System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting basic information of an accommodation; means for selecting a style of plan suggestion from a plurality of characteristic styles; generator means for generating a plan sentence based on the inputted basic information of the accommodation and the selected style; and means for displaying the generated plan sentence.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The appeal of the plan text is important for attracting guests to accommodation facilities. However, creating multiple plans requires time and effort, and it is easy to run out of ideas. In particular, creating plans in different styles to appeal to different user groups using various writing styles is even more difficult. A method to solve these problems and efficiently generate a variety of plans is needed. [Means for solving the problem]

[0005] The system includes a means for inputting basic information about accommodation facilities, a means for selecting a style for a plan proposal from among several distinctive styles, a generator for generating a plan proposal based on the input basic information about accommodation facilities and the selected style, and a means for displaying the generated plan proposal. The generator generates a plan proposal based on a style selected from three styles: a hotel manager style, a gyaru style, and an inn proprietress style, and further generates the plan proposal by calling a generation AI model based on the user's input. This makes it possible to efficiently generate a variety of plan proposals and make fresh and attractive proposals to different user groups.

[0006] "Basic information about the accommodation" refers to basic data such as the location of the accommodation and the meals provided.

[0007] "Style" refers to the style and atmosphere of a piece of writing, and includes a particular character-based way of expression.

[0008] "Plan proposal writing style" refers to the style of writing used when proposing accommodation plans, and refers to multiple distinctive ways of expression that can be selected.

[0009] "Generator means" refers to a part of the system that automatically generates plan text based on input information.

[0010] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate appropriate plan text from input information.

[0011] "Hotel manager-style writing" refers to a style of writing that exudes a sense of luxury and trustworthiness, as used by a hotel manager.

[0012] "Gal style" refers to the casual and friendly writing style that is unique to young people.

[0013] "The style of a ryokan hostess" refers to a style that expresses a traditional, warm, and hospitable spirit.

[0014] "User" refers to a person or organization that intends to generate an accommodation plan using this system.

[0015] "Terminal" refers to an electronic device that allows a user to input information and view generated plans. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention is a system that allows a user to input basic information about accommodations, select a style for the proposed plan from multiple styles, and automatically generate a plan document using an AI model. Specific embodiments of this system are described below.

[0038] Enter basic information

[0039] First, the user inputs basic information about the accommodation into the terminal, including location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). The terminal stores this information and provides real-time feedback to the user as needed (e.g., displays error messages for input errors or incomplete information).

[0040] Character Selection

[0041] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. The device confirms the user's selection and also saves this information.

[0042] Submitting a plan generation request

[0043] The terminal compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set, usually packaged in a format such as JSON, and sends this data to the server as an HTTP request.

[0044] Plan Generation Process

[0045] The server analyzes the request received from the terminal and extracts basic information about the accommodation facility and the selected writing style information. The server selects the most suitable generation AI model. For example, if a writing style in the style of a female innkeeper is selected, the server calls the generation AI model in the style of a female innkeeper. The server generates a plan text by providing the extracted information as input to the AI ​​model. Examples of generated plans include the following:

[0046] Basic information: "A 5-minute walk from Tokyo Station, this inn offers a Japanese breakfast."

[0047] Selected writing style: Innkeeper

[0048] Generated plan: "Dear guest, we are conveniently located just a 5-minute walk from Kyoto Station and offer a heart-warming Japanese breakfast. Please come and enjoy."

[0049] Submitting and Viewing Generated Plans

[0050] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0051] Specific examples

[0052] Specific examples are shown below.

[0053] 1. The user enters the basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 10 minutes' walk from Kyoto Station."

[0054] 2. The user selects the character "Innkeeper."

[0055] 3. The device sends the information to the server.

[0056] 4. The server generates a plan document using a generative AI model based on the information.

[0057] Generated plan example: "Dear guest, we are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a heart-warming Japanese breakfast. Please come and enjoy."

[0058] 5. The server sends the generated plan document to the terminal.

[0059] 6. The terminal displays the plan text to the user.

[0060] Displayed text: "Dear guest, we are conveniently located just a 10-minute walk from Kyoto Station, and we offer a heart-warming Japanese breakfast. Please come and enjoy."

[0061] As described above, this system allows users to easily generate a variety of plan documents and use them to attract customers to accommodation facilities.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] The user enters basic information about the accommodation into the terminal. Specifically, the user enters location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included") into an input form.

[0065] Step 2:

[0066] The user selects the style of the plan proposal from the UI on the device. The options include three styles: hotel manager style, gyaru style, and inn proprietress style. The user clicks or taps the appropriate option.

[0067] Step 3:

[0068] The device compiles the basic information entered by the user and the selected writing style, and the compiled data is usually structured in JSON format.

[0069] Step 4:

[0070] The device sends structured JSON data to the server as an HTTP POST request, which includes the basic information entered and the selected writing style.

[0071] Step 5:

[0072] The server analyzes the request received from the terminal, specifically extracting basic information about the accommodation and the selected writing style information from the request.

[0073] Step 6:

[0074] The server selects an appropriate AI model based on the selected writing style. For example, if the writing style is "innkeeper-style," the server selects an AI model that is in the innkeeper-style.

[0075] Step 7:

[0076] The server inputs the extracted basic information and stylistic information into a generative AI model to generate a plan sentence. The generated sentence is automatically created based on the input information.

[0077] Step 8:

[0078] The server structures the generated plan text in JSON format and sends it to the terminal as an HTTP response.

[0079] Step 9:

[0080] The device receives the response from the server and analyzes the plan text. Specifically, it extracts the plan text from the JSON data.

[0081] Step 10:

[0082] The terminal displays the extracted plan sentence to the user, so that the user can confirm the generated plan sentence.

[0083] Example 1

[0084] 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."

[0085] In conventional accommodation plan proposal systems, users had to spend a great deal of time and effort creating detailed plan documents. It was also difficult to generate plan documents using different writing styles, and many aspects relied on manual work, making it difficult to ensure consistency and quality. Furthermore, there were problems with sending incorrect information due to insufficient verification of input information and a lack of user feedback.

[0086] 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.

[0087] In this invention, the server includes means for inputting basic information about accommodations, means for selecting a style for a plan proposal from a plurality of distinctive styles, generator means for generating a plan document based on the input basic information about accommodations and the selected style, means for displaying the generated plan document, means for verifying and providing feedback on the input basic information, means for packaging the input basic information and style information, and means for transmitting the packaged data to the server, thereby enabling users to automatically generate high-quality, consistent plan documents while saving time and effort.

[0088] "Basic information about accommodation facilities" is detailed information that serves as a criterion when a user selects accommodation facilities, such as the location of the accommodation facility, meal contents, and room facilities.

[0089] "Writing style" refers to the particular wording and expression used in the proposal text, and is selected based on the user's desired style.

[0090] The "generation device means" is a device or software that automatically generates a plan text based on the input basic information and selected style information.

[0091] "Validation and feedback measures" are functions that check the information entered by the user to detect errors or incompleteness, and provide the user with suggested corrections or error messages in real time.

[0092] A "packaging means" is a method or device that combines different information (for example, basic information and stylistic information) into a single data unit, and is used to maintain data consistency.

[0093] The "means for transmitting to the server" is a process or device that sends the packaged data to the server over a network.

[0094] A "generative AI model" is an artificial intelligence algorithm or software that automatically generates text based on input data.

[0095] "User interface" refers to the screens and input devices that allow the system and the user to exchange information with each other.

[0096] This invention is a system that allows a user to input basic information about accommodations, select a style for the proposed plan from multiple styles, and automatically generate a plan document using an AI model. Specific embodiments of this system are described below.

[0097] Enter basic information

[0098] First, the user enters basic information about the accommodation into the terminal. The basic information about the accommodation includes location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). For example, let's say the user enters "a ryokan (Japanese inn) that is a 10-minute walk from Kyoto Station and serves a Japanese breakfast." The terminal immediately verifies this information and displays an error message in real time for any input errors or incomplete information. The verified basic information is saved in local storage.

[0099] Character Selection

[0100] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. When the user selects "innkeeper style," the device saves this information and notifies the user that the selection is complete.

[0101] Submitting a plan generation request

[0102] The terminal compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set. This data is usually packaged in a format such as JSON, but an example of a specific prompt sentence would be as follows:

[0103] Basic information: "A 10-minute walk from Kyoto Station, this inn offers a Japanese breakfast."

[0104] Selected writing style: Innkeeper

[0105] The device sends this data to the server as an HTTP request.

[0106] Plan Generation Process

[0107] The server analyzes the request received from the device and extracts basic information about the accommodation and the selected writing style. The server then selects the most appropriate generative AI model. For example, if the "style of a landlady at an inn" is selected, the server calls the generative AI model for a landlady at an inn. Specifically, the following generative AI models are used:

[0108] Generative AI models: large-scale generative models such as GPT-3

[0109] The server inputs the extracted information into the AI ​​model and generates a plan. For example, if a user selects the basic information "a 10-minute walk from Kyoto Station, a Japanese-style inn with breakfast" and the writing style "the inn's landlady," the following example plan is generated:

[0110] "Dear guest, we are a conveniently located inn, just a 10-minute walk from Kyoto Station, and we offer a heart-warming Japanese breakfast. Please feel free to come and enjoy."

[0111] Submitting and Viewing Generated Plans

[0112] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0113] Using this system, users can easily generate a variety of plan documents and use them to attract customers to their accommodations.

[0114] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0115] Step 1:

[0116] The user enters basic information about the accommodation into the terminal. For example, they might enter information such as "a hotel with breakfast included, a five-minute walk from Tokyo Station." The terminal receives this information and verifies in real time whether the input is in the correct format. Specifically, if required fields are not filled in, an error message is displayed. If the input information is correct, the terminal saves the basic information in local storage. Input is in text format, and the output is the verified basic information.

[0117] Step 2:

[0118] The user selects the writing style of the plan proposal from a drop-down menu or radio buttons provided on the terminal screen. For example, the user selects the writing style of "the proprietress of a ryokan." The terminal receives this selection, confirms the user's selection, and saves it. Specifically, it displays a notification to the user that the selection is complete. The input is the selection of writing style, and the output is the selected writing style information.

[0119] Step 3:

[0120] The device compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set, and then packages this data in JSON format. For example, the following JSON data is generated:

[0121] json

[0122] {

[0123] "basic_info": "Hotel with breakfast, 5 minutes walk from Tokyo Station",

[0124] "style": "Innkeeper"

[0125] }

[0126] The terminal sends this JSON data to the server as an HTTP request. The input is basic information and style information, and the output is packaged JSON data.

[0127] Step 4:

[0128] The server analyzes the HTTP request received from the terminal. It deserializes the received data and extracts basic information about the accommodation and stylistic information. For example, extract "Hotel with breakfast, 5 minutes' walk from Tokyo Station" and "Proprietress of the inn" from the received data. The input is JSON data, and the output is the extracted basic information and stylistic information.

[0129] Step 5:

[0130] The server selects the optimal generative AI model based on the extracted information. For example, if the writing style of "innkeeper" is selected, the corresponding generative AI model is loaded. The server inputs basic information and writing style information into the generative AI model and generates a plan sentence. The specific input is the basic information "A hotel with breakfast, a five-minute walk from Tokyo Station" and the writing style information "Innkeeper", and the output is the plan sentence "Dear customer, we are a conveniently located hotel, a five-minute walk from Tokyo Station, and breakfast is available. Please feel free to use it."

[0131] Step 6:

[0132] The server packages the generated plan document and sends it as an HTTP response to the terminal. The input is the generated plan document and the output is the HTTP response.

[0133] Step 7:

[0134] The terminal receives the HTTP response from the server and analyzes the received data. It extracts the plan text and displays it on the user interface. The user can then view and confirm the generated plan text. Specifically, the user sees the text on the screen: "Dear customer, we are offering breakfast at a hotel conveniently located a five-minute walk from Tokyo Station. Please feel free to enjoy it." The input is the HTTP response data, and the output is the displayed plan text.

[0135] (Application example 1)

[0136] 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."

[0137] Conventional accommodation plan proposal systems could only make proposals using a fixed style, making it difficult to generate promotional text that flexibly reflects the individual needs of users and the characteristics of the facility. Furthermore, there was no means of automatically generating flexible and effective promotional text for other service types, such as food delivery services. Therefore, there is a need for an effective way to convey the appeal of facilities and services to the fullest extent.

[0138] 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.

[0139] In this invention, the server includes a means for inputting basic information about accommodations or food service locations, a means for selecting a style for the plan proposal or promotional text from a plurality of distinctive styles, and a generator means for generating plan text or promotional text based on the input basic information and the selected style, thereby enabling the automatic generation of plan text or promotional text in a flexible and diverse style that meets the needs of users.

[0140] "Accommodation facilities" refers to all facilities that provide accommodation services, and specifically includes hotels, inns, private lodgings, guest houses, etc.

[0141] "Food service location" refers to any facility that serves food and beverages, including restaurants, cafes, and food delivery services.

[0142] "Basic information" refers to information about the characteristics and service details of accommodations and food service locations, and specifically includes location, menu items, service details, price range, etc.

[0143] "Writing style" refers to the style of expression used when creating plan documents and promotional texts, and specifically includes hotel manager style, funky pop style, chic restaurant style, inn proprietress style, etc.

[0144] "Plan proposal" refers to a document proposing the services and benefits of accommodations and food establishments to customers.

[0145] "Promotional text" refers to text created to effectively advertise the services and menus of food service establishments, etc.

[0146] The "generation device means" refers to a device having the function of automatically generating a plan text or promotional text based on the input basic information and the selected writing style.

[0147] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates appropriate sentences based on input data.

[0148] The term "server" refers to a computer system that manages and processes data, and in the present invention is a central device that is responsible for generating plan documents and promotional documents.

[0149] The present invention is a system that inputs basic information about accommodations or food service locations, selects a style of plan proposal or promotional text from multiple distinctive styles, and automatically generates text using a generative AI model. One specific embodiment of the present invention is described below.

[0150] First, the user uses a device (such as a smartphone or head-mounted display) to input basic information about the accommodation or food service location. This information includes location information (e.g., "5 minutes' walk from X station"), menu items (e.g., "pizza, salad, pasta"), and service details (e.g., "breakfast included").

[0151] Next, the user selects a writing style using drop-down menus or radio buttons provided on the device. The available writing styles include hotel manager, funky pop, chic restaurant, and innkeeper. The user's selected writing style information is also saved on the device.

[0152] The device compiles the input basic information and the selected writing style information into a single data package, usually in JSON format, and sends this data to the server as an HTTP request.

[0153] The server analyzes the request received from the device and extracts basic information and the selected writing style information. The server then selects the most appropriate generative AI model. For example, if a funky pop style writing style is selected, the server calls a funky pop style generative AI model. The server generates a plan or promotional text by providing the extracted information as input to the generative AI model.

[0154] An example of a generated plan or promotion statement is:

[0155] Basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 5 minutes' walk from XX Station."

[0156] Selected writing style: Innkeeper style

[0157] Generated plan: "Dear guest, we are a conveniently located inn, just a 5-minute walk from XX Station, and we offer a heart-warming Japanese breakfast. Please come and enjoy."

[0158] The server sends the generated text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the generated text, and displays it on the user interface. This allows the user to view the automatically generated text.

[0159] To implement this system, the following hardware and software are used:

[0160] Devices: Digital devices such as smartphones and head-mounted displays

[0161] Server: A computer system that manages and processes data.

[0162] Generative AI models, such as the OpenAI API for natural language generation

[0163] For example, to generate a funky pop style promotional text, the prompt text is:

[0164] Menu items: Pizza, Salad, Pasta

[0165] Delivery area: Shibuya Ward, Meguro Ward

[0166] Style: Funky Pop

[0167] Generate a promotional text:

[0168] This invention makes it possible to automatically generate plan texts or promotional texts in a variety of writing styles according to the needs of users, thereby maximizing the appeal of the services of accommodation facilities and food service establishments.

[0169] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0170] Step 1:

[0171] The user uses the device to input basic information about the accommodation or food service location. This information includes location information (e.g., "5 minutes' walk from X station"), menu items (e.g., "pizza, salad, pasta"), and service details (e.g., "breakfast included"). Based on this input, data is stored in the device.

[0172] Step 2:

[0173] Users can select a writing style using drop-down menus or radio buttons provided on the device. The available writing styles include hotel manager, funky pop, chic restaurant, and innkeeper. The writing style information selected by the user is also saved on the device.

[0174] Step 3:

[0175] The device compiles the input basic information and the selected writing style information into a single piece of data, usually packaged in a format such as JSON, and sends this data to the server as an HTTP request.

[0176] Step 4:

[0177] The server analyzes the request received from the terminal and extracts basic information and selected writing style information. The data obtained from this analysis is stored internally on the server.

[0178] Step 5:

[0179] The server selects the most suitable AI model. For example, if a funky pop style is selected, the server calls a funky pop AI model. The data required for this selection are basic information and style information.

[0180] Step 6:

[0181] The server provides the extracted basic information and style information as input to the generative AI model. The generative AI model performs natural language processing based on this data to generate appropriate plan or promotional text. The generated text is stored internally on the server.

[0182] Step 7:

[0183] The server sends the generated plan or promotion text to the terminal as an HTTP response, which includes the generated text.

[0184] Step 8:

[0185] The terminal receives the response from the server, analyzes it, and extracts the generated text. The terminal displays the text on the user interface, allowing the user to view the automatically generated plan text or promotion text.

[0186] In this way, a series of processes is completed in which a plan or promotional text is automatically generated using a generative AI model based on the basic information entered by the user and the writing style selected, and the results are displayed on the terminal.

[0187] 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.

[0188] This invention combines a system in which a user inputs basic information about an accommodation facility, selects a style of plan proposal from multiple styles, and automatically generates plan text using an AI model, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0189] Enter basic information

[0190] First, the user inputs basic information about the accommodation into the terminal, including location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). The terminal stores this information and provides real-time feedback to the user as needed (e.g., displays error messages for input errors or incomplete information).

[0191] Character Selection

[0192] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. The device confirms the user's selection and also saves this information.

[0193] Emotion Engine Operation

[0194] The device is equipped with an emotion engine that recognizes the user's emotions. The emotion engine estimates the user's emotions based on the user's input and interactions, such as keyboard typing speed and mouse movements, as well as facial recognition and voice analysis. This emotion information is used to generate the plan text.

[0195] Submitting a plan generation request

[0196] The device compiles the basic information entered by the user, the selected writing style, and the estimated emotion information into a single data set. This data is usually packaged in a format such as JSON. The device then sends this data to the server as an HTTP request.

[0197] Plan Generation Process

[0198] The server analyzes the request received from the device and extracts basic information about the accommodation facility, the selected writing style, and emotional information. The server then selects the optimal generative AI model. For example, if a writing style in the style of a female innkeeper is selected, the server calls the generative AI model in the style of a female innkeeper. The server generates a plan text by providing the extracted information as input to the AI ​​model. At this time, the tone and expression of the text are adjusted based on the emotional information.

[0199] Submitting and Viewing Generated Plans

[0200] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0201] Specific examples

[0202] Specific examples are shown below.

[0203] 1. The user enters the basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 10 minutes' walk from Kyoto Station."

[0204] 2. The user selects the character "Innkeeper."

[0205] 3. The device uses an emotion engine to estimate the user's emotion as "excited."

[0206] 4. The device sends the information to the server.

[0207] 5. The server generates a plan document using a generative AI model based on the information.

[0208] Generated plan example: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0209] 6. The server sends the generated plan document to the terminal.

[0210] 7. The terminal displays the plan text to the user.

[0211] Displayed text: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0212] As described above, this system can generate a variety of plan sentences that correspond to the user's emotions, which can be used to attract customers to accommodation facilities.

[0213] The processing flow will be explained below.

[0214] Step 1:

[0215] The user enters basic information about the accommodation into the terminal. Specifically, the user enters information about the location (e.g., "10 minutes' walk from Kyoto Station") and meal details (e.g., "Japanese breakfast included") into the input form.

[0216] Step 2:

[0217] The user selects the style of the plan proposal from the UI on the device. The options include three styles: hotel manager style, gyaru style, and inn proprietress style. The user clicks or taps the appropriate option.

[0218] Step 3:

[0219] The device compiles the basic information entered by the user and the selected writing style, and the compiled data is usually structured in JSON format.

[0220] Step 4:

[0221] The emotion engine built into the device analyzes the user's input and interactions (e.g., keyboard input speed, mouse movement, face recognition, voice analysis) to estimate the user's emotion. This estimated emotion information is added to the data.

[0222] Step 5:

[0223] The device sends structured JSON data to the server as an HTTP POST request, which includes the input basic information, the selected writing style, and the estimated emotion information.

[0224] Step 6:

[0225] The server analyzes the request received from the terminal, specifically extracting basic information about the accommodation, the selected writing style, and sentiment information from the request.

[0226] Step 7:

[0227] The server selects an appropriate AI model based on the selected writing style. For example, if the writing style is "innkeeper-style," the server selects an AI model that is in the innkeeper-style.

[0228] Step 8:

[0229] The server inputs the extracted basic information, stylistic information, and emotional information into a generative AI model to generate a plan sentence. The tone and expression of the generated sentence are adjusted based on the emotional information.

[0230] Step 9:

[0231] The server structures the generated plan text in JSON format and sends it to the terminal as an HTTP response.

[0232] Step 10:

[0233] The device receives the response from the server and analyzes the plan text. Specifically, it extracts the plan text from the JSON data.

[0234] Step 11:

[0235] The terminal displays the extracted plan sentence to the user, so that the user can confirm the generated plan sentence.

[0236] Example 2

[0237] 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."

[0238] Conventional accommodation plan proposal systems have difficulty generating flexible proposal text that reflects the user's emotions and preferences. Furthermore, the style of the proposal text is fixed, and users cannot choose from a variety of styles, making it difficult to attract their interest. Furthermore, because the automatic generation of plan text does not take the user's emotions into consideration, the proposal content can sometimes lack consistency.

[0239] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting basic information about accommodation facilities, a means for selecting a style of plan proposal from among a plurality of distinctive writing styles, a generation device means for generating a plan text based on the input basic information about accommodation facilities, the selected writing style, and emotional information, and a means for displaying the generated plan text. This makes it possible to generate a variety of plan texts according to the user's emotions and to help attract customers to accommodation facilities.

[0240] "Basic information about accommodation facilities" refers to key information about accommodation facilities, such as location information and meal contents.

[0241] "Plan proposal writing style" refers to the style and tone of expression in the plan text, and includes three types, for example, hotel manager style, gal style, and inn proprietress style.

[0242] "Emotional information" is information that indicates the user's emotional state and is estimated based on keyboard typing speed, facial recognition, voice analysis, etc.

[0243] The "generation device means" refers to a device or program for generating a plan text based on basic information about the accommodation facility, the selected style and emotion information.

[0244] A "generative AI model" refers to an artificial intelligence model that generates sentences based on input information, and is used to create appropriate sentences based on style and emotion.

[0245] "Display means" refers to means for displaying the generated plan text on the screen or display of a terminal so that the user can check it.

[0246] An "HTTP request" refers to a protocol-based communication method by which a client (here, a terminal) requests data or processing from a server.

[0247] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight data exchange format for structuring, storing, and transferring data.

[0248] This invention combines a system in which a user inputs basic information about an accommodation facility, selects a style of plan proposal from multiple styles, and automatically generates plan text using an AI model, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0249] First, the user enters basic information about the accommodation into the terminal. For example, basic information about the accommodation may include information such as "10 minutes' walk from Kyoto Station, Japanese breakfast included." The terminal temporarily stores the information entered by the user and displays an error message if the information is incomplete or there is an input error. This process of entering basic information allows the user to receive feedback in real time.

[0250] Next, the user selects the style of the plan proposal from the options provided on the device (drop-down menu or radio button). The style can be selected from "Hotel Manager Style," "Gyaru Style," or "Innkeeper Style." The device confirms the selected style and saves this information.

[0251] Furthermore, the device is equipped with an emotion engine that recognizes the user's emotions. This emotion recognition uses functions such as keyboard input speed, face recognition, and voice analysis. For example, if the user types quickly or smiles, it is estimated that the user is "excited." This emotion information is used when generating plan sentences.

[0252] The device combines basic information, the selected writing style, and estimated emotion information into a single package in JSON format, which is then sent to the server as an HTTP request. For example, the prompt text might look like this:

[0253] {

[0254] "Basic Information": "10 minutes walk from Kyoto Station, Japanese breakfast included",

[0255] "Style": "Innkeeper style",

[0256] "Emotion": "Excited"

[0257] }

[0258] The server receives the request sent from the device and analyzes the JSON data. Based on the analyzed information, it selects the most appropriate generative AI model. For example, if "innkeeper style" is selected as the writing style, the innkeeper style generative AI model is called. The server then inputs the information into the AI ​​model and generates a plan sentence. At this time, the tone and expression of the sentence are adjusted based on the emotional information.

[0259] The generated plan text is sent to the terminal as an HTTP response. The terminal receives the response, analyzes it, extracts the plan text, and displays it on the user interface. The user can check the automatically generated plan text in real time.

[0260] As a specific example, if a user inputs "a ryokan (Japanese inn) with a Japanese breakfast, a 10-minute walk from Kyoto Station," selects "ryokan proprietress" as the writing style, and the emotion engine estimates that the user is "excited," the server will generate a plan sentence such as "Hello! We are offering a heart-warming Japanese breakfast at a ryokan conveniently located a 10-minute walk from Kyoto Station. We hope you have a wonderful time!" The device will display this sentence to the user, allowing the user to confirm its contents.

[0261] As described above, this system generates and provides a variety of plan texts that take emotions into consideration in order to increase the user's satisfaction with accommodation proposals.

[0262] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0263] Step 1:

[0264] The user enters basic information.

[0265] Input: The user enters basic information about the accommodation, such as "10 minutes walk from Kyoto Station, Japanese breakfast included."

[0266] Data processing: The terminal temporarily stores the input data and checks the input contents of each field.

[0267] Output: The basic information entered by the user is saved and an error message is displayed if the information is incomplete or contains a typo.

[0268] What happens: The device may display the error message "Breakfast type not entered."

[0269] Step 2:

[0270] The user selects the style of the plan proposal.

[0271] Input: The user selects one of three writing styles: "Hotel manager style," "Gyaru style," and "Innkeeper style."

[0272] Data processing: The device saves the selected writing style.

[0273] Output: The selected writing style is saved to the terminal for the next processing step.

[0274] Specific behavior: The user selects "Innkeeper Style" using the radio button.

[0275] Step 3:

[0276] The device's emotion engine recognizes the user's emotions.

[0277] Input: User input and interaction (keyboard typing speed, facial recognition, voice analysis, etc.)

[0278] Data processing: The device's emotion engine analyzes these input data and estimates the user's emotions.

[0279] Output: Estimated emotion information (e.g., "excited")

[0280] Specific behavior: The device uses the camera to scan the user's face, detects a smile, and infers that the user is "excited."

[0281] Step 4:

[0282] The terminal sends a plan generation request to the server.

[0283] Input: Basic information, selected writing style, estimated sentiment information

[0284] Data processing: The device packages this information in JSON format.

[0285] Output: Sends the packaged JSON data to the server as an HTTP request.

[0286] Specific operation: The device sends the following data in JSON format: "10 minutes walk from Kyoto Station, Japanese breakfast included," "Landlady-like inn," and "Excited."

[0287] Step 5:

[0288] The server performs the plan generation process.

[0289] Input: JSON data sent from the terminal

[0290] Data processing: The server parses the JSON data and extracts basic information, selected writing style, and sentiment information. It then selects the optimal generative AI model and inputs the extracted information into the AI ​​model.

[0291] Output: Generated plan text (e.g., "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!")

[0292] Specific operation: The server selects the "ryokan proprietress-style" generation AI model, and generates a plan text by inputting the information "10 minutes' walk from Kyoto Station, Japanese breakfast included" and "Excited."

[0293] Step 6:

[0294] The server sends the generated plan text to the terminal.

[0295] Input: Generated plan document

[0296] Data processing: The server packages the generated plan document into an HTTP response.

[0297] Output: Sent to the device as an HTTP response.

[0298] Specific operation: The server sends the generated plan document to the terminal as an HTTP response.

[0299] Step 7:

[0300] The terminal displays the generated plan text.

[0301] Input: HTTP response received from the server

[0302] Data processing: The terminal analyzes the response and extracts the plan text.

[0303] Output: The plan text is displayed in the user interface.

[0304] What it does: The device displays the following text: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station, and we offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0305] (Application example 2)

[0306] 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."

[0307] Conventional generation systems generate text without considering the user's emotions, making them unable to flexibly respond to individual needs. It is also difficult to generate text with an appropriate tone for specific situations and emotions. In particular, when generating equipment inspection reports for factory robots, reports are provided that ignore the user's emotions, which can lead to problems in effectively conveying necessary information.

[0308] 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.

[0309] In this invention, the server is equipped with an emotion engine that recognizes the user's emotions, and includes means for adjusting the tone and expression of the text based on the analyzed emotion information, means for generating a plan text based on a style selected from three styles: formal, casual, and technical terminology, and means for calling a generation AI model based on the user's input and the analyzed emotion information to generate the plan text. This enables more individualized and effective text generation that is in line with the user's emotions.

[0310] "Basic information about accommodation facility" is data that allows the user to input details about the accommodation facility, including location information, meal details, and the like.

[0311] The "plan proposal writing style" is selected from among several distinctive styles of expression, and is a factor that determines the tone and atmosphere of the generated text.

[0312] "Generation device means" refers to a device for automatically generating sentences using a generative AI model based on basic information entered by a user and a selected writing style.

[0313] The "emotion engine" is an engine that analyzes the user's facial expressions and voice to recognize emotions, and adjusts the tone and expression of the text based on that information.

[0314] A "formal style" is a style that emphasizes formality and courtesy and is used in formal settings, and is suitable for official documents.

[0315] "Casual writing style" is a writing style that is everyday and familiar, and uses informal and simple expressions.

[0316] A "technical jargon style" is a style that includes many specialized terms and expressions used in a particular technical field, and is aimed at engineers and specialists.

[0317] A "generative AI model" is an artificial intelligence model used to generate appropriate sentences based on input data, and creates sentences using a learning algorithm.

[0318] This invention is a system that combines an emotion engine that recognizes the user's emotions with a system that allows a user to input basic information about an accommodation facility, select a suggested writing style from multiple distinctive writing styles, and automatically generate a plan document using an AI model. A specific embodiment of this system will be described below.

[0319] First, the user inputs basic information about the accommodation facility into the terminal. This basic information includes data such as "Cooling system within the factory, east side of the second factory, inspection details: check for abnormal fan noise." This information is input using an interface such as a keyboard or touch screen.

[0320] Next, the user selects the style of the inspection report from options provided on the device: formal, casual, or technical.

[0321] The device has a built-in emotion engine that recognizes the user's emotions. This emotion engine captures the user's facial expressions and voice using a camera and microphone, and estimates the user's emotions using emotion analysis software (e.g., Affectiva SDK). The estimated emotion information is then used to adjust the tone and expression of the generated text.

[0322] The emotional information collected by the emotion engine, the basic information entered by the user, and the selected writing style are packaged in JSON format and sent to the server as an HTTP request. The server receives this request and analyzes the request. The analysis involves using a programming language such as Python to input the data into a generative AI model (e.g., OpenAI GPT-3).

[0323] The server selects the most appropriate generative AI model based on the received content. For example, if a technical terminology style is selected, a generative AI model that matches that style will be called up. The generative AI model receives the prompt "Cooling system inside the factory, east side of the second factory, inspection content: check for abnormal fan noise" and generates an inspection report in the appropriate tone.

[0324] Here are some examples of prompts:

[0325] Cooling system inside the factory, east side of the second factory, inspection content: Check for abnormal fan noise

[0326] The generated inspection report may have the following format, for example: "Inspection results for the cooling system: An abnormal noise was detected from the cooling fan located on the east side of the second factory. Worn fan blades and deterioration of bearings were observed. Immediate replacement is recommended."

[0327] The generated report is sent from the server to the terminal as an HTTP response. The terminal receives this report and displays it on the user interface, allowing the user to check the automatically generated inspection report.

[0328] This system enables flexible responses based on the user's emotions, and is expected to effectively convey necessary information, particularly when generating equipment inspection reports for factory robots.

[0329] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0330] Step 1:

[0331] The user inputs basic information about the accommodation facility or factory equipment into the terminal. This basic information may include, for example, "Cooling system within the factory, east side of the second factory, inspection details: check for abnormal fan noise." This input information is stored in the terminal's memory and feedback is provided to the user in real time. The input data format is specified in JSON format or similar.

[0332] Step 2:

[0333] The user selects a writing style from the options provided on the device. There are three writing styles to choose from: formal, casual, and technical. This selection is saved on the device. For example, if "technical" is selected, that information will be used in the next step.

[0334] Step 3:

[0335] The device's built-in emotion engine analyzes the user's emotions. It captures the user's facial expressions and voice using a camera and microphone, and uses emotion analysis software (e.g., Affectiva SDK) to estimate emotional information. This emotional information is also stored on the device. The analyzed emotional information may include, for example, "I'm nervous."

[0336] Step 4:

[0337] The device will then compile the input basic information, the selected writing style, and the analyzed emotional information into a single data package. The package data will be in JSON format, and will look something like this:

[0338] {

[0339] "facility_info": "Factory cooling system, east side of Factory 2, inspection details: check for abnormal fan noise",

[0340] "selected_tone": "Technical jargon style",

[0341] "user_emotion": "I'm nervous"

[0342] }

[0343] This data is sent to the server as an HTTP request.

[0344] Step 5:

[0345] The server receives the data package sent from the client, analyzes the received data, and extracts basic information, selected writing style, and sentiment information separately.

[0346] Step 6:

[0347] The server selects the most appropriate generative AI model (e.g., OpenAI GPT-3) based on the analyzed data. For example, if "technical terminology style" is selected, the server calls the corresponding generative AI model. The extracted basic information, the selected style, and the emotional information are provided as input data to the called generative AI model.

[0348] Step 7:

[0349] The generative AI model generates a plan sentence based on the input data. The tone and expression of the sentence are adjusted based on the emotional information. For example, the generated plan sentence might be in the following format: "Inspection results for the cooling system: An abnormal noise was detected from the cooling fan located on the east side of the second factory. Wear on the fan blades and deterioration of the bearings were observed. Prompt replacement is recommended."

[0350] Step 8:

[0351] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives this response and displays the generated plan text on the user interface. As a result, the user can check the automatically generated appropriate plan text.

[0352] 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.

[0353] 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.

[0354] 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.

[0355] [Second embodiment]

[0356] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0357] 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.

[0358] 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).

[0359] 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.

[0360] 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.

[0361] 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).

[0362] 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.

[0363] 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.

[0364] 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.

[0365] 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.

[0366] 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.

[0367] 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."

[0368] This invention is a system that allows a user to input basic information about accommodations, select a style for the proposed plan from multiple styles, and automatically generate a plan document using an AI model. Specific embodiments of this system are described below.

[0369] Enter basic information

[0370] First, the user inputs basic information about the accommodation into the terminal, including location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). The terminal stores this information and provides real-time feedback to the user as needed (e.g., displays error messages for input errors or incomplete information).

[0371] Character Selection

[0372] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. The device confirms the user's selection and also saves this information.

[0373] Submitting a plan generation request

[0374] The terminal compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set, usually packaged in a format such as JSON, and sends this data to the server as an HTTP request.

[0375] Plan Generation Process

[0376] The server analyzes the request received from the terminal and extracts basic information about the accommodation facility and the selected writing style information. The server selects the most suitable generation AI model. For example, if a writing style in the style of a female innkeeper is selected, the server calls the generation AI model in the style of a female innkeeper. The server generates a plan text by providing the extracted information as input to the AI ​​model. Examples of generated plans include the following:

[0377] Basic information: "A 5-minute walk from Tokyo Station, this inn offers a Japanese breakfast."

[0378] Selected writing style: Innkeeper

[0379] Generated plan: "Dear guest, we are conveniently located just a 5-minute walk from Kyoto Station and offer a heart-warming Japanese breakfast. Please come and enjoy."

[0380] Submitting and Viewing Generated Plans

[0381] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0382] Specific examples

[0383] Specific examples are shown below.

[0384] 1. The user enters the basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 10 minutes' walk from Kyoto Station."

[0385] 2. The user selects the character "Innkeeper."

[0386] 3. The device sends the information to the server.

[0387] 4. The server generates a plan document using a generative AI model based on the information.

[0388] Generated plan example: "Dear guest, we are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a heart-warming Japanese breakfast. Please come and enjoy."

[0389] 5. The server sends the generated plan document to the terminal.

[0390] 6. The terminal displays the plan text to the user.

[0391] Displayed text: "Dear guest, we are conveniently located just a 10-minute walk from Kyoto Station, and we offer a heart-warming Japanese breakfast. Please come and enjoy."

[0392] As described above, this system allows users to easily generate a variety of plan documents and use them to attract customers to accommodation facilities.

[0393] The processing flow will be explained below.

[0394] Step 1:

[0395] The user enters basic information about the accommodation into the terminal. Specifically, the user enters location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included") into an input form.

[0396] Step 2:

[0397] The user selects the style of the plan proposal from the UI on the device. The options include three styles: hotel manager style, gyaru style, and inn proprietress style. The user clicks or taps the appropriate option.

[0398] Step 3:

[0399] The device compiles the basic information entered by the user and the selected writing style, and the compiled data is usually structured in JSON format.

[0400] Step 4:

[0401] The device sends structured JSON data to the server as an HTTP POST request, which includes the basic information entered and the selected writing style.

[0402] Step 5:

[0403] The server analyzes the request received from the terminal, specifically extracting basic information about the accommodation and the selected writing style information from the request.

[0404] Step 6:

[0405] The server selects an appropriate AI model based on the selected writing style. For example, if the writing style is "innkeeper-style," the server selects an AI model that is in the innkeeper-style.

[0406] Step 7:

[0407] The server inputs the extracted basic information and stylistic information into a generative AI model to generate a plan sentence. The generated sentence is automatically created based on the input information.

[0408] Step 8:

[0409] The server structures the generated plan text in JSON format and sends it to the terminal as an HTTP response.

[0410] Step 9:

[0411] The device receives the response from the server and analyzes the plan text. Specifically, it extracts the plan text from the JSON data.

[0412] Step 10:

[0413] The terminal displays the extracted plan sentence to the user, so that the user can confirm the generated plan sentence.

[0414] Example 1

[0415] 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."

[0416] In conventional accommodation plan proposal systems, users had to spend a great deal of time and effort creating detailed plan documents. It was also difficult to generate plan documents using different writing styles, and many aspects relied on manual work, making it difficult to ensure consistency and quality. Furthermore, there were problems with sending incorrect information due to insufficient verification of input information and a lack of user feedback.

[0417] 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.

[0418] In this invention, the server includes means for inputting basic information about accommodations, means for selecting a style for a plan proposal from a plurality of distinctive styles, generator means for generating a plan document based on the input basic information about accommodations and the selected style, means for displaying the generated plan document, means for verifying and providing feedback on the input basic information, means for packaging the input basic information and style information, and means for transmitting the packaged data to the server, thereby enabling users to automatically generate high-quality, consistent plan documents while saving time and effort.

[0419] "Basic information about accommodation facilities" is detailed information that serves as a criterion when a user selects accommodation facilities, such as the location of the accommodation facility, meal contents, and room facilities.

[0420] "Writing style" refers to the particular wording and expression used in the proposal text, and is selected based on the user's desired style.

[0421] The "generation device means" is a device or software that automatically generates a plan text based on the input basic information and selected style information.

[0422] "Validation and feedback measures" are functions that check the information entered by the user to detect errors or incompleteness, and provide the user with suggested corrections or error messages in real time.

[0423] A "packaging means" is a method or device that combines different information (for example, basic information and stylistic information) into a single data unit, and is used to maintain data consistency.

[0424] The "means for transmitting to the server" is a process or device that sends the packaged data to the server over a network.

[0425] A "generative AI model" is an artificial intelligence algorithm or software that automatically generates text based on input data.

[0426] "User interface" refers to the screens and input devices that allow the system and the user to exchange information with each other.

[0427] This invention is a system that allows a user to input basic information about accommodations, select a style for the proposed plan from multiple styles, and automatically generate a plan document using an AI model. Specific embodiments of this system are described below.

[0428] Enter basic information

[0429] First, the user enters basic information about the accommodation into the terminal. The basic information about the accommodation includes location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). For example, let's say the user enters "a ryokan (Japanese inn) that is a 10-minute walk from Kyoto Station and serves a Japanese breakfast." The terminal immediately verifies this information and displays an error message in real time for any input errors or incomplete information. The verified basic information is saved in local storage.

[0430] Character Selection

[0431] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. When the user selects "innkeeper style," the device saves this information and notifies the user that the selection is complete.

[0432] Submitting a plan generation request

[0433] The terminal compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set. This data is usually packaged in a format such as JSON, but an example of a specific prompt sentence would be as follows:

[0434] Basic information: "A 10-minute walk from Kyoto Station, this inn offers a Japanese breakfast."

[0435] Selected writing style: Innkeeper

[0436] The device sends this data to the server as an HTTP request.

[0437] Plan Generation Process

[0438] The server analyzes the request received from the device and extracts basic information about the accommodation and the selected writing style. The server then selects the most appropriate generative AI model. For example, if the "style of a landlady at an inn" is selected, the server calls the generative AI model for a landlady at an inn. Specifically, the following generative AI models are used:

[0439] Generative AI models: large-scale generative models such as GPT-3

[0440] The server inputs the extracted information into the AI ​​model and generates a plan. For example, if a user selects the basic information "a 10-minute walk from Kyoto Station, a Japanese-style inn with breakfast" and the writing style "the inn's landlady," the following example plan is generated:

[0441] "Dear guest, we are a conveniently located inn, just a 10-minute walk from Kyoto Station, and we offer a heart-warming Japanese breakfast. Please feel free to come and enjoy."

[0442] Submitting and Viewing Generated Plans

[0443] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0444] Using this system, users can easily generate a variety of plan documents and use them to attract customers to their accommodations.

[0445] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0446] Step 1:

[0447] The user enters basic information about the accommodation into the terminal. For example, they might enter information such as "a hotel with breakfast included, a five-minute walk from Tokyo Station." The terminal receives this information and verifies in real time whether the input is in the correct format. Specifically, if required fields are not filled in, an error message is displayed. If the input information is correct, the terminal saves the basic information in local storage. Input is in text format, and the output is the verified basic information.

[0448] Step 2:

[0449] The user selects the writing style of the plan proposal from a drop-down menu or radio buttons provided on the terminal screen. For example, the user selects the writing style of "the proprietress of a ryokan." The terminal receives this selection, confirms the user's selection, and saves it. Specifically, it displays a notification to the user that the selection is complete. The input is the selection of writing style, and the output is the selected writing style information.

[0450] Step 3:

[0451] The device compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set, and then packages this data in JSON format. For example, the following JSON data is generated:

[0452] json

[0453] {

[0454] "basic_info": "Hotel with breakfast, 5 minutes walk from Tokyo Station",

[0455] "style": "Innkeeper"

[0456] }

[0457] The terminal sends this JSON data to the server as an HTTP request. The input is basic information and style information, and the output is packaged JSON data.

[0458] Step 4:

[0459] The server analyzes the HTTP request received from the terminal. It deserializes the received data and extracts basic information about the accommodation and stylistic information. For example, extract "Hotel with breakfast, 5 minutes' walk from Tokyo Station" and "Proprietress of the inn" from the received data. The input is JSON data, and the output is the extracted basic information and stylistic information.

[0460] Step 5:

[0461] The server selects the optimal generative AI model based on the extracted information. For example, if the writing style of "innkeeper" is selected, the corresponding generative AI model is loaded. The server inputs basic information and writing style information into the generative AI model and generates a plan sentence. The specific input is the basic information "A hotel with breakfast, a five-minute walk from Tokyo Station" and the writing style information "Innkeeper", and the output is the plan sentence "Dear customer, we are a conveniently located hotel, a five-minute walk from Tokyo Station, and breakfast is available. Please feel free to use it."

[0462] Step 6:

[0463] The server packages the generated plan document and sends it as an HTTP response to the terminal. The input is the generated plan document and the output is the HTTP response.

[0464] Step 7:

[0465] The terminal receives the HTTP response from the server and analyzes the received data. It extracts the plan text and displays it on the user interface. The user can then view and confirm the generated plan text. Specifically, the user sees the text on the screen: "Dear customer, we are offering breakfast at a hotel conveniently located a five-minute walk from Tokyo Station. Please feel free to enjoy it." The input is the HTTP response data, and the output is the displayed plan text.

[0466] (Application example 1)

[0467] 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."

[0468] Conventional accommodation plan proposal systems could only make proposals using a fixed style, making it difficult to generate promotional text that flexibly reflects the individual needs of users and the characteristics of the facility. Furthermore, there was no means of automatically generating flexible and effective promotional text for other service types, such as food delivery services. Therefore, there is a need for an effective way to convey the appeal of facilities and services to the fullest extent.

[0469] 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.

[0470] In this invention, the server includes a means for inputting basic information about accommodations or food service locations, a means for selecting a style for the plan proposal or promotional text from a plurality of distinctive styles, and a generator means for generating plan text or promotional text based on the input basic information and the selected style, thereby enabling the automatic generation of plan text or promotional text in a flexible and diverse style that meets the needs of users.

[0471] "Accommodation facilities" refers to all facilities that provide accommodation services, and specifically includes hotels, inns, private lodgings, guest houses, etc.

[0472] "Food service location" refers to any facility that serves food and beverages, including restaurants, cafes, and food delivery services.

[0473] "Basic information" refers to information about the characteristics and service details of accommodations and food service locations, and specifically includes location, menu items, service details, price range, etc.

[0474] "Writing style" refers to the style of expression used when creating plan documents and promotional texts, and specifically includes hotel manager style, funky pop style, chic restaurant style, inn proprietress style, etc.

[0475] "Plan proposal" refers to a document proposing the services and benefits of accommodations and food establishments to customers.

[0476] "Promotional text" refers to text created to effectively advertise the services and menus of food service establishments, etc.

[0477] The "generation device means" refers to a device having the function of automatically generating a plan text or promotional text based on the input basic information and the selected writing style.

[0478] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates appropriate sentences based on input data.

[0479] The term "server" refers to a computer system that manages and processes data, and in the present invention is a central device that is responsible for generating plan documents and promotional documents.

[0480] The present invention is a system that inputs basic information about accommodations or food service locations, selects a style of plan proposal or promotional text from multiple distinctive styles, and automatically generates text using a generative AI model. One specific embodiment of the present invention is described below.

[0481] First, the user uses a device (such as a smartphone or head-mounted display) to input basic information about the accommodation or food service location. This information includes location information (e.g., "5 minutes' walk from X station"), menu items (e.g., "pizza, salad, pasta"), and service details (e.g., "breakfast included").

[0482] Next, the user selects a writing style using drop-down menus or radio buttons provided on the device. The available writing styles include hotel manager, funky pop, chic restaurant, and innkeeper. The user's selected writing style information is also saved on the device.

[0483] The device compiles the input basic information and the selected writing style information into a single data package, usually in JSON format, and sends this data to the server as an HTTP request.

[0484] The server analyzes the request received from the device and extracts basic information and the selected writing style information. The server then selects the most appropriate generative AI model. For example, if a funky pop style writing style is selected, the server calls a funky pop style generative AI model. The server generates a plan or promotional text by providing the extracted information as input to the generative AI model.

[0485] An example of a generated plan or promotion statement is:

[0486] Basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 5 minutes' walk from XX Station."

[0487] Selected writing style: Innkeeper style

[0488] Generated plan: "Dear guest, we are a conveniently located inn, just a 5-minute walk from XX Station, and we offer a heart-warming Japanese breakfast. Please come and enjoy."

[0489] The server sends the generated text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the generated text, and displays it on the user interface. This allows the user to view the automatically generated text.

[0490] To implement this system, the following hardware and software are used:

[0491] Devices: Digital devices such as smartphones and head-mounted displays

[0492] Server: A computer system that manages and processes data.

[0493] Generative AI models, such as the OpenAI API for natural language generation

[0494] For example, to generate a funky pop style promotional text, the prompt text is:

[0495] Menu items: Pizza, Salad, Pasta

[0496] Delivery area: Shibuya Ward, Meguro Ward

[0497] Style: Funky Pop

[0498] Generate a promotional text:

[0499] This invention makes it possible to automatically generate plan texts or promotional texts in a variety of writing styles according to the needs of users, thereby maximizing the appeal of the services of accommodation facilities and food service establishments.

[0500] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0501] Step 1:

[0502] The user uses the device to input basic information about the accommodation or food service location. This information includes location information (e.g., "5 minutes' walk from X station"), menu items (e.g., "pizza, salad, pasta"), and service details (e.g., "breakfast included"). Based on this input, data is stored in the device.

[0503] Step 2:

[0504] Users can select a writing style using drop-down menus or radio buttons provided on the device. The available writing styles include hotel manager, funky pop, chic restaurant, and innkeeper. The writing style information selected by the user is also saved on the device.

[0505] Step 3:

[0506] The device compiles the input basic information and the selected writing style information into a single piece of data, usually packaged in a format such as JSON, and sends this data to the server as an HTTP request.

[0507] Step 4:

[0508] The server analyzes the request received from the terminal and extracts basic information and selected writing style information. The data obtained from this analysis is stored internally on the server.

[0509] Step 5:

[0510] The server selects the most suitable AI model. For example, if a funky pop style is selected, the server calls a funky pop AI model. The data required for this selection are basic information and style information.

[0511] Step 6:

[0512] The server provides the extracted basic information and style information as input to the generative AI model. The generative AI model performs natural language processing based on this data to generate appropriate plan or promotional text. The generated text is stored internally on the server.

[0513] Step 7:

[0514] The server sends the generated plan or promotion text to the terminal as an HTTP response, which includes the generated text.

[0515] Step 8:

[0516] The terminal receives the response from the server, analyzes it, and extracts the generated text. The terminal displays the text on the user interface, allowing the user to view the automatically generated plan text or promotion text.

[0517] In this way, a series of processes is completed in which a plan or promotional text is automatically generated using a generative AI model based on the basic information entered by the user and the writing style selected, and the results are displayed on the terminal.

[0518] 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.

[0519] This invention combines a system in which a user inputs basic information about an accommodation facility, selects a style of plan proposal from multiple styles, and automatically generates plan text using an AI model, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0520] Enter basic information

[0521] First, the user inputs basic information about the accommodation into the terminal, including location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). The terminal stores this information and provides real-time feedback to the user as needed (e.g., displays error messages for input errors or incomplete information).

[0522] Character Selection

[0523] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. The device confirms the user's selection and also saves this information.

[0524] Emotion Engine Operation

[0525] The device is equipped with an emotion engine that recognizes the user's emotions. The emotion engine estimates the user's emotions based on the user's input and interactions, such as keyboard typing speed and mouse movements, as well as facial recognition and voice analysis. This emotion information is used to generate the plan text.

[0526] Submitting a plan generation request

[0527] The device compiles the basic information entered by the user, the selected writing style, and the estimated emotion information into a single data set. This data is usually packaged in a format such as JSON. The device then sends this data to the server as an HTTP request.

[0528] Plan Generation Process

[0529] The server analyzes the request received from the device and extracts basic information about the accommodation facility, the selected writing style, and emotional information. The server then selects the optimal generative AI model. For example, if a writing style in the style of a female innkeeper is selected, the server calls the generative AI model in the style of a female innkeeper. The server generates a plan text by providing the extracted information as input to the AI ​​model. At this time, the tone and expression of the text are adjusted based on the emotional information.

[0530] Submitting and Viewing Generated Plans

[0531] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0532] Specific examples

[0533] Specific examples are shown below.

[0534] 1. The user enters the basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 10 minutes' walk from Kyoto Station."

[0535] 2. The user selects the character "Innkeeper."

[0536] 3. The device uses an emotion engine to estimate the user's emotion as "excited."

[0537] 4. The device sends the information to the server.

[0538] 5. The server generates a plan document using a generative AI model based on the information.

[0539] Generated plan example: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0540] 6. The server sends the generated plan document to the terminal.

[0541] 7. The terminal displays the plan text to the user.

[0542] Displayed text: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0543] As described above, this system can generate a variety of plan sentences that correspond to the user's emotions, which can be used to attract customers to accommodation facilities.

[0544] The processing flow will be explained below.

[0545] Step 1:

[0546] The user enters basic information about the accommodation into the terminal. Specifically, the user enters information about the location (e.g., "10 minutes' walk from Kyoto Station") and meal details (e.g., "Japanese breakfast included") into the input form.

[0547] Step 2:

[0548] The user selects the style of the plan proposal from the UI on the device. The options include three styles: hotel manager style, gyaru style, and inn proprietress style. The user clicks or taps the appropriate option.

[0549] Step 3:

[0550] The device compiles the basic information entered by the user and the selected writing style, and the compiled data is usually structured in JSON format.

[0551] Step 4:

[0552] The emotion engine built into the device analyzes the user's input and interactions (e.g., keyboard input speed, mouse movement, face recognition, voice analysis) to estimate the user's emotion. This estimated emotion information is added to the data.

[0553] Step 5:

[0554] The device sends structured JSON data to the server as an HTTP POST request, which includes the input basic information, the selected writing style, and the estimated emotion information.

[0555] Step 6:

[0556] The server analyzes the request received from the terminal, specifically extracting basic information about the accommodation, the selected writing style, and sentiment information from the request.

[0557] Step 7:

[0558] The server selects an appropriate AI model based on the selected writing style. For example, if the writing style is "innkeeper-style," the server selects an AI model that is in the innkeeper-style.

[0559] Step 8:

[0560] The server inputs the extracted basic information, stylistic information, and emotional information into a generative AI model to generate a plan sentence. The tone and expression of the generated sentence are adjusted based on the emotional information.

[0561] Step 9:

[0562] The server structures the generated plan text in JSON format and sends it to the terminal as an HTTP response.

[0563] Step 10:

[0564] The device receives the response from the server and analyzes the plan text. Specifically, it extracts the plan text from the JSON data.

[0565] Step 11:

[0566] The terminal displays the extracted plan sentence to the user, so that the user can confirm the generated plan sentence.

[0567] Example 2

[0568] 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."

[0569] Conventional accommodation plan proposal systems have difficulty generating flexible proposal text that reflects the user's emotions and preferences. Furthermore, the style of the proposal text is fixed, and users cannot choose from a variety of styles, making it difficult to attract their interest. Furthermore, because the automatic generation of plan text does not take the user's emotions into consideration, the proposal content can sometimes lack consistency.

[0570] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting basic information about accommodation facilities, a means for selecting a style of plan proposal from among a plurality of distinctive writing styles, a generation device means for generating a plan text based on the input basic information about accommodation facilities, the selected writing style, and emotional information, and a means for displaying the generated plan text. This makes it possible to generate a variety of plan texts according to the user's emotions and to help attract customers to accommodation facilities.

[0571] "Basic information about accommodation facilities" refers to key information about accommodation facilities, such as location information and meal contents.

[0572] "Plan proposal writing style" refers to the style and tone of expression in the plan text, and includes three types, for example, hotel manager style, gal style, and inn proprietress style.

[0573] "Emotional information" is information that indicates the user's emotional state and is estimated based on keyboard typing speed, facial recognition, voice analysis, etc.

[0574] The "generation device means" refers to a device or program for generating a plan text based on basic information about the accommodation facility, the selected style and emotion information.

[0575] A "generative AI model" refers to an artificial intelligence model that generates sentences based on input information, and is used to create appropriate sentences based on style and emotion.

[0576] "Display means" refers to means for displaying the generated plan text on the screen or display of a terminal so that the user can check it.

[0577] An "HTTP request" refers to a protocol-based communication method by which a client (here, a terminal) requests data or processing from a server.

[0578] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight data exchange format for structuring, storing, and transferring data.

[0579] This invention combines a system in which a user inputs basic information about an accommodation facility, selects a style of plan proposal from multiple styles, and automatically generates plan text using an AI model, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0580] First, the user enters basic information about the accommodation into the terminal. For example, basic information about the accommodation may include information such as "10 minutes' walk from Kyoto Station, Japanese breakfast included." The terminal temporarily stores the information entered by the user and displays an error message if the information is incomplete or there is an input error. This process of entering basic information allows the user to receive feedback in real time.

[0581] Next, the user selects the style of the plan proposal from the options provided on the device (drop-down menu or radio button). The style can be selected from "Hotel Manager Style," "Gyaru Style," or "Innkeeper Style." The device confirms the selected style and saves this information.

[0582] Furthermore, the device is equipped with an emotion engine that recognizes the user's emotions. This emotion recognition uses functions such as keyboard input speed, face recognition, and voice analysis. For example, if the user types quickly or smiles, it is estimated that the user is "excited." This emotion information is used when generating plan sentences.

[0583] The device combines basic information, the selected writing style, and estimated emotion information into a single package in JSON format, which is then sent to the server as an HTTP request. For example, the prompt text might look like this:

[0584] {

[0585] "Basic Information": "10 minutes walk from Kyoto Station, Japanese breakfast included",

[0586] "Style": "Innkeeper style",

[0587] "Emotion": "Excited"

[0588] }

[0589] The server receives the request sent from the device and analyzes the JSON data. Based on the analyzed information, it selects the most appropriate generative AI model. For example, if "innkeeper style" is selected as the writing style, the innkeeper style generative AI model is called. The server then inputs the information into the AI ​​model and generates a plan sentence. At this time, the tone and expression of the sentence are adjusted based on the emotional information.

[0590] The generated plan text is sent to the terminal as an HTTP response. The terminal receives the response, analyzes it, extracts the plan text, and displays it on the user interface. The user can check the automatically generated plan text in real time.

[0591] As a specific example, if a user inputs "a ryokan (Japanese inn) with a Japanese breakfast, a 10-minute walk from Kyoto Station," selects "ryokan proprietress" as the writing style, and the emotion engine estimates that the user is "excited," the server will generate a plan sentence such as "Hello! We are offering a heart-warming Japanese breakfast at a ryokan conveniently located a 10-minute walk from Kyoto Station. We hope you have a wonderful time!" The device will display this sentence to the user, allowing the user to confirm its contents.

[0592] As described above, this system generates and provides a variety of plan texts that take emotions into consideration in order to increase the user's satisfaction with accommodation proposals.

[0593] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0594] Step 1:

[0595] The user enters basic information.

[0596] Input: The user enters basic information about the accommodation, such as "10 minutes walk from Kyoto Station, Japanese breakfast included."

[0597] Data processing: The terminal temporarily stores the input data and checks the input contents of each field.

[0598] Output: The basic information entered by the user is saved and an error message is displayed if the information is incomplete or contains a typo.

[0599] What happens: The device may display the error message "Breakfast type not entered."

[0600] Step 2:

[0601] The user selects the style of the plan proposal.

[0602] Input: The user selects one of three writing styles: "Hotel manager style," "Gyaru style," and "Innkeeper style."

[0603] Data processing: The device saves the selected writing style.

[0604] Output: The selected writing style is saved to the terminal for the next processing step.

[0605] Specific behavior: The user selects "Innkeeper Style" using the radio button.

[0606] Step 3:

[0607] The device's emotion engine recognizes the user's emotions.

[0608] Input: User input and interaction (keyboard typing speed, facial recognition, voice analysis, etc.)

[0609] Data processing: The device's emotion engine analyzes these input data and estimates the user's emotions.

[0610] Output: Estimated emotion information (e.g., "excited")

[0611] Specific behavior: The device uses the camera to scan the user's face, detects a smile, and infers that the user is "excited."

[0612] Step 4:

[0613] The terminal sends a plan generation request to the server.

[0614] Input: Basic information, selected writing style, estimated sentiment information

[0615] Data processing: The device packages this information in JSON format.

[0616] Output: Sends the packaged JSON data to the server as an HTTP request.

[0617] Specific operation: The device sends the following data in JSON format: "10 minutes walk from Kyoto Station, Japanese breakfast included," "Landlady-like inn," and "Excited."

[0618] Step 5:

[0619] The server performs the plan generation process.

[0620] Input: JSON data sent from the terminal

[0621] Data processing: The server parses the JSON data and extracts basic information, selected writing style, and sentiment information. It then selects the optimal generative AI model and inputs the extracted information into the AI ​​model.

[0622] Output: Generated plan text (e.g., "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!")

[0623] Specific operation: The server selects the "ryokan proprietress-style" generation AI model, and generates a plan text by inputting the information "10 minutes' walk from Kyoto Station, Japanese breakfast included" and "Excited."

[0624] Step 6:

[0625] The server sends the generated plan text to the terminal.

[0626] Input: Generated plan document

[0627] Data processing: The server packages the generated plan document into an HTTP response.

[0628] Output: Sent to the device as an HTTP response.

[0629] Specific operation: The server sends the generated plan document to the terminal as an HTTP response.

[0630] Step 7:

[0631] The terminal displays the generated plan text.

[0632] Input: HTTP response received from the server

[0633] Data processing: The terminal analyzes the response and extracts the plan text.

[0634] Output: The plan text is displayed in the user interface.

[0635] What it does: The device displays the following text: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station, and we offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0636] (Application example 2)

[0637] 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."

[0638] Conventional generation systems generate text without considering the user's emotions, making them unable to flexibly respond to individual needs. It is also difficult to generate text with an appropriate tone for specific situations and emotions. In particular, when generating equipment inspection reports for factory robots, reports are provided that ignore the user's emotions, which can lead to problems in effectively conveying necessary information.

[0639] 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.

[0640] In this invention, the server is equipped with an emotion engine that recognizes the user's emotions, and includes means for adjusting the tone and expression of the text based on the analyzed emotion information, means for generating a plan text based on a style selected from three styles: formal, casual, and technical terminology, and means for calling a generation AI model based on the user's input and the analyzed emotion information to generate the plan text. This enables more individualized and effective text generation that is in line with the user's emotions.

[0641] "Basic information about accommodation facility" is data that allows the user to input details about the accommodation facility, including location information, meal details, and the like.

[0642] The "plan proposal writing style" is selected from among several distinctive styles of expression, and is a factor that determines the tone and atmosphere of the generated text.

[0643] "Generation device means" refers to a device for automatically generating sentences using a generative AI model based on basic information entered by a user and a selected writing style.

[0644] The "emotion engine" is an engine that analyzes the user's facial expressions and voice to recognize emotions, and adjusts the tone and expression of the text based on that information.

[0645] A "formal style" is a style that emphasizes formality and courtesy and is used in formal settings, and is suitable for official documents.

[0646] "Casual writing style" is a writing style that is everyday and familiar, and uses informal and simple expressions.

[0647] A "technical jargon style" is a style that includes many specialized terms and expressions used in a particular technical field, and is aimed at engineers and specialists.

[0648] A "generative AI model" is an artificial intelligence model used to generate appropriate sentences based on input data, and creates sentences using a learning algorithm.

[0649] This invention is a system that combines an emotion engine that recognizes the user's emotions with a system that allows a user to input basic information about an accommodation facility, select a suggested writing style from multiple distinctive writing styles, and automatically generate a plan document using an AI model. A specific embodiment of this system will be described below.

[0650] First, the user inputs basic information about the accommodation facility into the terminal. This basic information includes data such as "Cooling system within the factory, east side of the second factory, inspection details: check for abnormal fan noise." This information is input using an interface such as a keyboard or touch screen.

[0651] Next, the user selects the style of the inspection report from options provided on the device: formal, casual, or technical.

[0652] The device has a built-in emotion engine that recognizes the user's emotions. This emotion engine captures the user's facial expressions and voice using a camera and microphone, and estimates the user's emotions using emotion analysis software (e.g., Affectiva SDK). The estimated emotion information is then used to adjust the tone and expression of the generated text.

[0653] The emotional information collected by the emotion engine, the basic information entered by the user, and the selected writing style are packaged in JSON format and sent to the server as an HTTP request. The server receives this request and analyzes the request. The analysis involves using a programming language such as Python to input the data into a generative AI model (e.g., OpenAI GPT-3).

[0654] The server selects the most appropriate generative AI model based on the received content. For example, if a technical terminology style is selected, a generative AI model that matches that style will be called up. The generative AI model receives the prompt "Cooling system inside the factory, east side of the second factory, inspection content: check for abnormal fan noise" and generates an inspection report in the appropriate tone.

[0655] Here are some examples of prompts:

[0656] Cooling system inside the factory, east side of the second factory, inspection content: Check for abnormal fan noise

[0657] The generated inspection report may have the following format, for example: "Inspection results for the cooling system: An abnormal noise was detected from the cooling fan located on the east side of the second factory. Worn fan blades and deterioration of bearings were observed. Immediate replacement is recommended."

[0658] The generated report is sent from the server to the terminal as an HTTP response. The terminal receives this report and displays it on the user interface, allowing the user to check the automatically generated inspection report.

[0659] This system enables flexible responses based on the user's emotions, and is expected to effectively convey necessary information, particularly when generating equipment inspection reports for factory robots.

[0660] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0661] Step 1:

[0662] The user inputs basic information about the accommodation facility or factory equipment into the terminal. This basic information may include, for example, "Cooling system within the factory, east side of the second factory, inspection details: check for abnormal fan noise." This input information is stored in the terminal's memory and feedback is provided to the user in real time. The input data format is specified in JSON format or similar.

[0663] Step 2:

[0664] The user selects a writing style from the options provided on the device. There are three writing styles to choose from: formal, casual, and technical. This selection is saved on the device. For example, if "technical" is selected, that information will be used in the next step.

[0665] Step 3:

[0666] The device's built-in emotion engine analyzes the user's emotions. It captures the user's facial expressions and voice using a camera and microphone, and uses emotion analysis software (e.g., Affectiva SDK) to estimate emotional information. This emotional information is also stored on the device. The analyzed emotional information may include, for example, "I'm nervous."

[0667] Step 4:

[0668] The device will then compile the input basic information, the selected writing style, and the analyzed emotional information into a single data package. The package data will be in JSON format, and will look something like this:

[0669] {

[0670] "facility_info": "Factory cooling system, east side of Factory 2, inspection details: check for abnormal fan noise",

[0671] "selected_tone": "Technical jargon style",

[0672] "user_emotion": "I'm nervous"

[0673] }

[0674] This data is sent to the server as an HTTP request.

[0675] Step 5:

[0676] The server receives the data package sent from the client, analyzes the received data, and extracts basic information, selected writing style, and sentiment information separately.

[0677] Step 6:

[0678] The server selects the most appropriate generative AI model (e.g., OpenAI GPT-3) based on the analyzed data. For example, if "technical terminology style" is selected, the server calls the corresponding generative AI model. The extracted basic information, the selected style, and the emotional information are provided as input data to the called generative AI model.

[0679] Step 7:

[0680] The generative AI model generates a plan sentence based on the input data. The tone and expression of the sentence are adjusted based on the emotional information. For example, the generated plan sentence might be in the following format: "Inspection results for the cooling system: An abnormal noise was detected from the cooling fan located on the east side of the second factory. Wear on the fan blades and deterioration of the bearings were observed. Prompt replacement is recommended."

[0681] Step 8:

[0682] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives this response and displays the generated plan text on the user interface. As a result, the user can check the automatically generated appropriate plan text.

[0683] 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.

[0684] 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.

[0685] 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.

[0686] [Third embodiment]

[0687] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0688] 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.

[0689] 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).

[0690] 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.

[0691] 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.

[0692] 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).

[0693] 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.

[0694] 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.

[0695] 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.

[0696] 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.

[0697] 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.

[0698] 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."

[0699] This invention is a system that allows a user to input basic information about accommodations, select a style for the proposed plan from multiple styles, and automatically generate a plan document using an AI model. Specific embodiments of this system are described below.

[0700] Enter basic information

[0701] First, the user inputs basic information about the accommodation into the terminal, including location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). The terminal stores this information and provides real-time feedback to the user as needed (e.g., displays error messages for input errors or incomplete information).

[0702] Character Selection

[0703] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. The device confirms the user's selection and also saves this information.

[0704] Submitting a plan generation request

[0705] The terminal compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set, usually packaged in a format such as JSON, and sends this data to the server as an HTTP request.

[0706] Plan Generation Process

[0707] The server analyzes the request received from the terminal and extracts basic information about the accommodation facility and the selected writing style information. The server selects the most suitable generation AI model. For example, if a writing style in the style of a female innkeeper is selected, the server calls the generation AI model in the style of a female innkeeper. The server generates a plan text by providing the extracted information as input to the AI ​​model. Examples of generated plans include the following:

[0708] Basic information: "A 5-minute walk from Tokyo Station, this inn offers a Japanese breakfast."

[0709] Selected writing style: Innkeeper

[0710] Generated plan: "Dear guest, we are conveniently located just a 5-minute walk from Kyoto Station and offer a heart-warming Japanese breakfast. Please come and enjoy."

[0711] Submitting and Viewing Generated Plans

[0712] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0713] Specific examples

[0714] Specific examples are shown below.

[0715] 1. The user enters the basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 10 minutes' walk from Kyoto Station."

[0716] 2. The user selects the character "Innkeeper."

[0717] 3. The device sends the information to the server.

[0718] 4. The server generates a plan document using a generative AI model based on the information.

[0719] Generated plan example: "Dear guest, we are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a heart-warming Japanese breakfast. Please come and enjoy."

[0720] 5. The server sends the generated plan document to the terminal.

[0721] 6. The terminal displays the plan text to the user.

[0722] Displayed text: "Dear guest, we are conveniently located just a 10-minute walk from Kyoto Station, and we offer a heart-warming Japanese breakfast. Please come and enjoy."

[0723] As described above, this system allows users to easily generate a variety of plan documents and use them to attract customers to accommodation facilities.

[0724] The processing flow will be explained below.

[0725] Step 1:

[0726] The user enters basic information about the accommodation into the terminal. Specifically, the user enters location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included") into an input form.

[0727] Step 2:

[0728] The user selects the style of the plan proposal from the UI on the device. The options include three styles: hotel manager style, gyaru style, and inn proprietress style. The user clicks or taps the appropriate option.

[0729] Step 3:

[0730] The device compiles the basic information entered by the user and the selected writing style, and the compiled data is usually structured in JSON format.

[0731] Step 4:

[0732] The device sends structured JSON data to the server as an HTTP POST request, which includes the basic information entered and the selected writing style.

[0733] Step 5:

[0734] The server analyzes the request received from the terminal, specifically extracting basic information about the accommodation and the selected writing style information from the request.

[0735] Step 6:

[0736] The server selects an appropriate AI model based on the selected writing style. For example, if the writing style is "innkeeper-style," the server selects an AI model that is in the innkeeper-style.

[0737] Step 7:

[0738] The server inputs the extracted basic information and stylistic information into a generative AI model to generate a plan sentence. The generated sentence is automatically created based on the input information.

[0739] Step 8:

[0740] The server structures the generated plan text in JSON format and sends it to the terminal as an HTTP response.

[0741] Step 9:

[0742] The device receives the response from the server and analyzes the plan text. Specifically, it extracts the plan text from the JSON data.

[0743] Step 10:

[0744] The terminal displays the extracted plan sentence to the user, so that the user can confirm the generated plan sentence.

[0745] Example 1

[0746] 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."

[0747] In conventional accommodation plan proposal systems, users had to spend a great deal of time and effort creating detailed plan documents. It was also difficult to generate plan documents using different writing styles, and many aspects relied on manual work, making it difficult to ensure consistency and quality. Furthermore, there were problems with sending incorrect information due to insufficient verification of input information and a lack of user feedback.

[0748] 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.

[0749] In this invention, the server includes means for inputting basic information about accommodations, means for selecting a style for a plan proposal from a plurality of distinctive styles, generator means for generating a plan document based on the input basic information about accommodations and the selected style, means for displaying the generated plan document, means for verifying and providing feedback on the input basic information, means for packaging the input basic information and style information, and means for transmitting the packaged data to the server, thereby enabling users to automatically generate high-quality, consistent plan documents while saving time and effort.

[0750] "Basic information about accommodation facilities" is detailed information that serves as a criterion when a user selects accommodation facilities, such as the location of the accommodation facility, meal contents, and room facilities.

[0751] "Writing style" refers to the particular wording and expression used in the proposal text, and is selected based on the user's desired style.

[0752] The "generation device means" is a device or software that automatically generates a plan text based on the input basic information and selected style information.

[0753] "Validation and feedback measures" are functions that check the information entered by the user to detect errors or incompleteness, and provide the user with suggested corrections or error messages in real time.

[0754] A "packaging means" is a method or device that combines different information (for example, basic information and stylistic information) into a single data unit, and is used to maintain data consistency.

[0755] The "means for transmitting to the server" is a process or device that sends the packaged data to the server over a network.

[0756] A "generative AI model" is an artificial intelligence algorithm or software that automatically generates text based on input data.

[0757] "User interface" refers to the screens and input devices that allow the system and the user to exchange information with each other.

[0758] This invention is a system that allows a user to input basic information about accommodations, select a style for the proposed plan from multiple styles, and automatically generate a plan document using an AI model. Specific embodiments of this system are described below.

[0759] Enter basic information

[0760] First, the user enters basic information about the accommodation into the terminal. The basic information about the accommodation includes location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). For example, let's say the user enters "a ryokan (Japanese inn) that is a 10-minute walk from Kyoto Station and serves a Japanese breakfast." The terminal immediately verifies this information and displays an error message in real time for any input errors or incomplete information. The verified basic information is saved in local storage.

[0761] Character Selection

[0762] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. When the user selects "innkeeper style," the device saves this information and notifies the user that the selection is complete.

[0763] Submitting a plan generation request

[0764] The terminal compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set. This data is usually packaged in a format such as JSON, but an example of a specific prompt sentence would be as follows:

[0765] Basic information: "A 10-minute walk from Kyoto Station, this inn offers a Japanese breakfast."

[0766] Selected writing style: Innkeeper

[0767] The device sends this data to the server as an HTTP request.

[0768] Plan Generation Process

[0769] The server analyzes the request received from the device and extracts basic information about the accommodation and the selected writing style. The server then selects the most appropriate generative AI model. For example, if the "style of a landlady at an inn" is selected, the server calls the generative AI model for a landlady at an inn. Specifically, the following generative AI models are used:

[0770] Generative AI models: large-scale generative models such as GPT-3

[0771] The server inputs the extracted information into the AI ​​model and generates a plan. For example, if a user selects the basic information "a 10-minute walk from Kyoto Station, a Japanese-style inn with breakfast" and the writing style "the inn's landlady," the following example plan is generated:

[0772] "Dear guest, we are a conveniently located inn, just a 10-minute walk from Kyoto Station, and we offer a heart-warming Japanese breakfast. Please feel free to come and enjoy."

[0773] Submitting and Viewing Generated Plans

[0774] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0775] Using this system, users can easily generate a variety of plan documents and use them to attract customers to their accommodations.

[0776] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0777] Step 1:

[0778] The user enters basic information about the accommodation into the terminal. For example, they might enter information such as "a hotel with breakfast included, a five-minute walk from Tokyo Station." The terminal receives this information and verifies in real time whether the input is in the correct format. Specifically, if required fields are not filled in, an error message is displayed. If the input information is correct, the terminal saves the basic information in local storage. Input is in text format, and the output is the verified basic information.

[0779] Step 2:

[0780] The user selects the writing style of the plan proposal from a drop-down menu or radio buttons provided on the terminal screen. For example, the user selects the writing style of "the proprietress of a ryokan." The terminal receives this selection, confirms the user's selection, and saves it. Specifically, it displays a notification to the user that the selection is complete. The input is the selection of writing style, and the output is the selected writing style information.

[0781] Step 3:

[0782] The device compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set, and then packages this data in JSON format. For example, the following JSON data is generated:

[0783] json

[0784] {

[0785] "basic_info": "Hotel with breakfast, 5 minutes walk from Tokyo Station",

[0786] "style": "Innkeeper"

[0787] }

[0788] The terminal sends this JSON data to the server as an HTTP request. The input is basic information and style information, and the output is packaged JSON data.

[0789] Step 4:

[0790] The server analyzes the HTTP request received from the terminal. It deserializes the received data and extracts basic information about the accommodation and stylistic information. For example, extract "Hotel with breakfast, 5 minutes' walk from Tokyo Station" and "Proprietress of the inn" from the received data. The input is JSON data, and the output is the extracted basic information and stylistic information.

[0791] Step 5:

[0792] The server selects the optimal generative AI model based on the extracted information. For example, if the writing style of "innkeeper" is selected, the corresponding generative AI model is loaded. The server inputs basic information and writing style information into the generative AI model and generates a plan sentence. The specific input is the basic information "A hotel with breakfast, a five-minute walk from Tokyo Station" and the writing style information "Innkeeper", and the output is the plan sentence "Dear customer, we are a conveniently located hotel, a five-minute walk from Tokyo Station, and breakfast is available. Please feel free to use it."

[0793] Step 6:

[0794] The server packages the generated plan document and sends it as an HTTP response to the terminal. The input is the generated plan document and the output is the HTTP response.

[0795] Step 7:

[0796] The terminal receives the HTTP response from the server and analyzes the received data. It extracts the plan text and displays it on the user interface. The user can then view and confirm the generated plan text. Specifically, the user sees the text on the screen: "Dear customer, we are offering breakfast at a hotel conveniently located a five-minute walk from Tokyo Station. Please feel free to enjoy it." The input is the HTTP response data, and the output is the displayed plan text.

[0797] (Application example 1)

[0798] 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."

[0799] Conventional accommodation plan proposal systems could only make proposals using a fixed style, making it difficult to generate promotional text that flexibly reflects the individual needs of users and the characteristics of the facility. Furthermore, there was no means of automatically generating flexible and effective promotional text for other service types, such as food delivery services. Therefore, there is a need for an effective way to convey the appeal of facilities and services to the fullest extent.

[0800] 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.

[0801] In this invention, the server includes a means for inputting basic information about accommodations or food service locations, a means for selecting a style for the plan proposal or promotional text from a plurality of distinctive styles, and a generator means for generating plan text or promotional text based on the input basic information and the selected style, thereby enabling the automatic generation of plan text or promotional text in a flexible and diverse style that meets the needs of users.

[0802] "Accommodation facilities" refers to all facilities that provide accommodation services, and specifically includes hotels, inns, private lodgings, guest houses, etc.

[0803] "Food service location" refers to any facility that serves food and beverages, including restaurants, cafes, and food delivery services.

[0804] "Basic information" refers to information about the characteristics and service details of accommodations and food service locations, and specifically includes location, menu items, service details, price range, etc.

[0805] "Writing style" refers to the style of expression used when creating plan documents and promotional texts, and specifically includes hotel manager style, funky pop style, chic restaurant style, inn proprietress style, etc.

[0806] "Plan proposal" refers to a document proposing the services and benefits of accommodations and food establishments to customers.

[0807] "Promotional text" refers to text created to effectively advertise the services and menus of food service establishments, etc.

[0808] The "generation device means" refers to a device having the function of automatically generating a plan text or promotional text based on the input basic information and the selected writing style.

[0809] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates appropriate sentences based on input data.

[0810] The term "server" refers to a computer system that manages and processes data, and in the present invention is a central device that is responsible for generating plan documents and promotional documents.

[0811] The present invention is a system that inputs basic information about accommodations or food service locations, selects a style of plan proposal or promotional text from multiple distinctive styles, and automatically generates text using a generative AI model. One specific embodiment of the present invention is described below.

[0812] First, the user uses a device (such as a smartphone or head-mounted display) to input basic information about the accommodation or food service location. This information includes location information (e.g., "5 minutes' walk from X station"), menu items (e.g., "pizza, salad, pasta"), and service details (e.g., "breakfast included").

[0813] Next, the user selects a writing style using drop-down menus or radio buttons provided on the device. The available writing styles include hotel manager, funky pop, chic restaurant, and innkeeper. The user's selected writing style information is also saved on the device.

[0814] The device compiles the input basic information and the selected writing style information into a single data package, usually in JSON format, and sends this data to the server as an HTTP request.

[0815] The server analyzes the request received from the device and extracts basic information and the selected writing style information. The server then selects the most appropriate generative AI model. For example, if a funky pop style writing style is selected, the server calls a funky pop style generative AI model. The server generates a plan or promotional text by providing the extracted information as input to the generative AI model.

[0816] An example of a generated plan or promotion statement is:

[0817] Basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 5 minutes' walk from XX Station."

[0818] Selected writing style: Innkeeper style

[0819] Generated plan: "Dear guest, we are a conveniently located inn, just a 5-minute walk from XX Station, and we offer a heart-warming Japanese breakfast. Please come and enjoy."

[0820] The server sends the generated text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the generated text, and displays it on the user interface. This allows the user to view the automatically generated text.

[0821] To implement this system, the following hardware and software are used:

[0822] Devices: Digital devices such as smartphones and head-mounted displays

[0823] Server: A computer system that manages and processes data.

[0824] Generative AI models, such as the OpenAI API for natural language generation

[0825] For example, to generate a funky pop style promotional text, the prompt text is:

[0826] Menu items: Pizza, Salad, Pasta

[0827] Delivery area: Shibuya Ward, Meguro Ward

[0828] Style: Funky Pop

[0829] Generate a promotional text:

[0830] This invention makes it possible to automatically generate plan texts or promotional texts in a variety of writing styles according to the needs of users, thereby maximizing the appeal of the services of accommodation facilities and food service establishments.

[0831] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0832] Step 1:

[0833] The user uses the device to input basic information about the accommodation or food service location. This information includes location information (e.g., "5 minutes' walk from X station"), menu items (e.g., "pizza, salad, pasta"), and service details (e.g., "breakfast included"). Based on this input, data is stored in the device.

[0834] Step 2:

[0835] Users can select a writing style using drop-down menus or radio buttons provided on the device. The available writing styles include hotel manager, funky pop, chic restaurant, and innkeeper. The writing style information selected by the user is also saved on the device.

[0836] Step 3:

[0837] The device compiles the input basic information and the selected writing style information into a single piece of data, usually packaged in a format such as JSON, and sends this data to the server as an HTTP request.

[0838] Step 4:

[0839] The server analyzes the request received from the terminal and extracts basic information and selected writing style information. The data obtained from this analysis is stored internally on the server.

[0840] Step 5:

[0841] The server selects the most suitable AI model. For example, if a funky pop style is selected, the server calls a funky pop AI model. The data required for this selection are basic information and style information.

[0842] Step 6:

[0843] The server provides the extracted basic information and style information as input to the generative AI model. The generative AI model performs natural language processing based on this data to generate appropriate plan or promotional text. The generated text is stored internally on the server.

[0844] Step 7:

[0845] The server sends the generated plan or promotion text to the terminal as an HTTP response, which includes the generated text.

[0846] Step 8:

[0847] The terminal receives the response from the server, analyzes it, and extracts the generated text. The terminal displays the text on the user interface, allowing the user to view the automatically generated plan text or promotion text.

[0848] In this way, a series of processes is completed in which a plan or promotional text is automatically generated using a generative AI model based on the basic information entered by the user and the writing style selected, and the results are displayed on the terminal.

[0849] 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.

[0850] This invention combines a system in which a user inputs basic information about an accommodation facility, selects a style of plan proposal from multiple styles, and automatically generates plan text using an AI model, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0851] Enter basic information

[0852] First, the user inputs basic information about the accommodation into the terminal, including location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). The terminal stores this information and provides real-time feedback to the user as needed (e.g., displays error messages for input errors or incomplete information).

[0853] Character Selection

[0854] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. The device confirms the user's selection and also saves this information.

[0855] Emotion Engine Operation

[0856] The device is equipped with an emotion engine that recognizes the user's emotions. The emotion engine estimates the user's emotions based on the user's input and interactions, such as keyboard typing speed and mouse movements, as well as facial recognition and voice analysis. This emotion information is used to generate the plan text.

[0857] Submitting a plan generation request

[0858] The device compiles the basic information entered by the user, the selected writing style, and the estimated emotion information into a single data set. This data is usually packaged in a format such as JSON. The device then sends this data to the server as an HTTP request.

[0859] Plan Generation Process

[0860] The server analyzes the request received from the device and extracts basic information about the accommodation facility, the selected writing style, and emotional information. The server then selects the optimal generative AI model. For example, if a writing style in the style of a female innkeeper is selected, the server calls the generative AI model in the style of a female innkeeper. The server generates a plan text by providing the extracted information as input to the AI ​​model. At this time, the tone and expression of the text are adjusted based on the emotional information.

[0861] Submitting and Viewing Generated Plans

[0862] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[0863] Specific examples

[0864] Specific examples are shown below.

[0865] 1. The user enters the basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 10 minutes' walk from Kyoto Station."

[0866] 2. The user selects the character "Innkeeper."

[0867] 3. The device uses an emotion engine to estimate the user's emotion as "excited."

[0868] 4. The device sends the information to the server.

[0869] 5. The server generates a plan document using a generative AI model based on the information.

[0870] Generated plan example: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0871] 6. The server sends the generated plan document to the terminal.

[0872] 7. The terminal displays the plan text to the user.

[0873] Displayed text: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0874] As described above, this system can generate a variety of plan sentences that correspond to the user's emotions, which can be used to attract customers to accommodation facilities.

[0875] The processing flow will be explained below.

[0876] Step 1:

[0877] The user enters basic information about the accommodation into the terminal. Specifically, the user enters information about the location (e.g., "10 minutes' walk from Kyoto Station") and meal details (e.g., "Japanese breakfast included") into the input form.

[0878] Step 2:

[0879] The user selects the style of the plan proposal from the UI on the device. The options include three styles: hotel manager style, gyaru style, and inn proprietress style. The user clicks or taps the appropriate option.

[0880] Step 3:

[0881] The device compiles the basic information entered by the user and the selected writing style, and the compiled data is usually structured in JSON format.

[0882] Step 4:

[0883] The emotion engine built into the device analyzes the user's input and interactions (e.g., keyboard input speed, mouse movement, face recognition, voice analysis) to estimate the user's emotion. This estimated emotion information is added to the data.

[0884] Step 5:

[0885] The device sends structured JSON data to the server as an HTTP POST request, which includes the input basic information, the selected writing style, and the estimated emotion information.

[0886] Step 6:

[0887] The server analyzes the request received from the terminal, specifically extracting basic information about the accommodation, the selected writing style, and sentiment information from the request.

[0888] Step 7:

[0889] The server selects an appropriate AI model based on the selected writing style. For example, if the writing style is "innkeeper-style," the server selects an AI model that is in the innkeeper-style.

[0890] Step 8:

[0891] The server inputs the extracted basic information, stylistic information, and emotional information into a generative AI model to generate a plan sentence. The tone and expression of the generated sentence are adjusted based on the emotional information.

[0892] Step 9:

[0893] The server structures the generated plan text in JSON format and sends it to the terminal as an HTTP response.

[0894] Step 10:

[0895] The device receives the response from the server and analyzes the plan text. Specifically, it extracts the plan text from the JSON data.

[0896] Step 11:

[0897] The terminal displays the extracted plan sentence to the user, so that the user can confirm the generated plan sentence.

[0898] Example 2

[0899] 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."

[0900] Conventional accommodation plan proposal systems have difficulty generating flexible proposal text that reflects the user's emotions and preferences. Furthermore, the style of the proposal text is fixed, and users cannot choose from a variety of styles, making it difficult to attract their interest. Furthermore, because the automatic generation of plan text does not take the user's emotions into consideration, the proposal content can sometimes lack consistency.

[0901] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting basic information about accommodation facilities, a means for selecting a style of plan proposal from among a plurality of distinctive writing styles, a generation device means for generating a plan text based on the input basic information about accommodation facilities, the selected writing style, and emotional information, and a means for displaying the generated plan text. This makes it possible to generate a variety of plan texts according to the user's emotions and to help attract customers to accommodation facilities.

[0902] "Basic information about accommodation facilities" refers to key information about accommodation facilities, such as location information and meal contents.

[0903] "Plan proposal writing style" refers to the style and tone of expression in the plan text, and includes three types, for example, hotel manager style, gal style, and inn proprietress style.

[0904] "Emotional information" is information that indicates the user's emotional state and is estimated based on keyboard typing speed, facial recognition, voice analysis, etc.

[0905] The "generation device means" refers to a device or program for generating a plan text based on basic information about the accommodation facility, the selected style and emotion information.

[0906] A "generative AI model" refers to an artificial intelligence model that generates sentences based on input information, and is used to create appropriate sentences based on style and emotion.

[0907] "Display means" refers to means for displaying the generated plan text on the screen or display of a terminal so that the user can check it.

[0908] An "HTTP request" refers to a protocol-based communication method by which a client (here, a terminal) requests data or processing from a server.

[0909] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight data exchange format for structuring, storing, and transferring data.

[0910] This invention combines a system in which a user inputs basic information about an accommodation facility, selects a style of plan proposal from multiple styles, and automatically generates plan text using an AI model, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0911] First, the user enters basic information about the accommodation into the terminal. For example, basic information about the accommodation may include information such as "10 minutes' walk from Kyoto Station, Japanese breakfast included." The terminal temporarily stores the information entered by the user and displays an error message if the information is incomplete or there is an input error. This process of entering basic information allows the user to receive feedback in real time.

[0912] Next, the user selects the style of the plan proposal from the options provided on the device (drop-down menu or radio button). The style can be selected from "Hotel Manager Style," "Gyaru Style," or "Innkeeper Style." The device confirms the selected style and saves this information.

[0913] Furthermore, the device is equipped with an emotion engine that recognizes the user's emotions. This emotion recognition uses functions such as keyboard input speed, face recognition, and voice analysis. For example, if the user types quickly or smiles, it is estimated that the user is "excited." This emotion information is used when generating plan sentences.

[0914] The device combines basic information, the selected writing style, and estimated emotion information into a single package in JSON format, which is then sent to the server as an HTTP request. For example, the prompt text might look like this:

[0915] {

[0916] "Basic Information": "10 minutes walk from Kyoto Station, Japanese breakfast included",

[0917] "Style": "Innkeeper style",

[0918] "Emotion": "Excited"

[0919] }

[0920] The server receives the request sent from the device and analyzes the JSON data. Based on the analyzed information, it selects the most appropriate generative AI model. For example, if "innkeeper style" is selected as the writing style, the innkeeper style generative AI model is called. The server then inputs the information into the AI ​​model and generates a plan sentence. At this time, the tone and expression of the sentence are adjusted based on the emotional information.

[0921] The generated plan text is sent to the terminal as an HTTP response. The terminal receives the response, analyzes it, extracts the plan text, and displays it on the user interface. The user can check the automatically generated plan text in real time.

[0922] As a specific example, if a user inputs "a ryokan (Japanese inn) with a Japanese breakfast, a 10-minute walk from Kyoto Station," selects "ryokan proprietress" as the writing style, and the emotion engine estimates that the user is "excited," the server will generate a plan sentence such as "Hello! We are offering a heart-warming Japanese breakfast at a ryokan conveniently located a 10-minute walk from Kyoto Station. We hope you have a wonderful time!" The device will display this sentence to the user, allowing the user to confirm its contents.

[0923] As described above, this system generates and provides a variety of plan texts that take emotions into consideration in order to increase the user's satisfaction with accommodation proposals.

[0924] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0925] Step 1:

[0926] The user enters basic information.

[0927] Input: The user enters basic information about the accommodation, such as "10 minutes walk from Kyoto Station, Japanese breakfast included."

[0928] Data processing: The terminal temporarily stores the input data and checks the input contents of each field.

[0929] Output: The basic information entered by the user is saved and an error message is displayed if the information is incomplete or contains a typo.

[0930] What happens: The device may display the error message "Breakfast type not entered."

[0931] Step 2:

[0932] The user selects the style of the plan proposal.

[0933] Input: The user selects one of three writing styles: "Hotel manager style," "Gyaru style," and "Innkeeper style."

[0934] Data processing: The device saves the selected writing style.

[0935] Output: The selected writing style is saved to the terminal for the next processing step.

[0936] Specific behavior: The user selects "Innkeeper Style" using the radio button.

[0937] Step 3:

[0938] The device's emotion engine recognizes the user's emotions.

[0939] Input: User input and interaction (keyboard typing speed, facial recognition, voice analysis, etc.)

[0940] Data processing: The device's emotion engine analyzes these input data and estimates the user's emotions.

[0941] Output: Estimated emotion information (e.g., "excited")

[0942] Specific behavior: The device uses the camera to scan the user's face, detects a smile, and infers that the user is "excited."

[0943] Step 4:

[0944] The terminal sends a plan generation request to the server.

[0945] Input: Basic information, selected writing style, estimated sentiment information

[0946] Data processing: The device packages this information in JSON format.

[0947] Output: Sends the packaged JSON data to the server as an HTTP request.

[0948] Specific operation: The device sends the following data in JSON format: "10 minutes walk from Kyoto Station, Japanese breakfast included," "Landlady-like inn," and "Excited."

[0949] Step 5:

[0950] The server performs the plan generation process.

[0951] Input: JSON data sent from the terminal

[0952] Data processing: The server parses the JSON data and extracts basic information, selected writing style, and sentiment information. It then selects the optimal generative AI model and inputs the extracted information into the AI ​​model.

[0953] Output: Generated plan text (e.g., "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!")

[0954] Specific operation: The server selects the "ryokan proprietress-style" generation AI model, and generates a plan text by inputting the information "10 minutes' walk from Kyoto Station, Japanese breakfast included" and "Excited."

[0955] Step 6:

[0956] The server sends the generated plan text to the terminal.

[0957] Input: Generated plan document

[0958] Data processing: The server packages the generated plan document into an HTTP response.

[0959] Output: Sent to the device as an HTTP response.

[0960] Specific operation: The server sends the generated plan document to the terminal as an HTTP response.

[0961] Step 7:

[0962] The terminal displays the generated plan text.

[0963] Input: HTTP response received from the server

[0964] Data processing: The terminal analyzes the response and extracts the plan text.

[0965] Output: The plan text is displayed in the user interface.

[0966] What it does: The device displays the following text: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station, and we offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[0967] (Application example 2)

[0968] 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."

[0969] Conventional generation systems generate text without considering the user's emotions, making them unable to flexibly respond to individual needs. It is also difficult to generate text with an appropriate tone for specific situations and emotions. In particular, when generating equipment inspection reports for factory robots, reports are provided that ignore the user's emotions, which can lead to problems in effectively conveying necessary information.

[0970] 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.

[0971] In this invention, the server is equipped with an emotion engine that recognizes the user's emotions, and includes means for adjusting the tone and expression of the text based on the analyzed emotion information, means for generating a plan text based on a style selected from three styles: formal, casual, and technical terminology, and means for calling a generation AI model based on the user's input and the analyzed emotion information to generate the plan text. This enables more individualized and effective text generation that is in line with the user's emotions.

[0972] "Basic information about accommodation facility" is data that allows the user to input details about the accommodation facility, including location information, meal details, and the like.

[0973] The "plan proposal writing style" is selected from among several distinctive styles of expression, and is a factor that determines the tone and atmosphere of the generated text.

[0974] "Generation device means" refers to a device for automatically generating sentences using a generative AI model based on basic information entered by a user and a selected writing style.

[0975] The "emotion engine" is an engine that analyzes the user's facial expressions and voice to recognize emotions, and adjusts the tone and expression of the text based on that information.

[0976] A "formal style" is a style that emphasizes formality and courtesy and is used in formal settings, and is suitable for official documents.

[0977] "Casual writing style" is a writing style that is everyday and familiar, and uses informal and simple expressions.

[0978] A "technical jargon style" is a style that includes many specialized terms and expressions used in a particular technical field, and is aimed at engineers and specialists.

[0979] A "generative AI model" is an artificial intelligence model used to generate appropriate sentences based on input data, and creates sentences using a learning algorithm.

[0980] This invention is a system that combines an emotion engine that recognizes the user's emotions with a system that allows a user to input basic information about an accommodation facility, select a suggested writing style from multiple distinctive writing styles, and automatically generate a plan document using an AI model. A specific embodiment of this system will be described below.

[0981] First, the user inputs basic information about the accommodation facility into the terminal. This basic information includes data such as "Cooling system within the factory, east side of the second factory, inspection details: check for abnormal fan noise." This information is input using an interface such as a keyboard or touch screen.

[0982] Next, the user selects the style of the inspection report from options provided on the device: formal, casual, or technical.

[0983] The device has a built-in emotion engine that recognizes the user's emotions. This emotion engine captures the user's facial expressions and voice using a camera and microphone, and estimates the user's emotions using emotion analysis software (e.g., Affectiva SDK). The estimated emotion information is then used to adjust the tone and expression of the generated text.

[0984] The emotional information collected by the emotion engine, the basic information entered by the user, and the selected writing style are packaged in JSON format and sent to the server as an HTTP request. The server receives this request and analyzes the request. The analysis involves using a programming language such as Python to input the data into a generative AI model (e.g., OpenAI GPT-3).

[0985] The server selects the most appropriate generative AI model based on the received content. For example, if a technical terminology style is selected, a generative AI model that matches that style will be called up. The generative AI model receives the prompt "Cooling system inside the factory, east side of the second factory, inspection content: check for abnormal fan noise" and generates an inspection report in the appropriate tone.

[0986] Here are some examples of prompts:

[0987] Cooling system inside the factory, east side of the second factory, inspection content: Check for abnormal fan noise

[0988] The generated inspection report may have the following format, for example: "Inspection results for the cooling system: An abnormal noise was detected from the cooling fan located on the east side of the second factory. Worn fan blades and deterioration of bearings were observed. Immediate replacement is recommended."

[0989] The generated report is sent from the server to the terminal as an HTTP response. The terminal receives this report and displays it on the user interface, allowing the user to check the automatically generated inspection report.

[0990] This system enables flexible responses based on the user's emotions, and is expected to effectively convey necessary information, particularly when generating equipment inspection reports for factory robots.

[0991] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0992] Step 1:

[0993] The user inputs basic information about the accommodation facility or factory equipment into the terminal. This basic information may include, for example, "Cooling system within the factory, east side of the second factory, inspection details: check for abnormal fan noise." This input information is stored in the terminal's memory and feedback is provided to the user in real time. The input data format is specified in JSON format or similar.

[0994] Step 2:

[0995] The user selects a writing style from the options provided on the device. There are three writing styles to choose from: formal, casual, and technical. This selection is saved on the device. For example, if "technical" is selected, that information will be used in the next step.

[0996] Step 3:

[0997] The device's built-in emotion engine analyzes the user's emotions. It captures the user's facial expressions and voice using a camera and microphone, and uses emotion analysis software (e.g., Affectiva SDK) to estimate emotional information. This emotional information is also stored on the device. The analyzed emotional information may include, for example, "I'm nervous."

[0998] Step 4:

[0999] The device will then compile the input basic information, the selected writing style, and the analyzed emotional information into a single data package. The package data will be in JSON format, and will look something like this:

[1000] {

[1001] "facility_info": "Factory cooling system, east side of Factory 2, inspection details: check for abnormal fan noise",

[1002] "selected_tone": "Technical jargon style",

[1003] "user_emotion": "I'm nervous"

[1004] }

[1005] This data is sent to the server as an HTTP request.

[1006] Step 5:

[1007] The server receives the data package sent from the client, analyzes the received data, and extracts basic information, selected writing style, and sentiment information separately.

[1008] Step 6:

[1009] The server selects the most appropriate generative AI model (e.g., OpenAI GPT-3) based on the analyzed data. For example, if "technical terminology style" is selected, the server calls the corresponding generative AI model. The extracted basic information, the selected style, and the emotional information are provided as input data to the called generative AI model.

[1010] Step 7:

[1011] The generative AI model generates a plan sentence based on the input data. The tone and expression of the sentence are adjusted based on the emotional information. For example, the generated plan sentence might be in the following format: "Inspection results for the cooling system: An abnormal noise was detected from the cooling fan located on the east side of the second factory. Wear on the fan blades and deterioration of the bearings were observed. Prompt replacement is recommended."

[1012] Step 8:

[1013] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives this response and displays the generated plan text on the user interface. As a result, the user can check the automatically generated appropriate plan text.

[1014] 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.

[1015] 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.

[1016] 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.

[1017] [Fourth embodiment]

[1018] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1019] 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.

[1020] 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).

[1021] 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.

[1022] 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.

[1023] 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).

[1024] 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.

[1025] 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.

[1026] 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.

[1027] 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.

[1028] 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.

[1029] 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.

[1030] 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."

[1031] This invention is a system that allows a user to input basic information about accommodations, select a style for the proposed plan from multiple styles, and automatically generate a plan document using an AI model. Specific embodiments of this system are described below.

[1032] Enter basic information

[1033] First, the user inputs basic information about the accommodation into the terminal, including location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). The terminal stores this information and provides real-time feedback to the user as needed (e.g., displays error messages for input errors or incomplete information).

[1034] Character Selection

[1035] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. The device confirms the user's selection and also saves this information.

[1036] Submitting a plan generation request

[1037] The terminal compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set, usually packaged in a format such as JSON, and sends this data to the server as an HTTP request.

[1038] Plan Generation Process

[1039] The server analyzes the request received from the terminal and extracts basic information about the accommodation facility and the selected writing style information. The server selects the most suitable generation AI model. For example, if a writing style in the style of a female innkeeper is selected, the server calls the generation AI model in the style of a female innkeeper. The server generates a plan text by providing the extracted information as input to the AI ​​model. Examples of generated plans include the following:

[1040] Basic information: "A 5-minute walk from Tokyo Station, this inn offers a Japanese breakfast."

[1041] Selected writing style: Innkeeper

[1042] Generated plan: "Dear guest, we are conveniently located just a 5-minute walk from Kyoto Station and offer a heart-warming Japanese breakfast. Please come and enjoy."

[1043] Submitting and Viewing Generated Plans

[1044] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[1045] Specific examples

[1046] Specific examples are shown below.

[1047] 1. The user enters the basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 10 minutes' walk from Kyoto Station."

[1048] 2. The user selects the character "Innkeeper."

[1049] 3. The device sends the information to the server.

[1050] 4. The server generates a plan document using a generative AI model based on the information.

[1051] Generated plan example: "Dear guest, we are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a heart-warming Japanese breakfast. Please come and enjoy."

[1052] 5. The server sends the generated plan document to the terminal.

[1053] 6. The terminal displays the plan text to the user.

[1054] Displayed text: "Dear guest, we are conveniently located just a 10-minute walk from Kyoto Station, and we offer a heart-warming Japanese breakfast. Please come and enjoy."

[1055] As described above, this system allows users to easily generate a variety of plan documents and use them to attract customers to accommodation facilities.

[1056] The processing flow will be explained below.

[1057] Step 1:

[1058] The user enters basic information about the accommodation into the terminal. Specifically, the user enters location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included") into an input form.

[1059] Step 2:

[1060] The user selects the style of the plan proposal from the UI on the device. The options include three styles: hotel manager style, gyaru style, and inn proprietress style. The user clicks or taps the appropriate option.

[1061] Step 3:

[1062] The device compiles the basic information entered by the user and the selected writing style, and the compiled data is usually structured in JSON format.

[1063] Step 4:

[1064] The device sends structured JSON data to the server as an HTTP POST request, which includes the basic information entered and the selected writing style.

[1065] Step 5:

[1066] The server analyzes the request received from the terminal, specifically extracting basic information about the accommodation and the selected writing style information from the request.

[1067] Step 6:

[1068] The server selects an appropriate AI model based on the selected writing style. For example, if the writing style is "innkeeper-style," the server selects an AI model that is in the innkeeper-style.

[1069] Step 7:

[1070] The server inputs the extracted basic information and stylistic information into a generative AI model to generate a plan sentence. The generated sentence is automatically created based on the input information.

[1071] Step 8:

[1072] The server structures the generated plan text in JSON format and sends it to the terminal as an HTTP response.

[1073] Step 9:

[1074] The device receives the response from the server and analyzes the plan text. Specifically, it extracts the plan text from the JSON data.

[1075] Step 10:

[1076] The terminal displays the extracted plan sentence to the user, so that the user can confirm the generated plan sentence.

[1077] Example 1

[1078] 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."

[1079] In conventional accommodation plan proposal systems, users had to spend a great deal of time and effort creating detailed plan documents. It was also difficult to generate plan documents using different writing styles, and many aspects relied on manual work, making it difficult to ensure consistency and quality. Furthermore, there were problems with sending incorrect information due to insufficient verification of input information and a lack of user feedback.

[1080] 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.

[1081] In this invention, the server includes means for inputting basic information about accommodations, means for selecting a style for a plan proposal from a plurality of distinctive styles, generator means for generating a plan document based on the input basic information about accommodations and the selected style, means for displaying the generated plan document, means for verifying and providing feedback on the input basic information, means for packaging the input basic information and style information, and means for transmitting the packaged data to the server, thereby enabling users to automatically generate high-quality, consistent plan documents while saving time and effort.

[1082] "Basic information about accommodation facilities" is detailed information that serves as a criterion when a user selects accommodation facilities, such as the location of the accommodation facility, meal contents, and room facilities.

[1083] "Writing style" refers to the particular wording and expression used in the proposal text, and is selected based on the user's desired style.

[1084] The "generation device means" is a device or software that automatically generates a plan text based on the input basic information and selected style information.

[1085] "Validation and feedback measures" are functions that check the information entered by the user to detect errors or incompleteness, and provide the user with suggested corrections or error messages in real time.

[1086] A "packaging means" is a method or device that combines different information (for example, basic information and stylistic information) into a single data unit, and is used to maintain data consistency.

[1087] The "means for transmitting to the server" is a process or device that sends the packaged data to the server over a network.

[1088] A "generative AI model" is an artificial intelligence algorithm or software that automatically generates text based on input data.

[1089] "User interface" refers to the screens and input devices that allow the system and the user to exchange information with each other.

[1090] This invention is a system that allows a user to input basic information about accommodations, select a style for the proposed plan from multiple styles, and automatically generate a plan document using an AI model. Specific embodiments of this system are described below.

[1091] Enter basic information

[1092] First, the user enters basic information about the accommodation into the terminal. The basic information about the accommodation includes location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). For example, let's say the user enters "a ryokan (Japanese inn) that is a 10-minute walk from Kyoto Station and serves a Japanese breakfast." The terminal immediately verifies this information and displays an error message in real time for any input errors or incomplete information. The verified basic information is saved in local storage.

[1093] Character Selection

[1094] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. When the user selects "innkeeper style," the device saves this information and notifies the user that the selection is complete.

[1095] Submitting a plan generation request

[1096] The terminal compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set. This data is usually packaged in a format such as JSON, but an example of a specific prompt sentence would be as follows:

[1097] Basic information: "A 10-minute walk from Kyoto Station, this inn offers a Japanese breakfast."

[1098] Selected writing style: Innkeeper

[1099] The device sends this data to the server as an HTTP request.

[1100] Plan Generation Process

[1101] The server analyzes the request received from the device and extracts basic information about the accommodation and the selected writing style. The server then selects the most appropriate generative AI model. For example, if the "style of a landlady at an inn" is selected, the server calls the generative AI model for a landlady at an inn. Specifically, the following generative AI models are used:

[1102] Generative AI models: large-scale generative models such as GPT-3

[1103] The server inputs the extracted information into the AI ​​model and generates a plan. For example, if a user selects the basic information "a 10-minute walk from Kyoto Station, a Japanese-style inn with breakfast" and the writing style "the inn's landlady," the following example plan is generated:

[1104] "Dear guest, we are a conveniently located inn, just a 10-minute walk from Kyoto Station, and we offer a heart-warming Japanese breakfast. Please feel free to come and enjoy."

[1105] Submitting and Viewing Generated Plans

[1106] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[1107] Using this system, users can easily generate a variety of plan documents and use them to attract customers to their accommodations.

[1108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1109] Step 1:

[1110] The user enters basic information about the accommodation into the terminal. For example, they might enter information such as "a hotel with breakfast included, a five-minute walk from Tokyo Station." The terminal receives this information and verifies in real time whether the input is in the correct format. Specifically, if required fields are not filled in, an error message is displayed. If the input information is correct, the terminal saves the basic information in local storage. Input is in text format, and the output is the verified basic information.

[1111] Step 2:

[1112] The user selects the writing style of the plan proposal from a drop-down menu or radio buttons provided on the terminal screen. For example, the user selects the writing style of "the proprietress of a ryokan." The terminal receives this selection, confirms the user's selection, and saves it. Specifically, it displays a notification to the user that the selection is complete. The input is the selection of writing style, and the output is the selected writing style information.

[1113] Step 3:

[1114] The device compiles the basic information about the accommodation and the selected writing style information entered by the user into a single data set, and then packages this data in JSON format. For example, the following JSON data is generated:

[1115] json

[1116] {

[1117] "basic_info": "Hotel with breakfast, 5 minutes walk from Tokyo Station",

[1118] "style": "Innkeeper"

[1119] }

[1120] The terminal sends this JSON data to the server as an HTTP request. The input is basic information and style information, and the output is packaged JSON data.

[1121] Step 4:

[1122] The server analyzes the HTTP request received from the terminal. It deserializes the received data and extracts basic information about the accommodation and stylistic information. For example, extract "Hotel with breakfast, 5 minutes' walk from Tokyo Station" and "Proprietress of the inn" from the received data. The input is JSON data, and the output is the extracted basic information and stylistic information.

[1123] Step 5:

[1124] The server selects the optimal generative AI model based on the extracted information. For example, if the writing style of "innkeeper" is selected, the corresponding generative AI model is loaded. The server inputs basic information and writing style information into the generative AI model and generates a plan sentence. The specific input is the basic information "A hotel with breakfast, a five-minute walk from Tokyo Station" and the writing style information "Innkeeper", and the output is the plan sentence "Dear customer, we are a conveniently located hotel, a five-minute walk from Tokyo Station, and breakfast is available. Please feel free to use it."

[1125] Step 6:

[1126] The server packages the generated plan document and sends it as an HTTP response to the terminal. The input is the generated plan document and the output is the HTTP response.

[1127] Step 7:

[1128] The terminal receives the HTTP response from the server and analyzes the received data. It extracts the plan text and displays it on the user interface. The user can then view and confirm the generated plan text. Specifically, the user sees the text on the screen: "Dear customer, we are offering breakfast at a hotel conveniently located a five-minute walk from Tokyo Station. Please feel free to enjoy it." The input is the HTTP response data, and the output is the displayed plan text.

[1129] (Application example 1)

[1130] 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."

[1131] Conventional accommodation plan proposal systems could only make proposals using a fixed style, making it difficult to generate promotional text that flexibly reflects the individual needs of users and the characteristics of the facility. Furthermore, there was no means of automatically generating flexible and effective promotional text for other service types, such as food delivery services. Therefore, there is a need for an effective way to convey the appeal of facilities and services to the fullest extent.

[1132] 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.

[1133] In this invention, the server includes a means for inputting basic information about accommodations or food service locations, a means for selecting a style for the plan proposal or promotional text from a plurality of distinctive styles, and a generator means for generating plan text or promotional text based on the input basic information and the selected style, thereby enabling the automatic generation of plan text or promotional text in a flexible and diverse style that meets the needs of users.

[1134] "Accommodation facilities" refers to all facilities that provide accommodation services, and specifically includes hotels, inns, private lodgings, guest houses, etc.

[1135] "Food service location" refers to any facility that serves food and beverages, including restaurants, cafes, and food delivery services.

[1136] "Basic information" refers to information about the characteristics and service details of accommodations and food service locations, and specifically includes location, menu items, service details, price range, etc.

[1137] "Writing style" refers to the style of expression used when creating plan documents and promotional texts, and specifically includes hotel manager style, funky pop style, chic restaurant style, inn proprietress style, etc.

[1138] "Plan proposal" refers to a document proposing the services and benefits of accommodations and food establishments to customers.

[1139] "Promotional text" refers to text created to effectively advertise the services and menus of food service establishments, etc.

[1140] The "generation device means" refers to a device having the function of automatically generating a plan text or promotional text based on the input basic information and the selected writing style.

[1141] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates appropriate sentences based on input data.

[1142] The term "server" refers to a computer system that manages and processes data, and in the present invention is a central device that is responsible for generating plan documents and promotional documents.

[1143] The present invention is a system that inputs basic information about accommodations or food service locations, selects a style of plan proposal or promotional text from multiple distinctive styles, and automatically generates text using a generative AI model. One specific embodiment of the present invention is described below.

[1144] First, the user uses a device (such as a smartphone or head-mounted display) to input basic information about the accommodation or food service location. This information includes location information (e.g., "5 minutes' walk from X station"), menu items (e.g., "pizza, salad, pasta"), and service details (e.g., "breakfast included").

[1145] Next, the user selects a writing style using drop-down menus or radio buttons provided on the device. The available writing styles include hotel manager, funky pop, chic restaurant, and innkeeper. The user's selected writing style information is also saved on the device.

[1146] The device compiles the input basic information and the selected writing style information into a single data package, usually in JSON format, and sends this data to the server as an HTTP request.

[1147] The server analyzes the request received from the device and extracts basic information and the selected writing style information. The server then selects the most appropriate generative AI model. For example, if a funky pop style writing style is selected, the server calls a funky pop style generative AI model. The server generates a plan or promotional text by providing the extracted information as input to the generative AI model.

[1148] An example of a generated plan or promotion statement is:

[1149] Basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 5 minutes' walk from XX Station."

[1150] Selected writing style: Innkeeper style

[1151] Generated plan: "Dear guest, we are a conveniently located inn, just a 5-minute walk from XX Station, and we offer a heart-warming Japanese breakfast. Please come and enjoy."

[1152] The server sends the generated text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the generated text, and displays it on the user interface. This allows the user to view the automatically generated text.

[1153] To implement this system, the following hardware and software are used:

[1154] Devices: Digital devices such as smartphones and head-mounted displays

[1155] Server: A computer system that manages and processes data.

[1156] Generative AI models, such as the OpenAI API for natural language generation

[1157] For example, to generate a funky pop style promotional text, the prompt text is:

[1158] Menu items: Pizza, Salad, Pasta

[1159] Delivery area: Shibuya Ward, Meguro Ward

[1160] Style: Funky Pop

[1161] Generate a promotional text:

[1162] This invention makes it possible to automatically generate plan texts or promotional texts in a variety of writing styles according to the needs of users, thereby maximizing the appeal of the services of accommodation facilities and food service establishments.

[1163] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1164] Step 1:

[1165] The user uses the device to input basic information about the accommodation or food service location. This information includes location information (e.g., "5 minutes' walk from X station"), menu items (e.g., "pizza, salad, pasta"), and service details (e.g., "breakfast included"). Based on this input, data is stored in the device.

[1166] Step 2:

[1167] Users can select a writing style using drop-down menus or radio buttons provided on the device. The available writing styles include hotel manager, funky pop, chic restaurant, and innkeeper. The writing style information selected by the user is also saved on the device.

[1168] Step 3:

[1169] The device compiles the input basic information and the selected writing style information into a single piece of data, usually packaged in a format such as JSON, and sends this data to the server as an HTTP request.

[1170] Step 4:

[1171] The server analyzes the request received from the terminal and extracts basic information and selected writing style information. The data obtained from this analysis is stored internally on the server.

[1172] Step 5:

[1173] The server selects the most suitable AI model. For example, if a funky pop style is selected, the server calls a funky pop AI model. The data required for this selection are basic information and style information.

[1174] Step 6:

[1175] The server provides the extracted basic information and style information as input to the generative AI model. The generative AI model performs natural language processing based on this data to generate appropriate plan or promotional text. The generated text is stored internally on the server.

[1176] Step 7:

[1177] The server sends the generated plan or promotion text to the terminal as an HTTP response, which includes the generated text.

[1178] Step 8:

[1179] The terminal receives the response from the server, analyzes it, and extracts the generated text. The terminal displays the text on the user interface, allowing the user to view the automatically generated plan text or promotion text.

[1180] In this way, a series of processes is completed in which a plan or promotional text is automatically generated using a generative AI model based on the basic information entered by the user and the writing style selected, and the results are displayed on the terminal.

[1181] 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.

[1182] This invention combines a system in which a user inputs basic information about an accommodation facility, selects a style of plan proposal from multiple styles, and automatically generates plan text using an AI model, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[1183] Enter basic information

[1184] First, the user inputs basic information about the accommodation into the terminal, including location information (e.g., "5 minutes' walk from Tokyo Station") and meal details (e.g., "breakfast included"). The terminal stores this information and provides real-time feedback to the user as needed (e.g., displays error messages for input errors or incomplete information).

[1185] Character Selection

[1186] Next, the user selects the style of the plan proposal from a drop-down menu or radio buttons provided on the device. The available styles include hotel manager style, gyaru style, and innkeeper style. The device confirms the user's selection and also saves this information.

[1187] Emotion Engine Operation

[1188] The device is equipped with an emotion engine that recognizes the user's emotions. The emotion engine estimates the user's emotions based on the user's input and interactions, such as keyboard typing speed and mouse movements, as well as facial recognition and voice analysis. This emotion information is used to generate the plan text.

[1189] Submitting a plan generation request

[1190] The device compiles the basic information entered by the user, the selected writing style, and the estimated emotion information into a single data set. This data is usually packaged in a format such as JSON. The device then sends this data to the server as an HTTP request.

[1191] Plan Generation Process

[1192] The server analyzes the request received from the device and extracts basic information about the accommodation facility, the selected writing style, and emotional information. The server then selects the optimal generative AI model. For example, if a writing style in the style of a female innkeeper is selected, the server calls the generative AI model in the style of a female innkeeper. The server generates a plan text by providing the extracted information as input to the AI ​​model. At this time, the tone and expression of the text are adjusted based on the emotional information.

[1193] Submitting and Viewing Generated Plans

[1194] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives the response from the server, analyzes it, extracts the plan text, and displays it on the user interface. The user can then view the automatically generated plan text.

[1195] Specific examples

[1196] Specific examples are shown below.

[1197] 1. The user enters the basic information: "A ryokan (Japanese inn) with a Japanese breakfast, 10 minutes' walk from Kyoto Station."

[1198] 2. The user selects the character "Innkeeper."

[1199] 3. The device uses an emotion engine to estimate the user's emotion as "excited."

[1200] 4. The device sends the information to the server.

[1201] 5. The server generates a plan document using a generative AI model based on the information.

[1202] Generated plan example: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[1203] 6. The server sends the generated plan document to the terminal.

[1204] 7. The terminal displays the plan text to the user.

[1205] Displayed text: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[1206] As described above, this system can generate a variety of plan sentences that correspond to the user's emotions, which can be used to attract customers to accommodation facilities.

[1207] The processing flow will be explained below.

[1208] Step 1:

[1209] The user enters basic information about the accommodation into the terminal. Specifically, the user enters information about the location (e.g., "10 minutes' walk from Kyoto Station") and meal details (e.g., "Japanese breakfast included") into the input form.

[1210] Step 2:

[1211] The user selects the style of the plan proposal from the UI on the device. The options include three styles: hotel manager style, gyaru style, and inn proprietress style. The user clicks or taps the appropriate option.

[1212] Step 3:

[1213] The device compiles the basic information entered by the user and the selected writing style, and the compiled data is usually structured in JSON format.

[1214] Step 4:

[1215] The emotion engine built into the device analyzes the user's input and interactions (e.g., keyboard input speed, mouse movement, face recognition, voice analysis) to estimate the user's emotion. This estimated emotion information is added to the data.

[1216] Step 5:

[1217] The device sends structured JSON data to the server as an HTTP POST request, which includes the input basic information, the selected writing style, and the estimated emotion information.

[1218] Step 6:

[1219] The server analyzes the request received from the terminal, specifically extracting basic information about the accommodation, the selected writing style, and sentiment information from the request.

[1220] Step 7:

[1221] The server selects an appropriate AI model based on the selected writing style. For example, if the writing style is "innkeeper-style," the server selects an AI model that is in the innkeeper-style.

[1222] Step 8:

[1223] The server inputs the extracted basic information, stylistic information, and emotional information into a generative AI model to generate a plan sentence. The tone and expression of the generated sentence are adjusted based on the emotional information.

[1224] Step 9:

[1225] The server structures the generated plan text in JSON format and sends it to the terminal as an HTTP response.

[1226] Step 10:

[1227] The device receives the response from the server and analyzes the plan text. Specifically, it extracts the plan text from the JSON data.

[1228] Step 11:

[1229] The terminal displays the extracted plan sentence to the user, so that the user can confirm the generated plan sentence.

[1230] Example 2

[1231] 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."

[1232] Conventional accommodation plan proposal systems have difficulty generating flexible proposal text that reflects the user's emotions and preferences. Furthermore, the style of the proposal text is fixed, and users cannot choose from a variety of styles, making it difficult to attract their interest. Furthermore, because the automatic generation of plan text does not take the user's emotions into consideration, the proposal content can sometimes lack consistency.

[1233] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting basic information about accommodation facilities, a means for selecting a style of plan proposal from among a plurality of distinctive writing styles, a generation device means for generating a plan text based on the input basic information about accommodation facilities, the selected writing style, and emotional information, and a means for displaying the generated plan text. This makes it possible to generate a variety of plan texts according to the user's emotions and to help attract customers to accommodation facilities.

[1234] "Basic information about accommodation facilities" refers to key information about accommodation facilities, such as location information and meal contents.

[1235] "Plan proposal writing style" refers to the style and tone of expression in the plan text, and includes three types, for example, hotel manager style, gal style, and inn proprietress style.

[1236] "Emotional information" is information that indicates the user's emotional state and is estimated based on keyboard typing speed, facial recognition, voice analysis, etc.

[1237] The "generation device means" refers to a device or program for generating a plan text based on basic information about the accommodation facility, the selected style and emotion information.

[1238] A "generative AI model" refers to an artificial intelligence model that generates sentences based on input information, and is used to create appropriate sentences based on style and emotion.

[1239] "Display means" refers to means for displaying the generated plan text on the screen or display of a terminal so that the user can check it.

[1240] An "HTTP request" refers to a protocol-based communication method by which a client (here, a terminal) requests data or processing from a server.

[1241] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight data exchange format for structuring, storing, and transferring data.

[1242] This invention combines a system in which a user inputs basic information about an accommodation facility, selects a style of plan proposal from multiple styles, and automatically generates plan text using an AI model, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[1243] First, the user enters basic information about the accommodation into the terminal. For example, basic information about the accommodation may include information such as "10 minutes' walk from Kyoto Station, Japanese breakfast included." The terminal temporarily stores the information entered by the user and displays an error message if the information is incomplete or there is an input error. This process of entering basic information allows the user to receive feedback in real time.

[1244] Next, the user selects the style of the plan proposal from the options provided on the device (drop-down menu or radio button). The style can be selected from "Hotel Manager Style," "Gyaru Style," or "Innkeeper Style." The device confirms the selected style and saves this information.

[1245] Furthermore, the device is equipped with an emotion engine that recognizes the user's emotions. This emotion recognition uses functions such as keyboard input speed, face recognition, and voice analysis. For example, if the user types quickly or smiles, it is estimated that the user is "excited." This emotion information is used when generating plan sentences.

[1246] The device combines basic information, the selected writing style, and estimated emotion information into a single package in JSON format, which is then sent to the server as an HTTP request. For example, the prompt text might look like this:

[1247] {

[1248] "Basic Information": "10 minutes walk from Kyoto Station, Japanese breakfast included",

[1249] "Style": "Innkeeper style",

[1250] "Emotion": "Excited"

[1251] }

[1252] The server receives the request sent from the device and analyzes the JSON data. Based on the analyzed information, it selects the most appropriate generative AI model. For example, if "innkeeper style" is selected as the writing style, the innkeeper style generative AI model is called. The server then inputs the information into the AI ​​model and generates a plan sentence. At this time, the tone and expression of the sentence are adjusted based on the emotional information.

[1253] The generated plan text is sent to the terminal as an HTTP response. The terminal receives the response, analyzes it, extracts the plan text, and displays it on the user interface. The user can check the automatically generated plan text in real time.

[1254] As a specific example, if a user inputs "a ryokan (Japanese inn) with a Japanese breakfast, a 10-minute walk from Kyoto Station," selects "ryokan proprietress" as the writing style, and the emotion engine estimates that the user is "excited," the server will generate a plan sentence such as "Hello! We are offering a heart-warming Japanese breakfast at a ryokan conveniently located a 10-minute walk from Kyoto Station. We hope you have a wonderful time!" The device will display this sentence to the user, allowing the user to confirm its contents.

[1255] As described above, this system generates and provides a variety of plan texts that take emotions into consideration in order to increase the user's satisfaction with accommodation proposals.

[1256] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1257] Step 1:

[1258] The user enters basic information.

[1259] Input: The user enters basic information about the accommodation, such as "10 minutes walk from Kyoto Station, Japanese breakfast included."

[1260] Data processing: The terminal temporarily stores the input data and checks the input contents of each field.

[1261] Output: The basic information entered by the user is saved and an error message is displayed if the information is incomplete or contains a typo.

[1262] What happens: The device may display the error message "Breakfast type not entered."

[1263] Step 2:

[1264] The user selects the style of the plan proposal.

[1265] Input: The user selects one of three writing styles: "Hotel manager style," "Gyaru style," and "Innkeeper style."

[1266] Data processing: The device saves the selected writing style.

[1267] Output: The selected writing style is saved to the terminal for the next processing step.

[1268] Specific behavior: The user selects "Innkeeper Style" using the radio button.

[1269] Step 3:

[1270] The device's emotion engine recognizes the user's emotions.

[1271] Input: User input and interaction (keyboard typing speed, facial recognition, voice analysis, etc.)

[1272] Data processing: The device's emotion engine analyzes these input data and estimates the user's emotions.

[1273] Output: Estimated emotion information (e.g., "excited")

[1274] Specific behavior: The device uses the camera to scan the user's face, detects a smile, and infers that the user is "excited."

[1275] Step 4:

[1276] The terminal sends a plan generation request to the server.

[1277] Input: Basic information, selected writing style, estimated sentiment information

[1278] Data processing: The device packages this information in JSON format.

[1279] Output: Sends the packaged JSON data to the server as an HTTP request.

[1280] Specific operation: The device sends the following data in JSON format: "10 minutes walk from Kyoto Station, Japanese breakfast included," "Landlady-like inn," and "Excited."

[1281] Step 5:

[1282] The server performs the plan generation process.

[1283] Input: JSON data sent from the terminal

[1284] Data processing: The server parses the JSON data and extracts basic information, selected writing style, and sentiment information. It then selects the optimal generative AI model and inputs the extracted information into the AI ​​model.

[1285] Output: Generated plan text (e.g., "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station. We offer a delicious Japanese breakfast. We hope you have a wonderful time!")

[1286] Specific operation: The server selects the "ryokan proprietress-style" generation AI model, and generates a plan text by inputting the information "10 minutes' walk from Kyoto Station, Japanese breakfast included" and "Excited."

[1287] Step 6:

[1288] The server sends the generated plan text to the terminal.

[1289] Input: Generated plan document

[1290] Data processing: The server packages the generated plan document into an HTTP response.

[1291] Output: Sent to the device as an HTTP response.

[1292] Specific operation: The server sends the generated plan document to the terminal as an HTTP response.

[1293] Step 7:

[1294] The terminal displays the generated plan text.

[1295] Input: HTTP response received from the server

[1296] Data processing: The terminal analyzes the response and extracts the plan text.

[1297] Output: The plan text is displayed in the user interface.

[1298] What it does: The device displays the following text: "Hello! We are a conveniently located inn, just a 10-minute walk from Kyoto Station, and we offer a delicious Japanese breakfast. We hope you have a wonderful time!"

[1299] (Application example 2)

[1300] 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."

[1301] Conventional generation systems generate text without considering the user's emotions, making them unable to flexibly respond to individual needs. It is also difficult to generate text with an appropriate tone for specific situations and emotions. In particular, when generating equipment inspection reports for factory robots, reports are provided that ignore the user's emotions, which can lead to problems in effectively conveying necessary information.

[1302] 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.

[1303] In this invention, the server is equipped with an emotion engine that recognizes the user's emotions, and includes means for adjusting the tone and expression of the text based on the analyzed emotion information, means for generating a plan text based on a style selected from three styles: formal, casual, and technical terminology, and means for calling a generation AI model based on the user's input and the analyzed emotion information to generate the plan text. This enables more individualized and effective text generation that is in line with the user's emotions.

[1304] "Basic information about accommodation facility" is data that allows the user to input details about the accommodation facility, including location information, meal details, and the like.

[1305] The "plan proposal writing style" is selected from among several distinctive styles of expression, and is a factor that determines the tone and atmosphere of the generated text.

[1306] "Generation device means" refers to a device for automatically generating sentences using a generative AI model based on basic information entered by a user and a selected writing style.

[1307] The "emotion engine" is an engine that analyzes the user's facial expressions and voice to recognize emotions, and adjusts the tone and expression of the text based on that information.

[1308] A "formal style" is a style that emphasizes formality and courtesy and is used in formal settings, and is suitable for official documents.

[1309] "Casual writing style" is a writing style that is everyday and familiar, and uses informal and simple expressions.

[1310] A "technical jargon style" is a style that includes many specialized terms and expressions used in a particular technical field, and is aimed at engineers and specialists.

[1311] A "generative AI model" is an artificial intelligence model used to generate appropriate sentences based on input data, and creates sentences using a learning algorithm.

[1312] This invention is a system that combines an emotion engine that recognizes the user's emotions with a system that allows a user to input basic information about an accommodation facility, select a suggested writing style from multiple distinctive writing styles, and automatically generate a plan document using an AI model. A specific embodiment of this system will be described below.

[1313] First, the user inputs basic information about the accommodation facility into the terminal. This basic information includes data such as "Cooling system within the factory, east side of the second factory, inspection details: check for abnormal fan noise." This information is input using an interface such as a keyboard or touch screen.

[1314] Next, the user selects the style of the inspection report from options provided on the device: formal, casual, or technical.

[1315] The device has a built-in emotion engine that recognizes the user's emotions. This emotion engine captures the user's facial expressions and voice using a camera and microphone, and estimates the user's emotions using emotion analysis software (e.g., Affectiva SDK). The estimated emotion information is then used to adjust the tone and expression of the generated text.

[1316] The emotional information collected by the emotion engine, the basic information entered by the user, and the selected writing style are packaged in JSON format and sent to the server as an HTTP request. The server receives this request and analyzes the request. The analysis involves using a programming language such as Python to input the data into a generative AI model (e.g., OpenAI GPT-3).

[1317] The server selects the most appropriate generative AI model based on the received content. For example, if a technical terminology style is selected, a generative AI model that matches that style will be called up. The generative AI model receives the prompt "Cooling system inside the factory, east side of the second factory, inspection content: check for abnormal fan noise" and generates an inspection report in the appropriate tone.

[1318] Here are some examples of prompts:

[1319] Cooling system inside the factory, east side of the second factory, inspection content: Check for abnormal fan noise

[1320] The generated inspection report may have the following format, for example: "Inspection results for the cooling system: An abnormal noise was detected from the cooling fan located on the east side of the second factory. Worn fan blades and deterioration of bearings were observed. Immediate replacement is recommended."

[1321] The generated report is sent from the server to the terminal as an HTTP response. The terminal receives this report and displays it on the user interface, allowing the user to check the automatically generated inspection report.

[1322] This system enables flexible responses based on the user's emotions, and is expected to effectively convey necessary information, particularly when generating equipment inspection reports for factory robots.

[1323] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1324] Step 1:

[1325] The user inputs basic information about the accommodation facility or factory equipment into the terminal. This basic information may include, for example, "Cooling system within the factory, east side of the second factory, inspection details: check for abnormal fan noise." This input information is stored in the terminal's memory and feedback is provided to the user in real time. The input data format is specified in JSON format or similar.

[1326] Step 2:

[1327] The user selects a writing style from the options provided on the device. There are three writing styles to choose from: formal, casual, and technical. This selection is saved on the device. For example, if "technical" is selected, that information will be used in the next step.

[1328] Step 3:

[1329] The device's built-in emotion engine analyzes the user's emotions. It captures the user's facial expressions and voice using a camera and microphone, and uses emotion analysis software (e.g., Affectiva SDK) to estimate emotional information. This emotional information is also stored on the device. The analyzed emotional information may include, for example, "I'm nervous."

[1330] Step 4:

[1331] The device will then compile the input basic information, the selected writing style, and the analyzed emotional information into a single data package. The package data will be in JSON format, and will look something like this:

[1332] {

[1333] "facility_info": "Factory cooling system, east side of Factory 2, inspection details: check for abnormal fan noise",

[1334] "selected_tone": "Technical jargon style",

[1335] "user_emotion": "I'm nervous"

[1336] }

[1337] This data is sent to the server as an HTTP request.

[1338] Step 5:

[1339] The server receives the data package sent from the client, analyzes the received data, and extracts basic information, selected writing style, and sentiment information separately.

[1340] Step 6:

[1341] The server selects the most appropriate generative AI model (e.g., OpenAI GPT-3) based on the analyzed data. For example, if "technical terminology style" is selected, the server calls the corresponding generative AI model. The extracted basic information, the selected style, and the emotional information are provided as input data to the called generative AI model.

[1342] Step 7:

[1343] The generative AI model generates a plan sentence based on the input data. The tone and expression of the sentence are adjusted based on the emotional information. For example, the generated plan sentence might be in the following format: "Inspection results for the cooling system: An abnormal noise was detected from the cooling fan located on the east side of the second factory. Wear on the fan blades and deterioration of the bearings were observed. Prompt replacement is recommended."

[1344] Step 8:

[1345] The server sends the generated plan text to the terminal as an HTTP response. The terminal receives this response and displays the generated plan text on the user interface. As a result, the user can check the automatically generated appropriate plan text.

[1346] 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.

[1347] 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.

[1348] 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.

[1349] 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.

[1350] FIG. 9 is a diagram illustrating 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 actions 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.

[1351] 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.

[1352] 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).

[1353] 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.

[1354] 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."

[1355] 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.

[1356] 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).

[1357] 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.

[1358] 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.

[1359] 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.

[1360] 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.

[1361] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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 example of a 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.

[1362] 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.

[1363] 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.

[1364] 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.

[1365] 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.

[1366] 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.

[1367] The following is further disclosed regarding the above embodiment.

[1368] (Claim 1)

[1369] A means to enter basic information about the accommodation;

[1370] a means for selecting a style of writing for the plan proposal from among a plurality of distinctive styles;

[1371] A generator means for generating a plan sentence based on the input basic information of the accommodation facility and the selected writing style;

[1372] a means for displaying the generated plan text;

[1373] A system including:

[1374] (Claim 2)

[1375] The system according to claim 1, wherein the generation device means generates a plan text based on a style selected from three styles: a hotel manager style, a gal style, and an inn proprietress style.

[1376] (Claim 3)

[1377] 2. The system according to claim 1, wherein the generator means calls a generative AI model based on user input to generate a plan document.

[1378] "Example 1"

[1379] (Claim 1)

[1380] A means to enter basic information about the accommodation;

[1381] a means for selecting a style of writing for the plan proposal from among a plurality of distinctive styles;

[1382] A generator means for generating a plan sentence based on the input basic information of the accommodation facility and the selected writing style;

[1383] a means for displaying the generated plan text;

[1384] A means of verifying and providing feedback on the basic information entered;

[1385] A means for packaging the input basic information and stylistic information;

[1386] means for transmitting the packaged data to a server;

[1387] A system including:

[1388] (Claim 2)

[1389] The system according to claim 1, wherein the generation device means generates a plan text based on a style selected from three styles: a hotel manager style, a gal style, and an innkeeper style.

[1390] (Claim 3)

[1391] 2. The system according to claim 1, wherein the generation device means calls a generation AI model based on user input to generate a plan document.

[1392] "Application Example 1"

[1393] (Claim 1)

[1394] a means for inputting basic information about the accommodation or food service location;

[1395] A means for selecting a style of proposal or promotional text from a plurality of distinctive styles;

[1396] a generator means for generating a plan or promotional text based on the input basic information and the selected writing style;

[1397] means for displaying the generated offer text or promotion text;

[1398] A system including:

[1399] (Claim 2)

[1400] The system according to claim 1, wherein the generation device means generates plan text or promotional text based on a writing style selected from a hotel manager's writing style, a funky pop writing style, a chic restaurant writing style, and an inn proprietress writing style.

[1401] (Claim 3)

[1402] 2. The system according to claim 1, wherein the generation device means calls a generation AI model based on user input to generate a plan document or promotional document.

[1403] "Example 2: Combining Emotion Engines"

[1404] (Claim 1)

[1405] A means to enter basic information about the accommodation;

[1406] a means for selecting a style of writing for the plan proposal from among a plurality of distinctive styles;

[1407] A generator means for generating a plan sentence based on the input basic information of the accommodation facility and the selected writing style and emotion information;

[1408] a means for displaying the generated plan text;

[1409] A system including:

[1410] (Claim 2)

[1411] The system according to claim 1, wherein the generation device means generates a plan text based on a style selected from three styles: a hotel manager style, a gal style, and an inn proprietress style.

[1412] (Claim 3)

[1413] 2. The system according to claim 1, wherein the generation device means calls a generation AI model based on user input and emotional information to generate a plan sentence.

[1414] "Application example 2 when combining emotion engines"

[1415] (Claim 1)

[1416] A means to enter basic information about the accommodation;

[1417] A means for selecting a style of writing for a plan proposal from among a plurality of distinctive styles;

[1418] A generator means for generating a plan sentence based on the input basic information of the accommodation facility and the selected writing style;

[1419] a means for displaying the generated plan text;

[1420] a means for adjusting the tone and expression of a sentence based on the analyzed emotion information, the emotion engine being provided to recognize the emotion of the user;

[1421] A system including:

[1422] (Claim 2)

[1423] 2. The system of claim 1, wherein said generator means generates plan text based on a style selected from three styles: formal, casual, and technical.

[1424] (Claim 3)

[1425] 2. The system according to claim 1, wherein the generation device means calls a generation AI model based on the user's input content and analyzed emotional information to generate a plan sentence. [Explanation of symbols]

[1426] 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. A means to enter basic information about the accommodation; a means for selecting a style of writing for a plan proposal from among a plurality of distinctive styles; A generator means for generating a plan sentence based on the input basic information of the accommodation facility and the selected writing style; a means for displaying the generated plan text; A system including:

2. The system according to claim 1, wherein the generation device means generates a plan text based on a style selected from three styles: a hotel manager style, a gal style, and an inn proprietress style.

3. 2. The system according to claim 1, wherein the generator means calls a generative AI model based on user input to generate a plan document.

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