[0354] 2. Emotion recognition

[0355] The server's emotion recognition means analyzes this text and determines positive emotions.

[0356] 3. Summary Generation

[0357] A summarization algorithm means summarizes this text and produces "Love new features product!"

[0358] 4. Translation Results

[0359] A translation algorithm means translates this summary into Japanese and produces "I love the new features!"

[0360] Prompt Sentence Examples

[0361] Example prompt for generative AI model:

[0362] Use the translation API to translate the following text into Japanese: "I love the new features!"

[0363] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0364] Step 1:

[0365] The user enters text

[0366] A user inputs text that will be used to generate an advertisement using a user interface provided by a smartphone application or a web browser. The input text is then sent to the device via the user interface (e.g., "I love the new features in this product!").

[0367] Step 2:

[0368] The device sends the text to the server

[0369] The device receives the text entered by the user, converts it into a data format (JSON format), and then sends it to the server using an HTTP request. Input: User text (e.g., "I love the new features in this product!") Output: JSON-formatted text data

[0370] Step 3:

[0371] The server recognizes emotions

[0372] The server analyzes the received text data using emotion recognition (textblob library) to identify positive, negative, or neutral emotions. Input: Text data in JSON format. Output: Emotion score and emotion category (e.g., positive).

[0373] Step 4:

[0374] The server summarizes the text

[0375] The server uses a summarization algorithm to extract key points from the received text based on the emotion information and generate a short summary. Input: Emotion-recognized text (e.g., "I love the new features in this product!") Output: Summarized text (e.g., "Love new features product!")

[0376] Step 5:

[0377] The server translates the summary

[0378] The server translates the summarized text into the specified language using a translation algorithm (googletrans library), possibly using an external translation API. Input: Summarized text (e.g. "Love new features product!") Output: Translated text (e.g. "Love the new features product!")

[0379] Step 6:

[0380] The server sends the translated summary to the device

[0381] The server converts the translated summary into JSON format and sends it to the device using an HTTP response. Input: Translated text (e.g., "I love the new feature!") Output: Translation data in JSON format

[0382] Step 7:

[0383] The device displays the translation results to the user

[0384] The device displays the translation data received from the server on the user interface and notifies the user of the results. Input: Translation data in JSON format Output: Translation results displayed to the user (e.g., "I love the new features!")

[0385] 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.

[0386] 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> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[0387] 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.

[0388] [Second embodiment]

[0389] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0390] 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.

[0391] 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).

[0392] 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.

[0393] 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.

[0394] 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).

[0395] 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.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] 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.

[0400] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0401] As an embodiment of the present invention, a system for automatically providing summaries and translations is constructed. The program processing of this system and a specific example of its operation will be described below.

[0402] The system consists of a user interface, a terminal, a server, a summarization algorithm, a translation algorithm, and a translation API. Users access the system through a browser or an application and input text to be summarized and translated.

[0403] System processing flow

[0404] 1. User text input

[0405] The user inputs the text they want to summarize and translate using an interface (e.g., a text input field) provided by the system. For example, the user inputs the English sentence, "The quick brown fox jumps over the lazy dog."

[0406] 2. Sending text from the device to the server

[0407] When the user completes the input and presses the send button, the terminal sends this text to the server in JSON format, specifically via an HTTP request.

[0408] 3. Server-generated text summarization

[0409] The server processes the text data received from the device using a summarization algorithm. The main points of the text are extracted and a short summary is generated. For example, the received text "The quick brown fox jumps over the lazy dog." is processed by the summarization algorithm and summarized as "The fox jumps over the dog."

[0410] 4. Japanese translation of the summary

[0411] The summarized text "The fox jumps over the dog." is then translated into Japanese by means of a translation algorithm. Using a translation API, a translation request is sent to an external service. The translation result is "The fox jumps over the dog."

[0412] 5. Send the translation results to your device

[0413] The translated summary is sent back to the device from the server, where it is again formatted in JSON and sent as an HTTP response.

[0414] 6. Displaying results to the user

[0415] The terminal receives the translation result from the server and displays it to the user. The user can view the translated summary through a browser or application interface.

[0416] In this way, the system of the present invention efficiently executes a series of processes from user text input, to summary generation, translation into Japanese, and final display, enabling users to quickly grasp vast amounts of information and significantly reduce the time and effort required to obtain the information they need.

[0417] Specific examples

[0418] 1. User Input

[0419] User types: "The quick brown fox jumps over the lazy dog."

[0420] 2. Summary of results

[0421] Summary by server's summarization algorithm: "The fox jumps over the dog."

[0422] 3. Translation results

[0423] Japanese translation by translation algorithm: "The fox jumps over the dog."

[0424] This allows users to easily obtain summaries and their translation results.By optimizing and automating this process, the system significantly reduces time and effort.

[0425] The processing flow will be explained below.

[0426] Step 1:

[0427] User enters text: The user enters the text they want summarized and translated into a text input field in their browser or app.

[0428] Step 2:

[0429] The terminal receives the user's input. When the user presses the Send button, the terminal receives the entered text.

[0430] Step 3:

[0431] The device sends text to the server. The device converts the received text into an appropriate data format (e.g., JSON) and sends it to the server using an HTTP request.

[0432] Step 4:

[0433] The server receives the request. The server receives the HTTP request sent from the terminal and extracts the text data.

[0434] Step 5:

[0435] The server applies the summarization algorithm: The server invokes the summarization algorithm, passing the received text as input. The algorithm extracts important sentences and keywords and generates a shortened summary.

[0436] Step 6:

[0437] The server stores the summary results. The server temporarily stores the generated summary results in memory.

[0438] Step 7:

[0439] The server invokes the translation algorithm, and passes the stored summary text to another translation algorithm or an external translation API (e.g., translation API) to translate it into Japanese.

[0440] Step 8:

[0441] The server receives the translation results, receives the Japanese summary results sent from the translation API, and formats them as necessary.

[0442] Step 9:

[0443] The server formats the results in JSON. The server formats a response containing the translated summary results in JSON.

[0444] Step 10:

[0445] The server sends the response to the terminal. The formatted data is sent to the terminal as an HTTP response.

[0446] Step 11:

[0447] The terminal receives the response. The terminal receives the response from the server and analyzes the data.

[0448] Step 12:

[0449] The terminal displays the results to the user. The terminal displays a summary of the analyzed Japanese text on the screen and informs the user of the results.

[0450] Example 1

[0451] Next, a description will be given of 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."

[0452] Conventional information processing systems have had difficulty efficiently summarizing large amounts of text data and translating it into different languages. In particular, the quality of summarization and translation is low, making it difficult to provide users with the fast and accurate information they require.

[0453] 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.

[0454] In this invention, the server includes a means for providing a user interface, a terminal means for receiving text data, converting it into a data format, and transmitting the data to the server, a summarization algorithm means, a translation algorithm means, a means for transmitting a translated summary to the terminal, and a means for displaying the translated summary to the user. This makes it possible to efficiently summarize large amounts of text data and quickly provide highly accurate translations.

[0455] "User interface" means an interface through which a user accesses a system and inputs or receives information.

[0456] "Terminal means" refers to a device or software for transmitting data entered by a user to a server.

[0457] The "summarization algorithm means" is an algorithm that processes input text data, extracts its main information, and generates a short summary.

[0458] A "translation algorithm means" is an algorithm for translating the summarized text into a different language.

[0459] "Translation API" means an application programming interface for accessing an external translation service, sending requests for translation of text, and receiving the results.

[0460] A "generative AI model" is an algorithm that processes data (summarizes and translates) based on machine learning and artificial intelligence.

[0461] "Data format" refers to the format for structuring and sending data, and specifically includes JSON and XML.

[0462] A "server" is a computer system that processes text data received from a user, summarizes and translates it, and returns the results.

[0463] MODE FOR CARRYING OUT THE INVENTION

[0464] The present invention is a system for automatically providing summarization and translation of text by a user, which is composed of a user interface, a terminal means, a server, a summarization algorithm means, a translation algorithm means, and a translation API.

[0465] System configuration

[0466] 1. User Interface

[0467] The user interface is the browser or application interface through which the user enters text, allowing the user to easily enter the text they wish to have summarized and translated.

[0468] 2. Terminal means

[0469] The terminal means is a device or software for transmitting text data entered by a user to a server. HTTP is used as the communication protocol, and JSON is used as the data format.

[0470] 3. Server

[0471] The server is a central processing unit that processes the text data received from the terminals, and uses a summarization algorithm means and a translation algorithm means to summarize and translate the text.

[0472] 4. Summarization Algorithm

[0473] The summarization algorithm is an algorithm that uses a generative AI model to summarize text data. It automatically extracts the main points of the received text and generates a short summary.

[0474] 5. Translation Algorithm Means

[0475] The translation algorithm means is an algorithm for translating the summarized text into a different language, in particular using an external translation API (e.g., Google Translate API).

[0476] 6. Translation API

[0477] A translation API is an application programming interface for accessing external services to perform translations.

[0478] 7. Displaying results to the user

[0479] The translated summary is sent back to the terminal and displayed to the user through a user interface.

[0480] Specific examples

[0481] 1. User Input

[0482] User: Enters the sentence "The quick brown fox jumps over the lazy dog." into the interface.

[0483] 2. Summary of results

[0484] Server: Generates a summary sentence "The fox jumps over the dog." using a summarization algorithm.

[0485] 3. Translation results

[0486] Server: Using the translation API, translate this summary into Japanese as "The fox jumps over the dog."

[0487] Prompt Sentence Examples

[0488] An example of a prompt when using a generative AI model is as follows:

[0489] English summary

[0490] "Please summarize the following text: The quick brown fox jumps over the lazy dog."

[0491] Summary English translation

[0492] "Please translate the following text to Japanese: The fox jumps over the dog."

[0493] In this way, the system of the present invention efficiently executes a series of processes from user text input, to summary generation, translation into Japanese, and final display, allowing users to quickly grasp vast amounts of information and significantly reduce the time and effort required to obtain the information they need.

[0494] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0495] Step 1:

[0496] The user inputs the text they want summarized and translated using the interface provided by the system (a text input field in a browser or application). The input text is an English sentence such as "The quick brown fox jumps over the lazy dog."

[0497] Input: The text the user types into the input field

[0498] Output: Text data entered by the user

[0499] Specific behavior:

[0500] A user opens a browser or application interface, enters text into an input field, and then presses a submit button.

[0501] Step 2:

[0502] The terminal converts the text entered in the user interface into a data format (JSON) and sends it to the server using an HTTP request.

[0503] Input: Text data entered by the user

[0504] Output: JSON format text data

[0505] Specific behavior:

[0506] The terminal converts the text received from the user interface into the following JSON format:

[0507] json

[0508] {

[0509] "text": "The quick brown fox jumps over the lazy dog."

[0510] }

[0511] This JSON data is sent to the server as an HTTP request.

[0512] Step 3:

[0513] The server analyzes the text data received from the device and passes it to a summarization algorithm means to generate a summary, which uses a generative AI model.

[0514] Input: JSON format text data

[0515] Output: Summarized text

[0516] Specific behavior:

[0517] The server extracts the value of the "text" field from the received JSON data and summarizes the sentence using a generative AI model. For example, it summarizes "The quick brown fox jumps over the lazy dog." to "The fox jumps over the dog."

[0518] Step 4:

[0519] The server passes the summarized text "The fox jumps over the dog." to a translation algorithm means, which translates it into Japanese using a translation API.

[0520] Input: Summarized text

[0521] Output: The translated text

[0522] Specific behavior:

[0523] The server sends a request to the translation API, asking it to translate the summary sentence, "The fox jumps over the dog." The translation API receives the request and returns the translation result, "The fox jumps over the dog."

[0524] Step 5:

[0525] The server formats the translated text in JSON format and sends it to the terminal as an HTTP response.

[0526] Input: Translated text

[0527] Output: Translation result data in JSON format

[0528] Specific behavior:

[0529] The server formats the translated text "The fox jumps over the dog." in the following JSON format:

[0530] json

[0531] {

[0532] "summary": "The fox jumps over the dog.",

[0533] "translation": "The fox jumps over the dog."

[0534] }

[0535] This data is sent to the terminal as an HTTP response.

[0536] Step 6:

[0537] The terminal displays the translation results received from the server on a user interface.

[0538] Input: Translation result data in JSON format

[0539] Output: The translation result displayed in the user interface

[0540] Specific behavior:

[0541] The device extracts the value of the "translation" field from the received JSON data and displays "The fox jumps over the dog" on the user interface, allowing the user to view the translated summary.

[0542] (Application example 1)

[0543] Next, a description will be given of Application 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."

[0544] At logistics centers, staff are required to efficiently understand lengthy logistics information written in multiple languages. However, manual summarization and translation takes time and effort, reducing work efficiency. To solve this issue and improve work efficiency, it is necessary to quickly and accurately summarize and translate information and provide it in a format that is easy for on-site staff to understand.

[0545] 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.

[0546] In this invention, the server includes means for providing a user interface for a user to input text, terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to the server, summarization algorithm means for summarizing the received text, translation algorithm means for translating the summarized text, means for transmitting the translated summary to the terminal, means for displaying the translation result transmitted to the terminal to the user, and means for displaying the summary and translated text to warehouse staff for logistics information. This enables logistics center staff to efficiently summarize and translate lengthy logistics information written in multiple languages ​​and quickly understand it.

[0547] A "user interface" is a screen or input device that allows a user to perform operations or input data to a system.

[0548] The "terminal means" is a device that has the function of receiving data input to a user interface, converting it into an appropriate data format, and transmitting it to a server.

[0549] A "summarization algorithm" is a program or process that extracts the main points from input text and generates a shortened summary.

[0550] A "translation algorithmic means" is a program or process for converting text written in one language into another language.

[0551] A "translation API" is an application program interface that provides translation functionality by accessing external translation services.

[0552] "Logistics information" refers to information managed by a logistics center, such as arrival information and shipping information.

[0553] "Warehouse staff" refers to workers and managers engaged in operations at logistics centers.

[0554] The "system" refers to a collection of a user interface, a terminal means, a summarization algorithm means, a translation algorithm means, and a server and a network for linking these together to operate.

[0555] "Multilingual" means two or more different languages.

[0556] A "long text" is a text that contains a large amount of information and is made up of multiple sentences or paragraphs.

[0557] A "server" is a computer system that provides information and processing power over a network.

[0558] A "data format" is a set of rules or formats for structuring and storing data.

[0559] The present invention aims to realize a system that efficiently summarizes long multilingual logistics information at a logistics center and provides the translated information to warehouse staff. This system is configured as follows.

[0560] First, a user uses a device such as a smartphone or tablet to input long multilingual text from a user interface, such as detailed information about incoming shipments or shipping status.

[0561] The terminal receives data entered by the user, converts it into a data format, and sends it to the server. JSON is a suitable data format for this purpose. An HTTP request is used to send data from the terminal to the server.

[0562] The server processes the received text data with a summarization algorithm means. The summarization algorithm means uses a specific statistical or machine learning algorithm to extract the main points of the text and generate a short summary. For example, the text "The shipment of 100 boxes of electronics has been delayed due to unexpected customs clearance issues, and will arrive by the end of next week." is summarized as the main information "The shipment of electronics has been delayed."

[0563] Next, the summarized text is translated into a desired language by a translation algorithm means. The translation algorithm means uses an external translation API to translate the summarized text into, for example, Japanese. For example, the translation API used is "https: / / api.translation.example.com / v1 / translate". The translation result is "Shipments of electronic devices are delayed."

[0564] The server then sends the translated summary back to the terminal in JSON format. The terminal then displays the translation results received from the server to the user through a user interface. Warehouse staff can quickly understand the translated summary and efficiently carry out their required tasks.

[0565] A concrete example would be the following scenario: Warehouse staff can input lengthy incoming goods information on their own devices, and receive a summary and translation of the information in a short time, enabling them to take appropriate action promptly.

[0566] Examples of prompts to be input to a generative AI model include:

[0567] Language used: Python

[0568] Objective: Write a program to summarize and translate lengthy logistics information for warehouse staff.

[0569] Assume that the summarized text is to be translated into Japanese.

[0570] In this way, the system of the present invention can efficiently summarize lengthy logistics information in multiple languages ​​and provide translated information, thereby significantly improving the operational efficiency of logistics centers.

[0571] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0572] Step 1:

[0573] Users use a smartphone or tablet device to input long multilingual text into the user interface. This input text is treated as the system's initial data. For example, specific text such as "The shipment of 100 boxes of electronics has been delayed due to unexpected customs clearance issues, and will arrive by the end of next week." is input.

[0574] Step 2:

[0575] The terminal receives text data entered by the user and converts it into a data format, for example, JSON format. In this process, the text data is structured as a JSON object, making it a format that can be sent to the next processing step. This converted data is then sent to the server using an HTTP request.

[0576] Step 3:

[0577] The server processes the text data received from the device using a summarization algorithm. Specifically, it uses machine learning or statistical algorithms to extract key points and generate a short summary. It analyzes the input long text and outputs a summary sentence, such as "The shipment of electronics has been delayed."

[0578] Step 4:

[0579] The server then translates the summary generated by the summarization algorithm into the desired language using a translation algorithm. This translation uses an external translation API, and the summary is sent to the API to obtain the translation result. The translation API translates the input summary into the corresponding language, and outputs a translation result such as "Shipments of electronic devices are delayed."

[0580] Step 5:

[0581] The server restructures the translated summary and formats it again in JSON format. This JSON data is sent to the terminal as an HTTP response. Here, the translation result text is properly formatted and provided as a response to the terminal.

[0582] Step 6:

[0583] The terminal displays the translation results received from the server to the user through a user interface. Warehouse staff visually check the displayed translation results and perform the necessary tasks quickly and efficiently. In this step, the process of displaying the specific data received on the screen is carried out.

[0584] 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.

[0585] As an embodiment of the present invention, a system is constructed that automatically provides summarization, translation, and user emotion recognition. Below, the program processing of this system and a specific example of its operation will be described.

[0586] The system consists of a user interface, a terminal, a server, a summarization algorithm, a translation algorithm, a translation API, and an emotion engine. Users access the system through a browser or an application and input text to be summarized and translated. At the same time, the emotion engine recognizes the user's emotions and provides the optimal summary and translation based on those emotions.

[0587] System processing flow

[0588] 1. User text input

[0589] The user inputs the text they want to summarize and translate using an interface (e.g., a text input field) provided by the system. For example, the user inputs the English sentence, "The quick brown fox jumps over the lazy dog."

[0590] 2. Sending text from the device to the server

[0591] When the user completes the input and presses the send button, the terminal sends this text to the server in JSON format, specifically via an HTTP request.

[0592] 3. Emotion Recognition by the Server

[0593] The server analyzes the received text data with an emotion engine to identify the user's emotion (positive, negative, neutral). For example, in the case of the text "I am very happy with the service," a positive emotion is recognized.

[0594] 4. Server-generated text summarization

[0595] The server processes the text using a summarization algorithm to extract key points and generate a short summary. For example, the received text "The quick brown fox jumps over the lazy dog." is processed by the summarization algorithm and summarized as "The fox jumps over the dog."

[0596] 5. Japanese translation of the summary

[0597] The summarized text "The fox jumps over the dog." is translated into Japanese by means of a translation algorithm. Using a translation API, a translation request is sent to an external service. The translation result is "The fox jumps over the dog."

[0598] 6. Sending translation results to your device

[0599] The translated summary is sent back to the device from the server, where it is again formatted in JSON and sent as an HTTP response.

[0600] 7. Displaying results to the user

[0601] The terminal receives the translation result from the server and displays it to the user. The user can view the translated summary through a browser or application interface.

[0602] Specific examples

[0603] 1. User Input

[0604] User types: "The quick brown fox jumps over the lazy dog."

[0605] 2. Emotion recognition

[0606] The server's emotion engine analyzes the text and determines the user's emotion as "neutral."

[0607] 3. Summary of results

[0608] Summary by server's summarization algorithm: "The fox jumps over the dog."

[0609] 4. Translation Results

[0610] Japanese translation by translation algorithm: "The fox jumps over the dog."

[0611] This allows users to easily obtain summaries and translation results that correspond to their emotions. By optimizing and automating this process, the system significantly reduces time and effort. The addition of an emotion engine makes it possible to provide optimal information according to the user's emotional state.

[0612] The processing flow will be explained below.

[0613] Step 1:

[0614] User enters text. In a text input field in a browser or app, the user enters the text they want summarized and translated. For example, they enter the sentence "The quick brown fox jumps over the lazy dog."

[0615] Step 2:

[0616] The terminal receives the user's input. When the user presses the "Send" button, the terminal receives the entered text and prepares to send this data to the server.

[0617] Step 3:

[0618] The device sends text to the server. The device converts the received text into an appropriate data format (e.g., JSON) and sends it to the server using an HTTP request.

[0619] Step 4:

[0620] The server receives the request. When the server receives the HTTP request sent from the terminal, it extracts the text data.

[0621] Step 5:

[0622] The server calls the emotion engine to analyze the text. The server passes the received text to the emotion engine, which analyzes the emotion (positive, negative, neutral) expressed by the text. For example, if the sentence says "I am very happy with the service," the emotion engine will recognize the positive emotion.

[0623] Step 6:

[0624] The server applies a summarization algorithm. Based on the sentiment analysis results, the server uses a summarization algorithm to summarize the received text. For example, the input "The quick brown fox jumps over the lazy dog." is summarized as "The fox jumps over the dog."

[0625] Step 7:

[0626] The server invokes the translation algorithm. The server passes the summarized text to the translation algorithm or an external translation API to translate it into the specified language. For example, translating the English summary sentence "The fox jumps over the dog." into Japanese.

[0627] Step 8:

[0628] The server receives the translation result. The server receives the Japanese summary result "The fox jumps over the dog." returned from the translation API and formats it as necessary.

[0629] Step 9:

[0630] The server formats the results in JSON format and sends the response to the device. The server then formats the response containing the translated summary results in JSON format and sends it to the device as an HTTP response.

[0631] Step 10:

[0632] The device receives the response and displays the result to the user. The device analyzes the response received from the server and displays the translated summary on the screen. The user can see the translation result, "The fox jumps over the dog," on the browser or application screen.

[0633] This processing step realizes a system that efficiently provides summaries and translation results to users and presents optimal information based on the user's emotions.

[0634] Example 2

[0635] Next, a description will be given of 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."

[0636] In modern digital communication, users are seeking efficient ways to summarize and translate large amounts of text. However, conventional systems generate uniform summaries and translations without considering the user's feelings, making it impossible to provide appropriate information that meets the user's needs. Furthermore, even when communicating between different languages, manual translation and summarization is time-consuming and labor-intensive.

[0637] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for providing a user interface for a user to input text, terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to the server, emotion engine means for recognizing the emotion of the received text, summarization algorithm means for summarizing the received text, translation algorithm means for translating the summarized text, means for transmitting the translated summary to the terminal, and means for displaying the translation result transmitted to the terminal to the user. This enables appropriate summaries and translations that take the user's emotions into consideration to be automatically provided, significantly reducing time and effort.

[0638] A "user" is an entity that uses the system to input text and receive results such as summaries and translations.

[0639] An "interface" is a structure on a system that contains the means by which a user inputs text and the elements used to validate that input.

[0640] "Terminal means" refers to a device or software that has the function of receiving text entered by a user, converting it into a data format, and sending it to a server.

[0641] An "emotion engine means" is an algorithm or software that analyzes received text and recognizes the user's emotions.

[0642] A "summarization algorithm" is a technique or algorithm that processes input text, extracts important information, and generates a short summary.

[0643] A "translation algorithm means" is a technique or algorithm for translating the summarized text into another language.

[0644] "Translation API" means an application programming interface for connecting to an external translation service to translate text.

[0645] "Data format" refers to the structure or format of data used when a terminal means communicates with a server, and includes, for example, JSON and XML.

[0646] An "HTTP request" is a communication protocol used to send text and other data between a device and a server.

[0647] An "HTTP response" is response data that the server sends to the terminal, and specifically includes the translation and summary results of the input text.

[0648] This invention is a system that efficiently summarizes and translates text entered by a user. It is particularly characterized by its ability to provide more appropriate summarization and translation results by taking into account the user's emotional state. This system is comprised of a user interface, a terminal device, a server, an emotion engine, a summarization algorithm, a translation algorithm, and a translation API.

[0649] The user accesses the system using a browser or application and enters the text they want to summarize and translate in the text input field. The entered text is temporarily stored on the device and sent to the server in JSON format when the submit button is pressed.

[0650] The server receives the text sent from the device and analyzes the sentiment of the text using an emotion engine. The emotion engine uses a natural language processing algorithm to identify the most appropriate emotion from three emotion categories: positive, negative, and neutral. The received text is then summarized by a summarization algorithm. The summarization algorithm uses statistical methods and machine learning algorithms to extract key information and generate a short summary.

[0651] Next, the generated summary is translated into another language (e.g., Japanese) using a translation algorithm. A translation API is used to send a request to an external service, such as the Google Translate API. The server receives the response from the translation API and obtains the translation result. After obtaining the translation result, the server sends it to the terminal in JSON format.

[0652] The device then displays the translation results received from the server in the browser or application, allowing the user to view a summary of the text they entered and the translation results.

[0653] For example, consider the following prompt:

[0654] If the English sentence "The quick brown fox jumps over the lazy dog" is input into the system, the emotion engine will analyze the sentence as neutral, and the summarization algorithm will generate the summary "The fox jumps over the dog." This will then be translated into Japanese by the translation algorithm, resulting in the result "The fox jumps over the dog." Finally, the user can view this translation result in their browser or application.

[0655] By incorporating sentiment analysis, this system not only provides appropriate information according to the user's emotional state, but also enables efficient communication across multiple languages, thereby saving users a great deal of time and effort.

[0656] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0657] Step 1:

[0658] User:

[0659] A user accesses the system using a browser or application and enters the text they want summarized and translated into the text input field. An example of the text entered is "The quick brown fox jumps over the lazy dog." The system recognizes the entered text.

[0660] Step 2:

[0661] Device:

[0662] When the user presses the send button, the terminal temporarily saves the entered text, converts it to JSON format, and generates an HTTP POST request. This request contains the entered text data. The terminal then sends this to the server. The input is the user's text, and the output is an HTTP request in JSON format.

[0663] Step 3:

[0664] server:

[0665] The server receives JSON-formatted text sent from the terminal. The received data is parsed as raw text data. The input is the JSON data sent from the terminal, and the output is parseable text data.

[0666] Step 4:

[0667] server:

[0668] The server calls the emotion engine to analyze the emotion of the received text. The emotion engine uses natural language processing algorithms to classify the text as positive, negative, or neutral. For example, if the text is "I am very happy with the service," the emotion engine will recognize it as a positive emotion. The input is the parseable text data, and the output is the emotion category.

[0669] Step 5:

[0670] server:

[0671] After emotion recognition is complete, the server invokes a summarization algorithm to summarize the text. The summarization algorithm uses statistical methods and machine learning algorithms to extract important information and generate a short summary. For example, "The quick brown fox jumps over the lazy dog." can be summarized as "The fox jumps over the dog." The input is the text data after emotion recognition, and the output is the summary.

[0672] Step 6:

[0673] server:

[0674] The generated summary is then translated into another language (e.g., Japanese) by a translation algorithm. The translation algorithm sends a request to an external translation API (e.g., Google Translate API) to obtain the translation result. For example, the summary "The fox jumps over the dog." is translated to "The fox jumps over the dog." The input is the summary, and the output is the translation result.

[0675] Step 7:

[0676] server:

[0677] The server repackages the translation results in JSON format and sends them to the terminal as an HTTP response. The input is the translation results, and the output is the JSON-formatted HTTP response.

[0678] Step 8:

[0679] Device:

[0680] The terminal receives the HTTP response from the server and parses the data again. The parsed translation result is displayed on the user interface. The input is the JSON data received from the server, and the output is the display to the user.

[0681] Step 9:

[0682] User:

[0683] The user checks the translation results displayed on the screen of the terminal, allowing them to visually check the summary of the input text and its translation results.

[0684] (Application example 2)

[0685] Next, a description will be given of Application 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."

[0686] In today's advertising industry, there is a demand for fast and accurate delivery of advertisements that match user emotions. However, conventional ad generation methods have difficulty customizing advertisements that take user emotions into account, resulting in ineffective ad presentation. Furthermore, there is no system that can automatically summarize and translate user-provided text at the same time, which leads to a poor user experience.

[0687] 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.

[0688] In this invention, the server includes emotion recognition means for recognizing the emotion of the received text, summarization algorithm means for summarizing the received text based on the emotion information obtained by the emotion recognition means, and translation algorithm means for translating the summarized text, thereby enabling the automatic generation of customized advertisements based on the user's emotions, as well as the summarization and translation of the advertisements, thereby enabling effective advertisement presentation and an improved user experience.

[0689] A "user interface" is an input means by which a user enters text and interacts with a system.

[0690] "Terminal means" refers to a device or software for receiving text entered at a user interface, converting it into a data format, and transmitting it to a server.

[0691] An "emotion recognizer" is an algorithm or engine for analyzing a user's emotions from received text and identifying positive, negative, or neutral emotions.

[0692] The "summarization algorithm means" is an algorithm for extracting important points of the text and generating a concise summary based on the received text and its sentiment information.

[0693] "Translation algorithm means" is an algorithm for translating the summarized text into a different language, which may use an external translation API.

[0694] A "translation API" is a program interface for translating text into a specified language using a translation function provided as an external service.

[0695] The "means for transmitting to the terminal" is a communication means for transmitting the translated summary from the server to the terminal.

[0696] The "display means" refers to a display device or display software for visually presenting the translation results on the user's terminal.

[0697] This invention is a system that generates advertisements based on user emotions and automatically summarizes and translates them. Specific embodiments for implementing this system will be described in detail below.

[0698] System Overview

[0699] This system is composed of a user, a terminal, and a server, and includes a user interface, emotion recognition, a summarization algorithm, a translation algorithm, and means for displaying results.

[0700] Hardware and software used

[0701] Hardware: Smartphones, servers

[0702] Software: Python, textblob library (emotion recognition), googletrans library (translation)

[0703] Data processing and calculation methods

[0704] 1. Providing a user interface

[0705] The device provides a user interface that allows the user to input text, which can be achieved through a smartphone application or a web browser.

[0706] 2. Entering and Receiving Text

[0707] The user inputs text, the device receives the input text, and sends it to the server, using JSON as the data format.

[0708] 3. Emotion recognition

[0709] The server analyzes the received text using an emotion recognition means (textblob library) to identify positive, negative, or neutral emotions.

[0710] 4. Summary Generation

[0711] Based on the sentiment information, the server uses a summarization algorithm to extract key points of the text and generate a summary.

[0712] 5. Translation of Abstracts

[0713] The summarized text is translated into the specified language by means of a translation algorithm (googletrans library), possibly using an external translation API.

[0714] 6. Results transmission and display

[0715] The translated summary is sent from the server to the terminal and displayed to the user through a user interface.

[0716] Specific examples

[0717] 1. User Input

[0718] The user enters the text "I love the new features in this product!"

[0719] 2. Emotion recognition

[0720] The server's emotion recognition means analyzes this text and determines positive emotions.

[0721] 3. Summary Generation

[0722] A summarization algorithm means summarizes this text and produces "Love new features product!"

[0723] 4. Translation Results

[0724] A translation algorithm means translates this summary into Japanese and produces "I love the new features!"

[0725] Prompt Sentence Examples

[0726] Example prompt for generative AI model:

[0727] Use the translation API to translate the following text into Japanese: "I love the new features!"

[0728] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0729] Step 1:

[0730] The user enters text

[0731] A user inputs text that will be used to generate an advertisement using a user interface provided by a smartphone application or a web browser. The input text is then sent to the device via the user interface (e.g., "I love the new features in this product!").

[0732] Step 2:

[0733] The device sends the text to the server

[0734] The device receives the text entered by the user, converts it into a data format (JSON format), and then sends it to the server using an HTTP request. Input: User text (e.g., "I love the new features in this product!") Output: JSON-formatted text data

[0735] Step 3:

[0736] The server recognizes emotions

[0737] The server analyzes the received text data using emotion recognition (textblob library) to identify positive, negative, or neutral emotions. Input: Text data in JSON format. Output: Emotion score and emotion category (e.g., positive).

[0738] Step 4:

[0739] The server summarizes the text

[0740] The server uses a summarization algorithm to extract key points from the received text based on the emotion information and generate a short summary. Input: Emotion-recognized text (e.g., "I love the new features in this product!") Output: Summarized text (e.g., "Love new features product!")

[0741] Step 5:

[0742] The server translates the summary

[0743] The server translates the summarized text into the specified language using a translation algorithm (googletrans library), possibly using an external translation API. Input: Summarized text (e.g. "Love new features product!") Output: Translated text (e.g. "Love the new features product!")

[0744] Step 6:

[0745] The server sends the translated summary to the device

[0746] The server converts the translated summary into JSON format and sends it to the device using an HTTP response. Input: Translated text (e.g., "I love the new feature!") Output: Translation data in JSON format

[0747] Step 7:

[0748] The device displays the translation results to the user

[0749] The device displays the translation data received from the server on the user interface and notifies the user of the results. Input: Translation data in JSON format Output: Translation results displayed to the user (e.g., "I love the new features!")

[0750] 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.

[0751] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[0752] 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.

[0753] [Third embodiment]

[0754] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0755] 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.

[0756] 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).

[0757] 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.

[0758] 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.

[0759] 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).

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0766] As an embodiment of the present invention, a system for automatically providing summaries and translations is constructed. The program processing of this system and a specific example of its operation will be described below.

[0767] The system consists of a user interface, a terminal, a server, a summarization algorithm, a translation algorithm, and a translation API. Users access the system through a browser or an application and input text to be summarized and translated.

[0768] System processing flow

[0769] 1. User text input

[0770] The user inputs the text they want to summarize and translate using an interface (e.g., a text input field) provided by the system. For example, the user inputs the English sentence, "The quick brown fox jumps over the lazy dog."

[0771] 2. Sending text from the device to the server

[0772] When the user completes the input and presses the send button, the terminal sends this text to the server in JSON format, specifically via an HTTP request.

[0773] 3. Server-generated text summarization

[0774] The server processes the text data received from the device using a summarization algorithm. The main points of the text are extracted and a short summary is generated. For example, the received text "The quick brown fox jumps over the lazy dog." is processed by the summarization algorithm and summarized as "The fox jumps over the dog."

[0775] 4. Japanese translation of the summary

[0776] The summarized text "The fox jumps over the dog." is then translated into Japanese by means of a translation algorithm. Using a translation API, a translation request is sent to an external service. The translation result is "The fox jumps over the dog."

[0777] 5. Send the translation results to your device

[0778] The translated summary is sent back to the device from the server, where it is again formatted in JSON and sent as an HTTP response.

[0779] 6. Displaying results to the user

[0780] The terminal receives the translation result from the server and displays it to the user. The user can view the translated summary through a browser or application interface.

[0781] In this way, the system of the present invention efficiently executes a series of processes from user text input, to summary generation, translation into Japanese, and final display, enabling users to quickly grasp vast amounts of information and significantly reduce the time and effort required to obtain the information they need.

[0782] Specific examples

[0783] 1. User Input

[0784] User types: "The quick brown fox jumps over the lazy dog."

[0785] 2. Summary of results

[0786] Summary by server's summarization algorithm: "The fox jumps over the dog."

[0787] 3. Translation results

[0788] Japanese translation by translation algorithm: "The fox jumps over the dog."

[0789] This allows users to easily obtain summaries and their translation results.By optimizing and automating this process, the system significantly reduces time and effort.

[0790] The processing flow will be explained below.

[0791] Step 1:

[0792] User enters text: The user enters the text they want summarized and translated into a text input field in their browser or app.

[0793] Step 2:

[0794] The terminal receives the user's input. When the user presses the Send button, the terminal receives the entered text.

[0795] Step 3:

[0796] The device sends text to the server. The device converts the received text into an appropriate data format (e.g., JSON) and sends it to the server using an HTTP request.

[0797] Step 4:

[0798] The server receives the request. The server receives the HTTP request sent from the terminal and extracts the text data.

[0799] Step 5:

[0800] The server applies the summarization algorithm: The server invokes the summarization algorithm, passing the received text as input. The algorithm extracts important sentences and keywords and generates a shortened summary.

[0801] Step 6:

[0802] The server stores the summary results. The server temporarily stores the generated summary results in memory.

[0803] Step 7:

[0804] The server invokes the translation algorithm, and passes the stored summary text to another translation algorithm or an external translation API (e.g., translation API) to translate it into Japanese.

[0805] Step 8:

[0806] The server receives the translation results, receives the Japanese summary results sent from the translation API, and formats them as necessary.

[0807] Step 9:

[0808] The server formats the results in JSON. The server formats a response containing the translated summary results in JSON.

[0809] Step 10:

[0810] The server sends the response to the terminal. The formatted data is sent to the terminal as an HTTP response.

[0811] Step 11:

[0812] The terminal receives the response. The terminal receives the response from the server and analyzes the data.

[0813] Step 12:

[0814] The terminal displays the results to the user. The terminal displays a summary of the analyzed Japanese text on the screen and informs the user of the results.

[0815] Example 1

[0816] Next, a description will be given of 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."

[0817] Conventional information processing systems have had difficulty efficiently summarizing large amounts of text data and translating it into different languages. In particular, the quality of summarization and translation is low, making it difficult to provide users with the fast and accurate information they require.

[0818] 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.

[0819] In this invention, the server includes a means for providing a user interface, a terminal means for receiving text data, converting it into a data format, and transmitting the data to the server, a summarization algorithm means, a translation algorithm means, a means for transmitting a translated summary to the terminal, and a means for displaying the translated summary to the user. This makes it possible to efficiently summarize large amounts of text data and quickly provide highly accurate translations.

[0820] "User interface" means an interface through which a user accesses a system and inputs or receives information.

[0821] "Terminal means" refers to a device or software for transmitting data entered by a user to a server.

[0822] The "summarization algorithm means" is an algorithm that processes input text data, extracts its main information, and generates a short summary.

[0823] A "translation algorithm means" is an algorithm for translating the summarized text into a different language.

[0824] "Translation API" means an application programming interface for accessing an external translation service, sending requests for translation of text, and receiving the results.

[0825] A "generative AI model" is an algorithm that processes data (summarizes and translates) based on machine learning and artificial intelligence.

[0826] "Data format" refers to the format for structuring and sending data, and specifically includes JSON and XML.

[0827] A "server" is a computer system that processes text data received from a user, summarizes and translates it, and returns the results.

[0828] MODE FOR CARRYING OUT THE INVENTION

[0829] The present invention is a system for automatically providing summarization and translation of text by a user, which is composed of a user interface, a terminal means, a server, a summarization algorithm means, a translation algorithm means, and a translation API.

[0830] System configuration

[0831] 1. User Interface

[0832] The user interface is the browser or application interface through which the user enters text, allowing the user to easily enter the text they wish to have summarized and translated.

[0833] 2. Terminal means

[0834] The terminal means is a device or software for transmitting text data entered by a user to a server. HTTP is used as the communication protocol, and JSON is used as the data format.

[0835] 3. Server

[0836] The server is a central processing unit that processes the text data received from the terminals, and uses a summarization algorithm means and a translation algorithm means to summarize and translate the text.

[0837] 4. Summarization Algorithm

[0838] The summarization algorithm is an algorithm that uses a generative AI model to summarize text data. It automatically extracts the main points of the received text and generates a short summary.

[0839] 5. Translation Algorithm Means

[0840] The translation algorithm means is an algorithm for translating the summarized text into a different language, in particular using an external translation API (e.g., Google Translate API).

[0841] 6. Translation API

[0842] A translation API is an application programming interface for accessing external services to perform translations.

[0843] 7. Displaying results to the user

[0844] The translated summary is sent back to the terminal and displayed to the user through a user interface.

[0845] Specific examples

[0846] 1. User Input

[0847] User: Enters the sentence "The quick brown fox jumps over the lazy dog." into the interface.

[0848] 2. Summary of results

[0849] Server: Generates a summary sentence "The fox jumps over the dog." using a summarization algorithm.

[0850] 3. Translation results

[0851] Server: Using the translation API, translate this summary into Japanese as "The fox jumps over the dog."

[0852] Prompt Sentence Examples

[0853] An example of a prompt when using a generative AI model is as follows:

[0854] English summary

[0855] "Please summarize the following text: The quick brown fox jumps over the lazy dog."

[0856] Summary English translation

[0857] "Please translate the following text to Japanese: The fox jumps over the dog."

[0858] In this way, the system of the present invention efficiently executes a series of processes from user text input, to summary generation, translation into Japanese, and final display, allowing users to quickly grasp vast amounts of information and significantly reduce the time and effort required to obtain the information they need.

[0859] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0860] Step 1:

[0861] The user inputs the text they want summarized and translated using the interface provided by the system (a text input field in a browser or application). The input text is an English sentence such as "The quick brown fox jumps over the lazy dog."

[0862] Input: The text the user types into the input field

[0863] Output: Text data entered by the user

[0864] Specific behavior:

[0865] A user opens a browser or application interface, enters text into an input field, and then presses a submit button.

[0866] Step 2:

[0867] The terminal converts the text entered in the user interface into a data format (JSON) and sends it to the server using an HTTP request.

[0868] Input: Text data entered by the user

[0869] Output: JSON format text data

[0870] Specific behavior:

[0871] The terminal converts the text received from the user interface into the following JSON format:

[0872] json

[0873] {

[0874] "text": "The quick brown fox jumps over the lazy dog."

[0875] }

[0876] This JSON data is sent to the server as an HTTP request.

[0877] Step 3:

[0878] The server analyzes the text data received from the device and passes it to a summarization algorithm means to generate a summary, which uses a generative AI model.

[0879] Input: JSON format text data

[0880] Output: Summarized text

[0881] Specific behavior:

[0882] The server extracts the value of the "text" field from the received JSON data and summarizes the sentence using a generative AI model. For example, it summarizes "The quick brown fox jumps over the lazy dog." to "The fox jumps over the dog."

[0883] Step 4:

[0884] The server passes the summarized text "The fox jumps over the dog." to a translation algorithm means, which translates it into Japanese using a translation API.

[0885] Input: Summarized text

[0886] Output: The translated text

[0887] Specific behavior:

[0888] The server sends a request to the translation API, asking it to translate the summary sentence, "The fox jumps over the dog." The translation API receives the request and returns the translation result, "The fox jumps over the dog."

[0889] Step 5:

[0890] The server formats the translated text in JSON format and sends it to the terminal as an HTTP response.

[0891] Input: Translated text

[0892] Output: Translation result data in JSON format

[0893] Specific behavior:

[0894] The server formats the translated text "The fox jumps over the dog." in the following JSON format:

[0895] json

[0896] {

[0897] "summary": "The fox jumps over the dog.",

[0898] "translation": "The fox jumps over the dog."

[0899] }

[0900] This data is sent to the terminal as an HTTP response.

[0901] Step 6:

[0902] The terminal displays the translation results received from the server on a user interface.

[0903] Input: Translation result data in JSON format

[0904] Output: The translation result displayed in the user interface

[0905] Specific behavior:

[0906] The device extracts the value of the "translation" field from the received JSON data and displays "The fox jumps over the dog" on the user interface, allowing the user to view the translated summary.

[0907] (Application example 1)

[0908] Next, a description will be given of Application 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."

[0909] At logistics centers, staff are required to efficiently understand lengthy logistics information written in multiple languages. However, manual summarization and translation takes time and effort, reducing work efficiency. To solve this issue and improve work efficiency, it is necessary to quickly and accurately summarize and translate information and provide it in a format that is easy for on-site staff to understand.

[0910] 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.

[0911] In this invention, the server includes means for providing a user interface for a user to input text, terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to the server, summarization algorithm means for summarizing the received text, translation algorithm means for translating the summarized text, means for transmitting the translated summary to the terminal, means for displaying the translation result transmitted to the terminal to the user, and means for displaying the summary and translated text to warehouse staff for logistics information. This enables logistics center staff to efficiently summarize and translate lengthy logistics information written in multiple languages ​​and quickly understand it.

[0912] A "user interface" is a screen or input device that allows a user to perform operations or input data to a system.

[0913] The "terminal means" is a device that has the function of receiving data input to a user interface, converting it into an appropriate data format, and transmitting it to a server.

[0914] A "summarization algorithm" is a program or process that extracts the main points from input text and generates a shortened summary.

[0915] A "translation algorithmic means" is a program or process for converting text written in one language into another language.

[0916] A "translation API" is an application program interface that provides translation functionality by accessing external translation services.

[0917] "Logistics information" refers to information managed by a logistics center, such as arrival information and shipping information.

[0918] "Warehouse staff" refers to workers and managers engaged in operations at logistics centers.

[0919] The "system" refers to a collection of a user interface, a terminal means, a summarization algorithm means, a translation algorithm means, and a server and a network for linking these together to operate.

[0920] "Multilingual" means two or more different languages.

[0921] A "long text" is a text that contains a large amount of information and is made up of multiple sentences or paragraphs.

[0922] A "server" is a computer system that provides information and processing power over a network.

[0923] A "data format" is a set of rules or formats for structuring and storing data.

[0924] The present invention aims to realize a system that efficiently summarizes long multilingual logistics information at a logistics center and provides the translated information to warehouse staff. This system is configured as follows.

[0925] First, a user uses a device such as a smartphone or tablet to input long multilingual text from a user interface, such as detailed information about incoming shipments or shipping status.

[0926] The terminal receives data entered by the user, converts it into a data format, and sends it to the server. JSON is a suitable data format for this purpose. An HTTP request is used to send data from the terminal to the server.

[0927] The server processes the received text data with a summarization algorithm means. The summarization algorithm means uses a specific statistical or machine learning algorithm to extract the main points of the text and generate a short summary. For example, the text "The shipment of 100 boxes of electronics has been delayed due to unexpected customs clearance issues, and will arrive by the end of next week." is summarized as the main information "The shipment of electronics has been delayed."

[0928] Next, the summarized text is translated into a desired language by a translation algorithm means. The translation algorithm means uses an external translation API to translate the summarized text into, for example, Japanese. For example, the translation API used is "https: / / api.translation.example.com / v1 / translate". The translation result is "Shipments of electronic devices are delayed."

[0929] The server then sends the translated summary back to the terminal in JSON format. The terminal then displays the translation results received from the server to the user through a user interface. Warehouse staff can quickly understand the translated summary and efficiently carry out their required tasks.

[0930] A concrete example would be the following scenario: Warehouse staff can input lengthy incoming goods information on their own devices, and receive a summary and translation of the information in a short time, enabling them to take appropriate action promptly.

[0931] Examples of prompts to be input to a generative AI model include:

[0932] Language used: Python

[0933] Objective: Write a program to summarize and translate lengthy logistics information for warehouse staff.

[0934] Assume that the summarized text is to be translated into Japanese.

[0935] In this way, the system of the present invention can efficiently summarize lengthy logistics information in multiple languages ​​and provide translated information, thereby significantly improving the operational efficiency of logistics centers.

[0936] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0937] Step 1:

[0938] Users use a smartphone or tablet device to input long multilingual text into the user interface. This input text is treated as the system's initial data. For example, specific text such as "The shipment of 100 boxes of electronics has been delayed due to unexpected customs clearance issues, and will arrive by the end of next week." is input.

[0939] Step 2:

[0940] The terminal receives text data entered by the user and converts it into a data format, for example, JSON format. In this process, the text data is structured as a JSON object, making it a format that can be sent to the next processing step. This converted data is then sent to the server using an HTTP request.

[0941] Step 3:

[0942] The server processes the text data received from the device using a summarization algorithm. Specifically, it uses machine learning or statistical algorithms to extract key points and generate a short summary. It analyzes the input long text and outputs a summary sentence, such as "The shipment of electronics has been delayed."

[0943] Step 4:

[0944] The server then translates the summary generated by the summarization algorithm into the desired language using a translation algorithm. This translation uses an external translation API, and the summary is sent to the API to obtain the translation result. The translation API translates the input summary into the corresponding language, and outputs a translation result such as "Shipments of electronic devices are delayed."

[0945] Step 5:

[0946] The server restructures the translated summary and formats it again in JSON format. This JSON data is sent to the terminal as an HTTP response. Here, the translation result text is properly formatted and provided as a response to the terminal.

[0947] Step 6:

[0948] The terminal displays the translation results received from the server to the user through a user interface. Warehouse staff visually check the displayed translation results and perform the necessary tasks quickly and efficiently. In this step, the process of displaying the specific data received on the screen is carried out.

[0949] 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.

[0950] As an embodiment of the present invention, a system is constructed that automatically provides summarization, translation, and user emotion recognition. Below, the program processing of this system and a specific example of its operation will be described.

[0951] The system consists of a user interface, a terminal, a server, a summarization algorithm, a translation algorithm, a translation API, and an emotion engine. Users access the system through a browser or an application and input text to be summarized and translated. At the same time, the emotion engine recognizes the user's emotions and provides the optimal summary and translation based on those emotions.

[0952] System processing flow

[0953] 1. User text input

[0954] The user inputs the text they want to summarize and translate using an interface (e.g., a text input field) provided by the system. For example, the user inputs the English sentence, "The quick brown fox jumps over the lazy dog."

[0955] 2. Sending text from the device to the server

[0956] When the user completes the input and presses the send button, the terminal sends this text to the server in JSON format, specifically via an HTTP request.

[0957] 3. Emotion Recognition by the Server

[0958] The server analyzes the received text data with an emotion engine to identify the user's emotion (positive, negative, neutral). For example, in the case of the text "I am very happy with the service," a positive emotion is recognized.

[0959] 4. Server-generated text summarization

[0960] The server processes the text using a summarization algorithm to extract key points and generate a short summary. For example, the received text "The quick brown fox jumps over the lazy dog." is processed by the summarization algorithm and summarized as "The fox jumps over the dog."

[0961] 5. Japanese translation of the summary

[0962] The summarized text "The fox jumps over the dog." is translated into Japanese by means of a translation algorithm. Using a translation API, a translation request is sent to an external service. The translation result is "The fox jumps over the dog."

[0963] 6. Sending translation results to your device

[0964] The translated summary is sent back to the device from the server, where it is again formatted in JSON and sent as an HTTP response.

[0965] 7. Displaying results to the user

[0966] The terminal receives the translation result from the server and displays it to the user. The user can view the translated summary through a browser or application interface.

[0967] Specific examples

[0968] 1. User Input

[0969] User types: "The quick brown fox jumps over the lazy dog."

[0970] 2. Emotion recognition

[0971] The server's emotion engine analyzes the text and determines the user's emotion as "neutral."

[0972] 3. Summary of results

[0973] Summary by server's summarization algorithm: "The fox jumps over the dog."

[0974] 4. Translation Results

[0975] Japanese translation by translation algorithm: "The fox jumps over the dog."

[0976] This allows users to easily obtain summaries and translation results that correspond to their emotions. By optimizing and automating this process, the system significantly reduces time and effort. The addition of an emotion engine makes it possible to provide optimal information according to the user's emotional state.

[0977] The processing flow will be explained below.

[0978] Step 1:

[0979] User enters text. In a text input field in a browser or app, the user enters the text they want summarized and translated. For example, they enter the sentence "The quick brown fox jumps over the lazy dog."

[0980] Step 2:

[0981] The terminal receives the user's input. When the user presses the "Send" button, the terminal receives the entered text and prepares to send this data to the server.

[0982] Step 3:

[0983] The device sends text to the server. The device converts the received text into an appropriate data format (e.g., JSON) and sends it to the server using an HTTP request.

[0984] Step 4:

[0985] The server receives the request. When the server receives the HTTP request sent from the terminal, it extracts the text data.

[0986] Step 5:

[0987] The server calls the emotion engine to analyze the text. The server passes the received text to the emotion engine, which analyzes the emotion (positive, negative, neutral) expressed by the text. For example, if the sentence says "I am very happy with the service," the emotion engine will recognize the positive emotion.

[0988] Step 6:

[0989] The server applies a summarization algorithm. Based on the sentiment analysis results, the server uses a summarization algorithm to summarize the received text. For example, the input "The quick brown fox jumps over the lazy dog." is summarized as "The fox jumps over the dog."

[0990] Step 7:

[0991] The server invokes the translation algorithm. The server passes the summarized text to the translation algorithm or an external translation API to translate it into the specified language. For example, translating the English summary sentence "The fox jumps over the dog." into Japanese.

[0992] Step 8:

[0993] The server receives the translation result. The server receives the Japanese summary result "The fox jumps over the dog." returned from the translation API and formats it as necessary.

[0994] Step 9:

[0995] The server formats the results in JSON format and sends the response to the device. The server then formats the response containing the translated summary results in JSON format and sends it to the device as an HTTP response.

[0996] Step 10:

[0997] The device receives the response and displays the result to the user. The device analyzes the response received from the server and displays the translated summary on the screen. The user can see the translation result, "The fox jumps over the dog," on the browser or application screen.

[0998] This processing step realizes a system that efficiently provides summaries and translation results to users and presents optimal information based on the user's emotions.

[0999] Example 2

[1000] Next, a description will be given of 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."

[1001] In modern digital communication, users are seeking efficient ways to summarize and translate large amounts of text. However, conventional systems generate uniform summaries and translations without considering the user's feelings, making it impossible to provide appropriate information that meets the user's needs. Furthermore, even when communicating between different languages, manual translation and summarization is time-consuming and labor-intensive.

[1002] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for providing a user interface for a user to input text, terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to the server, emotion engine means for recognizing the emotion of the received text, summarization algorithm means for summarizing the received text, translation algorithm means for translating the summarized text, means for transmitting the translated summary to the terminal, and means for displaying the translation result transmitted to the terminal to the user. This enables appropriate summaries and translations that take the user's emotions into consideration to be automatically provided, significantly reducing time and effort.

[1003] A "user" is an entity that uses the system to input text and receive results such as summaries and translations.

[1004] An "interface" is a structure on a system that contains the means by which a user inputs text and the elements used to validate that input.

[1005] "Terminal means" refers to a device or software that has the function of receiving text entered by a user, converting it into a data format, and sending it to a server.

[1006] An "emotion engine means" is an algorithm or software that analyzes received text and recognizes the user's emotions.

[1007] A "summarization algorithm" is a technique or algorithm that processes input text, extracts important information, and generates a short summary.

[1008] A "translation algorithm means" is a technique or algorithm for translating the summarized text into another language.

[1009] "Translation API" means an application programming interface for connecting to an external translation service to translate text.

[1010] "Data format" refers to the structure or format of data used when a terminal means communicates with a server, and includes, for example, JSON and XML.

[1011] An "HTTP request" is a communication protocol used to send text and other data between a device and a server.

[1012] An "HTTP response" is response data that the server sends to the terminal, and specifically includes the translation and summary results of the input text.

[1013] This invention is a system that efficiently summarizes and translates text entered by a user. It is particularly characterized by its ability to provide more appropriate summarization and translation results by taking into account the user's emotional state. This system is comprised of a user interface, a terminal device, a server, an emotion engine, a summarization algorithm, a translation algorithm, and a translation API.

[1014] The user accesses the system using a browser or application and enters the text they want to summarize and translate in the text input field. The entered text is temporarily stored on the device and sent to the server in JSON format when the submit button is pressed.

[1015] The server receives the text sent from the device and analyzes the sentiment of the text using an emotion engine. The emotion engine uses a natural language processing algorithm to identify the most appropriate emotion from three emotion categories: positive, negative, and neutral. The received text is then summarized by a summarization algorithm. The summarization algorithm uses statistical methods and machine learning algorithms to extract key information and generate a short summary.

[1016] Next, the generated summary is translated into another language (e.g., Japanese) using a translation algorithm. A translation API is used to send a request to an external service, such as the Google Translate API. The server receives the response from the translation API and obtains the translation result. After obtaining the translation result, the server sends it to the terminal in JSON format.

[1017] The device then displays the translation results received from the server in the browser or application, allowing the user to view a summary of the text they entered and the translation results.

[1018] For example, consider the following prompt:

[1019] If the English sentence "The quick brown fox jumps over the lazy dog" is input into the system, the emotion engine will analyze the sentence as neutral, and the summarization algorithm will generate the summary "The fox jumps over the dog." This will then be translated into Japanese by the translation algorithm, resulting in the result "The fox jumps over the dog." Finally, the user can view this translation result in their browser or application.

[1020] By incorporating sentiment analysis, this system not only provides appropriate information according to the user's emotional state, but also enables efficient communication across multiple languages, thereby saving users a great deal of time and effort.

[1021] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1022] Step 1:

[1023] User:

[1024] A user accesses the system using a browser or application and enters the text they want summarized and translated into the text input field. An example of the text entered is "The quick brown fox jumps over the lazy dog." The system recognizes the entered text.

[1025] Step 2:

[1026] Device:

[1027] When the user presses the send button, the terminal temporarily saves the entered text, converts it to JSON format, and generates an HTTP POST request. This request contains the entered text data. The terminal then sends this to the server. The input is the user's text, and the output is an HTTP request in JSON format.

[1028] Step 3:

[1029] server:

[1030] The server receives JSON-formatted text sent from the terminal. The received data is parsed as raw text data. The input is the JSON data sent from the terminal, and the output is parseable text data.

[1031] Step 4:

[1032] server:

[1033] The server calls the emotion engine to analyze the emotion of the received text. The emotion engine uses natural language processing algorithms to classify the text as positive, negative, or neutral. For example, if the text is "I am very happy with the service," the emotion engine will recognize it as a positive emotion. The input is the parseable text data, and the output is the emotion category.

[1034] Step 5:

[1035] server:

[1036] After emotion recognition is complete, the server invokes a summarization algorithm to summarize the text. The summarization algorithm uses statistical methods and machine learning algorithms to extract important information and generate a short summary. For example, "The quick brown fox jumps over the lazy dog." can be summarized as "The fox jumps over the dog." The input is the text data after emotion recognition, and the output is the summary.

[1037] Step 6:

[1038] server:

[1039] The generated summary is then translated into another language (e.g., Japanese) by a translation algorithm. The translation algorithm sends a request to an external translation API (e.g., Google Translate API) to obtain the translation result. For example, the summary "The fox jumps over the dog." is translated to "The fox jumps over the dog." The input is the summary, and the output is the translation result.

[1040] Step 7:

[1041] server:

[1042] The server repackages the translation results in JSON format and sends them to the terminal as an HTTP response. The input is the translation results, and the output is the JSON-formatted HTTP response.

[1043] Step 8:

[1044] Device:

[1045] The terminal receives the HTTP response from the server and parses the data again. The parsed translation result is displayed on the user interface. The input is the JSON data received from the server, and the output is the display to the user.

[1046] Step 9:

[1047] User:

[1048] The user checks the translation results displayed on the screen of the terminal, allowing them to visually check the summary of the input text and its translation results.

[1049] (Application example 2)

[1050] Next, a description will be given of Application 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."

[1051] In today's advertising industry, there is a demand for fast and accurate delivery of advertisements that match user emotions. However, conventional ad generation methods have difficulty customizing advertisements that take user emotions into account, resulting in ineffective ad presentation. Furthermore, there is no system that can automatically summarize and translate user-provided text at the same time, which leads to a poor user experience.

[1052] 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.

[1053] In this invention, the server includes emotion recognition means for recognizing the emotion of the received text, summarization algorithm means for summarizing the received text based on the emotion information obtained by the emotion recognition means, and translation algorithm means for translating the summarized text, thereby enabling the automatic generation of customized advertisements based on the user's emotions, as well as the summarization and translation of the advertisements, thereby enabling effective advertisement presentation and an improved user experience.

[1054] A "user interface" is an input means by which a user enters text and interacts with a system.

[1055] "Terminal means" refers to a device or software for receiving text entered at a user interface, converting it into a data format, and transmitting it to a server.

[1056] An "emotion recognizer" is an algorithm or engine for analyzing a user's emotions from received text and identifying positive, negative, or neutral emotions.

[1057] The "summarization algorithm means" is an algorithm for extracting important points of the text and generating a concise summary based on the received text and its sentiment information.

[1058] "Translation algorithm means" is an algorithm for translating the summarized text into a different language, which may use an external translation API.

[1059] A "translation API" is a program interface for translating text into a specified language using a translation function provided as an external service.

[1060] The "means for transmitting to the terminal" is a communication means for transmitting the translated summary from the server to the terminal.

[1061] The "display means" refers to a display device or display software for visually presenting the translation results on the user's terminal.

[1062] This invention is a system that generates advertisements based on user emotions and automatically summarizes and translates them. Specific embodiments for implementing this system will be described in detail below.

[1063] System Overview

[1064] This system is composed of a user, a terminal, and a server, and includes a user interface, emotion recognition, a summarization algorithm, a translation algorithm, and means for displaying results.

[1065] Hardware and software used

[1066] Hardware: Smartphones, servers

[1067] Software: Python, textblob library (emotion recognition), googletrans library (translation)

[1068] Data processing and calculation methods

[1069] 1. Providing a user interface

[1070] The device provides a user interface that allows the user to input text, which can be achieved through a smartphone application or a web browser.

[1071] 2. Entering and Receiving Text

[1072] The user inputs text, the device receives the input text, and sends it to the server, using JSON as the data format.

[1073] 3. Emotion recognition

[1074] The server analyzes the received text using an emotion recognition means (textblob library) to identify positive, negative, or neutral emotions.

[1075] 4. Summary Generation

[1076] Based on the sentiment information, the server uses a summarization algorithm to extract key points of the text and generate a summary.

[1077] 5. Translation of Abstracts

[1078] The summarized text is translated into the specified language by means of a translation algorithm (googletrans library), possibly using an external translation API.

[1079] 6. Results transmission and display

[1080] The translated summary is sent from the server to the terminal and displayed to the user through a user interface.

[1081] Specific examples

[1082] 1. User Input

[1083] The user enters the text "I love the new features in this product!"

[1084] 2. Emotion recognition

[1085] The server's emotion recognition means analyzes this text and determines positive emotions.

[1086] 3. Summary Generation

[1087] A summarization algorithm means summarizes this text and produces "Love new features product!"

[1088] 4. Translation Results

[1089] A translation algorithm means translates this summary into Japanese and produces "I love the new features!"

[1090] Prompt Sentence Examples

[1091] Example prompt for generative AI model:

[1092] Use the translation API to translate the following text into Japanese: "I love the new features!"

[1093] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1094] Step 1:

[1095] The user enters text

[1096] A user inputs text that will be used to generate an advertisement using a user interface provided by a smartphone application or a web browser. The input text is then sent to the device via the user interface (e.g., "I love the new features in this product!").

[1097] Step 2:

[1098] The device sends the text to the server

[1099] The device receives the text entered by the user, converts it into a data format (JSON format), and then sends it to the server using an HTTP request. Input: User text (e.g., "I love the new features in this product!") Output: JSON-formatted text data

[1100] Step 3:

[1101] The server recognizes emotions

[1102] The server analyzes the received text data using emotion recognition (textblob library) to identify positive, negative, or neutral emotions. Input: Text data in JSON format. Output: Emotion score and emotion category (e.g., positive).

[1103] Step 4:

[1104] The server summarizes the text

[1105] The server uses a summarization algorithm to extract key points from the received text based on the emotion information and generate a short summary. Input: Emotion-recognized text (e.g., "I love the new features in this product!") Output: Summarized text (e.g., "Love new features product!")

[1106] Step 5:

[1107] The server translates the summary

[1108] The server translates the summarized text into the specified language using a translation algorithm (googletrans library), possibly using an external translation API. Input: Summarized text (e.g. "Love new features product!") Output: Translated text (e.g. "Love the new features product!")

[1109] Step 6:

[1110] The server sends the translated summary to the device

[1111] The server converts the translated summary into JSON format and sends it to the device using an HTTP response. Input: Translated text (e.g., "I love the new feature!") Output: Translation data in JSON format

[1112] Step 7:

[1113] The device displays the translation results to the user

[1114] The device displays the translation data received from the server on the user interface and notifies the user of the results. Input: Translation data in JSON format Output: Translation results displayed to the user (e.g., "I love the new features!")

[1115] 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.

[1116] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[1117] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1118] [Fourth embodiment]

[1119] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1120] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1121] 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).

[1122] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. 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 control target 443 are also connected to the bus 52.

[1123] 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.

[1124] 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).

[1125] 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.

[1126] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1127] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, 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.

[1128] 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.

[1129] 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.

[1130] In the robot 414, the processor 46 performs the reception output process. 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.

[1131] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1132] As an embodiment of the present invention, a system for automatically providing summaries and translations is constructed. The program processing of this system and a specific example of its operation will be described below.

[1133] The system consists of a user interface, a terminal, a server, a summarization algorithm, a translation algorithm, and a translation API. Users access the system through a browser or an application and input text to be summarized and translated.

[1134] System processing flow

[1135] 1. User text input

[1136] The user inputs the text they want to summarize and translate using an interface (e.g., a text input field) provided by the system. For example, the user inputs the English sentence, "The quick brown fox jumps over the lazy dog."

[1137] 2. Sending text from the device to the server

[1138] When the user completes the input and presses the send button, the terminal sends this text to the server in JSON format, specifically via an HTTP request.

[1139] 3. Server-generated text summarization

[1140] The server processes the text data received from the device using a summarization algorithm. The main points of the text are extracted and a short summary is generated. For example, the received text "The quick brown fox jumps over the lazy dog." is processed by the summarization algorithm and summarized as "The fox jumps over the dog."

[1141] 4. Japanese translation of the summary

[1142] The summarized text "The fox jumps over the dog." is then translated into Japanese by means of a translation algorithm. Using a translation API, a translation request is sent to an external service. The translation result is "The fox jumps over the dog."

[1143] 5. Send the translation results to your device

[1144] The translated summary is sent back to the device from the server, where it is again formatted in JSON and sent as an HTTP response.

[1145] 6. Displaying results to the user

[1146] The terminal receives the translation result from the server and displays it to the user. The user can view the translated summary through a browser or application interface.

[1147] In this way, the system of the present invention efficiently executes a series of processes from user text input, to summary generation, translation into Japanese, and final display, enabling users to quickly grasp vast amounts of information and significantly reduce the time and effort required to obtain the information they need.

[1148] Specific examples

[1149] 1. User Input

[1150] User types: "The quick brown fox jumps over the lazy dog."

[1151] 2. Summary of results

[1152] Summary by server's summarization algorithm: "The fox jumps over the dog."

[1153] 3. Translation results

[1154] Japanese translation by translation algorithm: "The fox jumps over the dog."

[1155] This allows users to easily obtain summaries and their translation results.By optimizing and automating this process, the system significantly reduces time and effort.

[1156] The processing flow will be explained below.

[1157] Step 1:

[1158] User enters text: The user enters the text they want summarized and translated into a text input field in their browser or app.

[1159] Step 2:

[1160] The terminal receives the user's input. When the user presses the Send button, the terminal receives the entered text.

[1161] Step 3:

[1162] The device sends text to the server. The device converts the received text into an appropriate data format (e.g., JSON) and sends it to the server using an HTTP request.

[1163] Step 4:

[1164] The server receives the request. The server receives the HTTP request sent from the terminal and extracts the text data.

[1165] Step 5:

[1166] The server applies the summarization algorithm: The server invokes the summarization algorithm, passing the received text as input. The algorithm extracts important sentences and keywords and generates a shortened summary.

[1167] Step 6:

[1168] The server stores the summary results. The server temporarily stores the generated summary results in memory.

[1169] Step 7:

[1170] The server invokes the translation algorithm, and passes the stored summary text to another translation algorithm or an external translation API (e.g., translation API) to translate it into Japanese.

[1171] Step 8:

[1172] The server receives the translation results, receives the Japanese summary results sent from the translation API, and formats them as necessary.

[1173] Step 9:

[1174] The server formats the results in JSON. The server formats a response containing the translated summary results in JSON.

[1175] Step 10:

[1176] The server sends the response to the terminal. The formatted data is sent to the terminal as an HTTP response.

[1177] Step 11:

[1178] The terminal receives the response. The terminal receives the response from the server and analyzes the data.

[1179] Step 12:

[1180] The terminal displays the results to the user. The terminal displays a summary of the analyzed Japanese text on the screen and informs the user of the results.

[1181] Example 1

[1182] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1183] Conventional information processing systems have had difficulty efficiently summarizing large amounts of text data and translating it into different languages. In particular, the quality of summarization and translation is low, making it difficult to provide users with the fast and accurate information they require.

[1184] 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.

[1185] In this invention, the server includes a means for providing a user interface, a terminal means for receiving text data, converting it into a data format, and transmitting the data to the server, a summarization algorithm means, a translation algorithm means, a means for transmitting a translated summary to the terminal, and a means for displaying the translated summary to the user. This makes it possible to efficiently summarize large amounts of text data and quickly provide highly accurate translations.

[1186] "User interface" means an interface through which a user accesses a system and inputs or receives information.

[1187] "Terminal means" refers to a device or software for transmitting data entered by a user to a server.

[1188] The "summarization algorithm means" is an algorithm that processes input text data, extracts its main information, and generates a short summary.

[1189] A "translation algorithm means" is an algorithm for translating the summarized text into a different language.

[1190] "Translation API" means an application programming interface for accessing an external translation service, sending requests for translation of text, and receiving the results.

[1191] A "generative AI model" is an algorithm that processes data (summarizes and translates) based on machine learning and artificial intelligence.

[1192] "Data format" refers to the format for structuring and sending data, and specifically includes JSON and XML.

[1193] A "server" is a computer system that processes text data received from a user, summarizes and translates it, and returns the results.

[1194] MODE FOR CARRYING OUT THE INVENTION

[1195] The present invention is a system for automatically providing summarization and translation of text by a user, which is composed of a user interface, a terminal means, a server, a summarization algorithm means, a translation algorithm means, and a translation API.

[1196] System configuration

[1197] 1. User Interface

[1198] The user interface is the browser or application interface through which the user enters text, allowing the user to easily enter the text they wish to have summarized and translated.

[1199] 2. Terminal means

[1200] The terminal means is a device or software for transmitting text data entered by a user to a server. HTTP is used as the communication protocol, and JSON is used as the data format.

[1201] 3. Server

[1202] The server is a central processing unit that processes the text data received from the terminals, and uses a summarization algorithm means and a translation algorithm means to summarize and translate the text.

[1203] 4. Summarization Algorithm

[1204] The summarization algorithm is an algorithm that uses a generative AI model to summarize text data. It automatically extracts the main points of the received text and generates a short summary.

[1205] 5. Translation Algorithm Means

[1206] The translation algorithm means is an algorithm for translating the summarized text into a different language, in particular using an external translation API (e.g., Google Translate API).

[1207] 6. Translation API

[1208] A translation API is an application programming interface for accessing external services to perform translations.

[1209] 7. Displaying results to the user

[1210] The translated summary is sent back to the terminal and displayed to the user through a user interface.

[1211] Specific examples

[1212] 1. User Input

[1213] User: Enters the sentence "The quick brown fox jumps over the lazy dog." into the interface.

[1214] 2. Summary of results

[1215] Server: Generates a summary sentence "The fox jumps over the dog." using a summarization algorithm.

[1216] 3. Translation results

[1217] Server: Using the translation API, translate this summary into Japanese as "The fox jumps over the dog."

[1218] Prompt Sentence Examples

[1219] An example of a prompt when using a generative AI model is as follows:

[1220] English summary

[1221] "Please summarize the following text: The quick brown fox jumps over the lazy dog."

[1222] Summary English translation

[1223] "Please translate the following text to Japanese: The fox jumps over the dog."

[1224] In this way, the system of the present invention efficiently executes a series of processes from user text input, to summary generation, translation into Japanese, and final display, allowing users to quickly grasp vast amounts of information and significantly reduce the time and effort required to obtain the information they need.

[1225] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1226] Step 1:

[1227] The user inputs the text they want summarized and translated using the interface provided by the system (a text input field in a browser or application). The input text is an English sentence such as "The quick brown fox jumps over the lazy dog."

[1228] Input: The text the user types into the input field

[1229] Output: Text data entered by the user

[1230] Specific behavior:

[1231] A user opens a browser or application interface, enters text into an input field, and then presses a submit button.

[1232] Step 2:

[1233] The terminal converts the text entered in the user interface into a data format (JSON) and sends it to the server using an HTTP request.

[1234] Input: Text data entered by the user

[1235] Output: JSON format text data

[1236] Specific behavior:

[1237] The terminal converts the text received from the user interface into the following JSON format:

[1238] json

[1239] {

[1240] "text": "The quick brown fox jumps over the lazy dog."

[1241] }

[1242] This JSON data is sent to the server as an HTTP request.

[1243] Step 3:

[1244] The server analyzes the text data received from the device and passes it to a summarization algorithm means to generate a summary, which uses a generative AI model.

[1245] Input: JSON format text data

[1246] Output: Summarized text

[1247] Specific behavior:

[1248] The server extracts the value of the "text" field from the received JSON data and summarizes the sentence using a generative AI model. For example, it summarizes "The quick brown fox jumps over the lazy dog." to "The fox jumps over the dog."

[1249] Step 4:

[1250] The server passes the summarized text "The fox jumps over the dog." to a translation algorithm means, which translates it into Japanese using a translation API.

[1251] Input: Summarized text

[1252] Output: The translated text

[1253] Specific behavior:

[1254] The server sends a request to the translation API, asking it to translate the summary sentence, "The fox jumps over the dog." The translation API receives the request and returns the translation result, "The fox jumps over the dog."

[1255] Step 5:

[1256] The server formats the translated text in JSON format and sends it to the terminal as an HTTP response.

[1257] Input: Translated text

[1258] Output: Translation result data in JSON format

[1259] Specific behavior:

[1260] The server formats the translated text "The fox jumps over the dog." in the following JSON format:

[1261] json

[1262] {

[1263] "summary": "The fox jumps over the dog.",

[1264] "translation": "The fox jumps over the dog."

[1265] }

[1266] This data is sent to the terminal as an HTTP response.

[1267] Step 6:

[1268] The terminal displays the translation results received from the server on a user interface.

[1269] Input: Translation result data in JSON format

[1270] Output: The translation result displayed in the user interface

[1271] Specific behavior:

[1272] The device extracts the value of the "translation" field from the received JSON data and displays "The fox jumps over the dog" on the user interface, allowing the user to view the translated summary.

[1273] (Application example 1)

[1274] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1275] At logistics centers, staff are required to efficiently understand lengthy logistics information written in multiple languages. However, manual summarization and translation takes time and effort, reducing work efficiency. To solve this issue and improve work efficiency, it is necessary to quickly and accurately summarize and translate information and provide it in a format that is easy for on-site staff to understand.

[1276] 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.

[1277] In this invention, the server includes means for providing a user interface for a user to input text, terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to the server, summarization algorithm means for summarizing the received text, translation algorithm means for translating the summarized text, means for transmitting the translated summary to the terminal, means for displaying the translation result transmitted to the terminal to the user, and means for displaying the summary and translated text to warehouse staff for logistics information. This enables logistics center staff to efficiently summarize and translate lengthy logistics information written in multiple languages ​​and quickly understand it.

[1278] A "user interface" is a screen or input device that allows a user to perform operations or input data to a system.

[1279] The "terminal means" is a device that has the function of receiving data input to a user interface, converting it into an appropriate data format, and transmitting it to a server.

[1280] A "summarization algorithm" is a program or process that extracts the main points from input text and generates a shortened summary.

[1281] A "translation algorithmic means" is a program or process for converting text written in one language into another language.

[1282] A "translation API" is an application program interface that provides translation functionality by accessing external translation services.

[1283] "Logistics information" refers to information managed by a logistics center, such as arrival information and shipping information.

[1284] "Warehouse staff" refers to workers and managers engaged in operations at logistics centers.

[1285] The "system" refers to a collection of a user interface, a terminal means, a summarization algorithm means, a translation algorithm means, and a server and a network for linking these together to operate.

[1286] "Multilingual" means two or more different languages.

[1287] A "long text" is a text that contains a large amount of information and is made up of multiple sentences or paragraphs.

[1288] A "server" is a computer system that provides information and processing power over a network.

[1289] A "data format" is a set of rules or formats for structuring and storing data.

[1290] The present invention aims to realize a system that efficiently summarizes long multilingual logistics information at a logistics center and provides the translated information to warehouse staff. This system is configured as follows.

[1291] First, a user uses a device such as a smartphone or tablet to input long multilingual text from a user interface, such as detailed information about incoming shipments or shipping status.

[1292] The terminal receives data entered by the user, converts it into a data format, and sends it to the server. JSON is a suitable data format for this purpose. An HTTP request is used to send data from the terminal to the server.

[1293] The server processes the received text data with a summarization algorithm means. The summarization algorithm means uses a specific statistical or machine learning algorithm to extract the main points of the text and generate a short summary. For example, the text "The shipment of 100 boxes of electronics has been delayed due to unexpected customs clearance issues, and will arrive by the end of next week." is summarized as the main information "The shipment of electronics has been delayed."

[1294] Next, the summarized text is translated into a desired language by a translation algorithm means. The translation algorithm means uses an external translation API to translate the summarized text into, for example, Japanese. For example, the translation API used is "https: / / api.translation.example.com / v1 / translate". The translation result is "Shipments of electronic devices are delayed."

[1295] The server then sends the translated summary back to the terminal in JSON format. The terminal then displays the translation results received from the server to the user through a user interface. Warehouse staff can quickly understand the translated summary and efficiently carry out their required tasks.

[1296] A concrete example would be the following scenario: Warehouse staff can input lengthy incoming goods information on their own devices, and receive a summary and translation of the information in a short time, enabling them to take appropriate action promptly.

[1297] Examples of prompts to be input to a generative AI model include:

[1298] Language used: Python

[1299] Objective: Write a program to summarize and translate lengthy logistics information for warehouse staff.

[1300] Assume that the summarized text is to be translated into Japanese.

[1301] In this way, the system of the present invention can efficiently summarize lengthy logistics information in multiple languages ​​and provide translated information, thereby significantly improving the operational efficiency of logistics centers.

[1302] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1303] Step 1:

[1304] Users use a smartphone or tablet device to input long multilingual text into the user interface. This input text is treated as the system's initial data. For example, specific text such as "The shipment of 100 boxes of electronics has been delayed due to unexpected customs clearance issues, and will arrive by the end of next week." is input.

[1305] Step 2:

[1306] The terminal receives text data entered by the user and converts it into a data format, for example, JSON format. In this process, the text data is structured as a JSON object, making it a format that can be sent to the next processing step. This converted data is then sent to the server using an HTTP request.

[1307] Step 3:

[1308] The server processes the text data received from the device using a summarization algorithm. Specifically, it uses machine learning or statistical algorithms to extract key points and generate a short summary. It analyzes the input long text and outputs a summary sentence, such as "The shipment of electronics has been delayed."

[1309] Step 4:

[1310] The server then translates the summary generated by the summarization algorithm into the desired language using a translation algorithm. This translation uses an external translation API, and the summary is sent to the API to obtain the translation result. The translation API translates the input summary into the corresponding language, and outputs a translation result such as "Shipments of electronic devices are delayed."

[1311] Step 5:

[1312] The server restructures the translated summary and formats it again in JSON format. This JSON data is sent to the terminal as an HTTP response. Here, the translation result text is properly formatted and provided as a response to the terminal.

[1313] Step 6:

[1314] The terminal displays the translation results received from the server to the user through a user interface. Warehouse staff visually check the displayed translation results and perform the necessary tasks quickly and efficiently. In this step, the process of displaying the specific data received on the screen is carried out.

[1315] 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.

[1316] As an embodiment of the present invention, a system is constructed that automatically provides summarization, translation, and user emotion recognition. Below, the program processing of this system and a specific example of its operation will be described.

[1317] The system consists of a user interface, a terminal, a server, a summarization algorithm, a translation algorithm, a translation API, and an emotion engine. Users access the system through a browser or an application and input text to be summarized and translated. At the same time, the emotion engine recognizes the user's emotions and provides the optimal summary and translation based on those emotions.

[1318] System processing flow

[1319] 1. User text input

[1320] The user inputs the text they want to summarize and translate using an interface (e.g., a text input field) provided by the system. For example, the user inputs the English sentence, "The quick brown fox jumps over the lazy dog."

[1321] 2. Sending text from the device to the server

[1322] When the user completes the input and presses the send button, the terminal sends this text to the server in JSON format, specifically via an HTTP request.

[1323] 3. Emotion Recognition by the Server

[1324] The server analyzes the received text data with an emotion engine to identify the user's emotion (positive, negative, neutral). For example, in the case of the text "I am very happy with the service," a positive emotion is recognized.

[1325] 4. Server-generated text summarization

[1326] The server processes the text using a summarization algorithm to extract key points and generate a short summary. For example, the received text "The quick brown fox jumps over the lazy dog." is processed by the summarization algorithm and summarized as "The fox jumps over the dog."

[1327] 5. Japanese translation of the summary

[1328] The summarized text "The fox jumps over the dog." is translated into Japanese by means of a translation algorithm. Using a translation API, a translation request is sent to an external service. The translation result is "The fox jumps over the dog."

[1329] 6. Sending translation results to your device

[1330] The translated summary is sent back to the device from the server, where it is again formatted in JSON and sent as an HTTP response.

[1331] 7. Displaying results to the user

[1332] The terminal receives the translation result from the server and displays it to the user. The user can view the translated summary through a browser or application interface.

[1333] Specific examples

[1334] 1. User Input

[1335] User types: "The quick brown fox jumps over the lazy dog."

[1336] 2. Emotion recognition

[1337] The server's emotion engine analyzes the text and determines the user's emotion as "neutral."

[1338] 3. Summary of results

[1339] Summary by server's summarization algorithm: "The fox jumps over the dog."

[1340] 4. Translation Results

[1341] Japanese translation by translation algorithm: "The fox jumps over the dog."

[1342] This allows users to easily obtain summaries and translation results that correspond to their emotions. By optimizing and automating this process, the system significantly reduces time and effort. The addition of an emotion engine makes it possible to provide optimal information according to the user's emotional state.

[1343] The processing flow will be explained below.

[1344] Step 1:

[1345] User enters text. In a text input field in a browser or app, the user enters the text they want summarized and translated. For example, they enter the sentence "The quick brown fox jumps over the lazy dog."

[1346] Step 2:

[1347] The terminal receives the user's input. When the user presses the "Send" button, the terminal receives the entered text and prepares to send this data to the server.

[1348] Step 3:

[1349] The device sends text to the server. The device converts the received text into an appropriate data format (e.g., JSON) and sends it to the server using an HTTP request.

[1350] Step 4:

[1351] The server receives the request. When the server receives the HTTP request sent from the terminal, it extracts the text data.

[1352] Step 5:

[1353] The server calls the emotion engine to analyze the text. The server passes the received text to the emotion engine, which analyzes the emotion (positive, negative, neutral) expressed by the text. For example, if the sentence says "I am very happy with the service," the emotion engine will recognize the positive emotion.

[1354] Step 6:

[1355] The server applies a summarization algorithm. Based on the sentiment analysis results, the server uses a summarization algorithm to summarize the received text. For example, the input "The quick brown fox jumps over the lazy dog." is summarized as "The fox jumps over the dog."

[1356] Step 7:

[1357] The server invokes the translation algorithm. The server passes the summarized text to the translation algorithm or an external translation API to translate it into the specified language. For example, translating the English summary sentence "The fox jumps over the dog." into Japanese.

[1358] Step 8:

[1359] The server receives the translation result. The server receives the Japanese summary result "The fox jumps over the dog." returned from the translation API and formats it as necessary.

[1360] Step 9:

[1361] The server formats the results in JSON format and sends the response to the device. The server then formats the response containing the translated summary results in JSON format and sends it to the device as an HTTP response.

[1362] Step 10:

[1363] The device receives the response and displays the result to the user. The device analyzes the response received from the server and displays the translated summary on the screen. The user can see the translation result, "The fox jumps over the dog," on the browser or application screen.

[1364] This processing step realizes a system that efficiently provides summaries and translation results to users and presents optimal information based on the user's emotions.

[1365] Example 2

[1366] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1367] In modern digital communication, users are seeking efficient ways to summarize and translate large amounts of text. However, conventional systems generate uniform summaries and translations without considering the user's feelings, making it impossible to provide appropriate information that meets the user's needs. Furthermore, even when communicating between different languages, manual translation and summarization is time-consuming and labor-intensive.

[1368] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for providing a user interface for a user to input text, terminal means for receiving the text input to the user interface, converting it into a data format, and transmitting the data to the server, emotion engine means for recognizing the emotion of the received text, summarization algorithm means for summarizing the received text, translation algorithm means for translating the summarized text, means for transmitting the translated summary to the terminal, and means for displaying the translation result transmitted to the terminal to the user. This enables appropriate summaries and translations that take the user's emotions into consideration to be automatically provided, significantly reducing time and effort.

[1369] A "user" is an entity that uses the system to input text and receive results such as summaries and translations.

[1370] An "interface" is a structure on a system that contains the means by which a user inputs text and the elements used to validate that input.

[1371] "Terminal means" refers to a device or software that has the function of receiving text entered by a user, converting it into a data format, and sending it to a server.

[1372] An "emotion engine means" is an algorithm or software that analyzes received text and recognizes the user's emotions.

[1373] A "summarization algorithm" is a technique or algorithm that processes input text, extracts important information, and generates a short summary.

[1374] A "translation algorithm means" is a technique or algorithm for translating the summarized text into another language.

[1375] "Translation API" means an application programming interface for connecting to an external translation service to translate text.

[1376] "Data format" refers to the structure or format of data used when a terminal means communicates with a server, and includes, for example, JSON and XML.

[1377] An "HTTP request" is a communication protocol used to send text and other data between a device and a server.

[1378] An "HTTP response" is response data that the server sends to the terminal, and specifically includes the translation and summary results of the input text.

[1379] This invention is a system that efficiently summarizes and translates text entered by a user. It is particularly characterized by its ability to provide more appropriate summarization and translation results by taking into account the user's emotional state. This system is comprised of a user interface, a terminal device, a server, an emotion engine, a summarization algorithm, a translation algorithm, and a translation API.

[1380] The user accesses the system using a browser or application and enters the text they want to summarize and translate in the text input field. The entered text is temporarily stored on the device and sent to the server in JSON format when the submit button is pressed.

[1381] The server receives the text sent from the device and analyzes the sentiment of the text using an emotion engine. The emotion engine uses a natural language processing algorithm to identify the most appropriate emotion from three emotion categories: positive, negative, and neutral. The received text is then summarized by a summarization algorithm. The summarization algorithm uses statistical methods and machine learning algorithms to extract key information and generate a short summary.

[1382] Next, the generated summary is translated into another language (e.g., Japanese) using a translation algorithm. A translation API is used to send a request to an external service, such as the Google Translate API. The server receives the response from the translation API and obtains the translation result. After obtaining the translation result, the server sends it to the terminal in JSON format.

[1383] The device then displays the translation results received from the server in the browser or application, allowing the user to view a summary of the text they entered and the translation results.

[1384] For example, consider the following prompt:

[1385] If the English sentence "The quick brown fox jumps over the lazy dog" is input into the system, the emotion engine will analyze the sentence as neutral, and the summarization algorithm will generate the summary "The fox jumps over the dog." This will then be translated into Japanese by the translation algorithm, resulting in the result "The fox jumps over the dog." Finally, the user can view this translation result in their browser or application.

[1386] By incorporating sentiment analysis, this system not only provides appropriate information according to the user's emotional state, but also enables efficient communication across multiple languages, thereby saving users a great deal of time and effort.

[1387] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1388] Step 1:

[1389] User:

[1390] A user accesses the system using a browser or application and enters the text they want summarized and translated into the text input field. An example of the text entered is "The quick brown fox jumps over the lazy dog." The system recognizes the entered text.

[1391] Step 2:

[1392] Device:

[1393] When the user presses the send button, the terminal temporarily saves the entered text, converts it to JSON format, and generates an HTTP POST request. This request contains the entered text data. The terminal then sends this to the server. The input is the user's text, and the output is an HTTP request in JSON format.

[1394] Step 3:

[1395] server:

[1396] The server receives JSON-formatted text sent from the terminal. The received data is parsed as raw text data. The input is the JSON data sent from the terminal, and the output is parseable text data.

[1397] Step 4:

[1398] server:

[1399] The server calls the emotion engine to analyze the emotion of the received text. The emotion engine uses natural language processing algorithms to classify the text as positive, negative, or neutral. For example, if the text is "I am very happy with the service," the emotion engine will recognize it as a positive emotion. The input is the parseable text data, and the output is the emotion category.

[1400] Step 5:

[1401] server:

[1402] After emotion recognition is complete, the server invokes a summarization algorithm to summarize the text. The summarization algorithm uses statistical methods and machine learning algorithms to extract important information and generate a short summary. For example, "The quick brown fox jumps over the lazy dog." can be summarized as "The fox jumps over the dog." The input is the text data after emotion recognition, and the output is the summary.

[1403] Step 6:

[1404] server:

[1405] The generated summary is then translated into another language (e.g., Japanese) by a translation algorithm. The translation algorithm sends a request to an external translation API (e.g., Google Translate API) to obtain the translation result. For example, the summary "The fox jumps over the dog." is translated to "The fox jumps over the dog." The input is the summary, and the output is the translation result.

[1406] Step 7:

[1407] server:

[1408] The server repackages the translation results in JSON format and sends them to the terminal as an HTTP response. The input is the translation results, and the output is the JSON-formatted HTTP response.

[1409] Step 8:

[1410] Device:

[1411] The terminal receives the HTTP response from the server and parses the data again. The parsed translation result is displayed on the user interface. The input is the JSON data received from the server, and the output is the display to the user.

[1412] Step 9:

[1413] User:

[1414] The user checks the translation results displayed on the screen of the terminal, allowing them to visually check the summary of the input text and its translation results.

[1415] (Application example 2)

[1416] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1417] In today's advertising industry, there is a demand for fast and accurate delivery of advertisements that match user emotions. However, conventional ad generation methods have difficulty customizing advertisements that take user emotions into account, resulting in ineffective ad presentation. Furthermore, there is no system that can automatically summarize and translate user-provided text at the same time, which leads to a poor user experience.

[1418] 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.

[1419] In this invention, the server includes emotion recognition means for recognizing the emotion of the received text, summarization algorithm means for summarizing the received text based on the emotion information obtained by the emotion recognition means, and translation algorithm means for translating the summarized text, thereby enabling the automatic generation of customized advertisements based on the user's emotions, as well as the summarization and translation of the advertisements, thereby enabling effective advertisement presentation and an improved user experience.

[1420] A "user interface" is an input means by which a user enters text and interacts with a system.

[1421] "Terminal means" refers to a device or software for receiving text entered at a user interface, converting it into a data format, and transmitting it to a server.

[1422] An "emotion recognizer" is an algorithm or engine for analyzing a user's emotions from received text and identifying positive, negative, or neutral emotions.

[1423] The "summarization algorithm means" is an algorithm for extracting important points of the text and generating a concise summary based on the received text and its sentiment information.

[1424] "Translation algorithm means" is an algorithm for translating the summarized text into a different language, which may use an external translation API.

[1425] A "translation API" is a program interface for translating text into a specified language using a translation function provided as an external service.

[1426] The "means for transmitting to the terminal" is a communication means for transmitting the translated summary from the server to the terminal.

[1427] The "display means" refers to a display device or display software for visually presenting the translation results on the user's terminal.

[1428] This invention is a system that generates advertisements based on user emotions and automatically summarizes and translates them. Specific embodiments for implementing this system will be described in detail below.

[1429] System Overview

[1430] This system is composed of a user, a terminal, and a server, and includes a user interface, emotion recognition, a summarization algorithm, a translation algorithm, and means for displaying results.

[1431] Hardware and software used

[1432] Hardware: Smartphones, servers

[1433] Software: Python, textblob library (emotion recognition), googletrans library (translation)

[1434] Data processing and calculation methods

[1435] 1. Providing a user interface

[1436] The device provides a user interface that allows the user to input text, which can be achieved through a smartphone application or a web browser.

[1437] 2. Entering and Receiving Text

[1438] The user inputs text, the device receives the input text, and sends it to the server, using JSON as the data format.

[1439] 3. Emotion recognition

[1440] The server analyzes the received text using an emotion recognition means (textblob library) to identify positive, negative, or neutral emotions.

[1441] 4. Summary Generation

[1442] Based on the sentiment information, the server uses a summarization algorithm to extract key points of the text and generate a summary.

[1443] 5. Translation of Abstracts

[1444] The summarized text is translated into the specified language by means of a translation algorithm (googletrans library), possibly using an external translation API.

[1445] 6. Results transmission and display

[1446] The translated summary is sent from the server to the terminal and displayed to the user through a user interface.

[1447] Specific examples

[1448] 1. User Input

[1449] The user enters the text "I love the new features in this product!"

[1450] 2. Emotion recognition

[1451] The server's emotion recognition means analyzes this text and determines positive emotions.

[1452] 3. Summary Generation

[1453] A summarization algorithm means summarizes this text and produces "Love new features product!"

[1454] 4. Translation Results

[1455] A translation algorithm means translates this summary into Japanese and produces "I love the new features!"

[1456] Prompt Sentence Examples

[1457] Example prompt for generative AI model:

[1458] Use the translation API to translate the following text into Japanese: "I love the new features!"

[1459] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1460] Step 1:

[1461] The user enters text

[1462] A user inputs text that will be used to generate an advertisement using a user interface provided by a smartphone application or a web browser. The input text is then sent to the device via the user interface (e.g., "I love the new features in this product!").

[1463] Step 2:

[1464] The device sends the text to the server

[1465] The device receives the text entered by the user, converts it into a data format (JSON format), and then sends it to the server using an HTTP request. Input: User text (e.g., "I love the new features in this product!") Output: JSON-formatted text data

[1466] Step 3:

[1467] The server recognizes emotions

[1468] The server analyzes the received text data using emotion recognition (textblob library) to identify positive, negative, or neutral emotions. Input: Text data in JSON format. Output: Emotion score and emotion category (e.g., positive).

[1469] Step 4:

[1470] The server summarizes the text

[1471] The server uses a summarization algorithm to extract key points from the received text based on the emotion information and generate a short summary. Input: Emotion-recognized text (e.g., "I love the new features in this product!") Output: Summarized text (e.g., "Love new features product!")

[1472] Step 5:

[1473] The server translates the summary

[1474] The server translates the summarized text into the specified language using a translation algorithm (googletrans library), possibly using an external translation API. Input: Summarized text (e.g. "Love new features product!") Output: Translated text (e.g. "Love the new features product!")

[1475] Step 6:

[1476] The server sends the translated summary to the device

[1477] The server converts the translated summary into JSON format and sends it to the device using an HTTP response. Input: Translated text (e.g., "I love the new feature!") Output: Translation data in JSON format

[1478] Step 7:

[1479] The device displays the translation results to the user

[1480] The device displays the translation data received from the server on the user interface and notifies the user of the results. Input: Translation data in JSON format Output: Translation results displayed to the user (e.g., "I love the new features!")

[1481] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1482] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[1483] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1484] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1485] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1486] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1487] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1488] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1489] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1490] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1491] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1492] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1493] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1494] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1495] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1496] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1497] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1498] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1499] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1500] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1501] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1502] The following is further disclosed regarding the above embodiment.

[1503] (Claim 1)

[1504] means for providing a user interface for a user to input text;

[1505] a terminal means for receiving text input to a user interface, converting the text into a data format, and transmitting the data to a server;

[1506] a summarization algorithm means for summarizing the received text;

[1507] a translation algorithm means for translating the summarized text;

[1508] means for transmitting the translated summary to a terminal;

[1509] means for displaying the translation results sent to the terminal to the user;

[1510] A system including:

[1511] (Claim 2)

[1512] 10. The system of claim 1, wherein the translation algorithm means uses an external translation API.

[1513] (Claim 3)

[1514] 10. The system of claim 1, wherein the summarization algorithm means uses a particular statistical or machine learning algorithm to generate the summaries.

[1515] "Example 1"

[1516] (Claim 1)

[1517] means for providing a user interface for a user to input text;

[1518] a terminal means for receiving text input to a user interface, converting the text into a data format, and transmitting the data to a server;

[1519] a summarization algorithm means for summarizing the received text;

[1520] a translation algorithm means for translating the summarized text;

[1521] means for transmitting the translated summary to a terminal;

[1522] means for displaying the translation results sent to the terminal to the user;

[1523] A system including:

[1524] (Claim 2)

[1525] 10. The system of claim 1, wherein the translation algorithm means uses an external translation API.

[1526] (Claim 3)

[1527] 10. The system of claim 1, wherein the translation algorithm means and the summarization algorithm means use a generative AI model.

[1528] "Application Example 1"

[1529] (Claim 1)

[1530] means for providing a user interface for a user to input text;

[1531] a terminal means for receiving text input to a user interface, converting the text into a data format, and transmitting the data to a server;

[1532] a summarization algorithm means for summarizing the received text;

[1533] a translation algorithm means for translating the summarized text;

[1534] means for transmitting the translated summary to a terminal;

[1535] means for displaying the translation results sent to the terminal to the user;

[1536] a means for displaying summarized and translated text for logistics information to warehouse staff;

[1537] A system including:

[1538] (Claim 2)

[1539] 10. The system of claim 1, wherein the translation algorithm means uses an external translation API.

[1540] (Claim 3)

[1541] 10. The system of claim 1, wherein the summarization algorithm means uses a particular statistical or machine learning algorithm to generate the summaries.

[1542] "Example 2: Combining Emotion Engines"

[1543] (Claim 1)

[1544] means for providing a user interface for a user to input text;

[1545] a terminal means for receiving text input to a user interface, converting the text into a data format, and transmitting the data to a server;

[1546] emotion engine means for recognizing the emotion of received text;

[1547] a summarization algorithm means for summarizing the received text;

[1548] a translation algorithm means for translating the summarized text;

[1549] means for transmitting the translated summary to a terminal;

[1550] means for displaying the translation results sent to the terminal to the user;

[1551] A system including:

[1552] (Claim 2)

[1553] 10. The system of claim 1, wherein the translation algorithm means uses an external translation API.

[1554] (Claim 3)

[1555] 10. The system of claim 1, wherein the summarization algorithm means uses a particular statistical or machine learning algorithm to generate the summaries.

[1556] "Application example 2 when combining emotion engines"

[1557] (Claim 1)

[1558] means for providing a user interface for a user to input text;

[1559] a terminal means for receiving text input to a user interface, converting the text into a data format, and transmitting the data to a server;

[1560] emotion recognition means for recognizing the emotion of the received text;

[1561] a summarization algorithm means for summarizing the received text based on the emotion information obtained by the emotion recognition means;

[1562] a translation algorithm means for translating the summarized text;

[1563] means for transmitting the translated summary to a terminal;

[1564] means for displaying the translation results sent to the terminal to the user;

[1565] A system including:

[1566] (Claim 2)

[1567] 10. The system of claim 1, wherein the translation algorithm means uses an external translation API.

[1568] (Claim 3)

[1569] 10. The system of claim 1, wherein the summarization algorithm means uses a particular statistical or machine learning algorithm to generate the summaries. [Explanation of symbols]

[1570] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for providing a user interface for a user to input text; a terminal means for receiving text input to a user interface, converting the text into a data format, and transmitting the data to a server; a summarization algorithm means for summarizing the received text; a translation algorithm means for translating the summarized text; means for transmitting the translated summary to a terminal; means for displaying the translation results sent to the terminal to the user; A system including:

2. The system of claim 1 , wherein the translation algorithm means uses an external translation API.

3. The system of claim 1 , wherein the summarization algorithm means generates the summaries using a specific statistical or machine learning algorithm.

Images