system

Abstract

We provide the system. [Solution] A means for storing information received from the user, Means for establishing connections with external sites, A method for translating user messages using generative artificial intelligence, A means of sending the translated message to an external site, A means of translating and notifying users of replies from external sites, A means of saving the negotiation history, A means of collecting and storing feedback, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is 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 an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Currently, when conducting business negotiations with overseas e-commerce sites or retail sites, many users do not have sufficient English skills and need to spend time and money to acquire those skills. In addition, due to language and cultural differences, misunderstandings and miscommunications are likely to occur. For this reason, negotiations often do not proceed smoothly, and there is a problem that the success rate of transactions decreases.

Means for Solving the Problems

[0005] In order to solve these problems, the present invention provides the following means.

[0006] The system includes means for storing information received from users, means for establishing connections with external sites, means for translating user messages using generative artificial intelligence, means for sending translated messages to external sites, means for translating and notifying users of replies from external sites, means for storing negotiation history, and means for collecting and storing feedback. Specifically, it includes means for translating user messages into appropriate business terminology using generative artificial intelligence, as well as means for confirming the success or failure of external site connections and saving the connection status.

[0007] A "user" is an individual or company that uses the system to conduct business negotiations or business deals.

[0008] "Means of saving information" refers to a function that records various data entered by users (age, gender, English skills, etc.) in a database or similar system, making it accessible later.

[0009] "External sites" refer to online commercial platforms such as e-commerce sites and retail sites.

[0010] "Means of establishing a connection" refers to the function of accessing external sites and establishing a connection using APIs or other communication protocols.

[0011] "Generative artificial intelligence" refers to artificial intelligence algorithms that perform natural language processing to generate translations and texts appropriate to a specific context.

[0012] A "user message" is a text message entered by a user for negotiation or business discussion purposes.

[0013] "Translation means" refers to a function that uses generative artificial intelligence to appropriately convert user messages into a specified language.

[0014] "Means of sending to external sites" refers to the function of transmitting translated messages to a specific receiving location on an external site (such as an API endpoint).

[0015] "Reply" means a response to a user's message received from an external site.

[0016] "Translation and notification means" is a function that translates a reply from an external site into a language that the user can understand and notifies the user.

[0017] "Negotiation history" means the entire record of messages exchanged between the user and the external site.

[0018] "History storage means" is a function that stores the negotiation history in a database or the like and makes it accessible later.

[0019] "Feedback" means evaluations and comments provided by the user regarding the negotiation or business negotiation process.

[0020] "Collection and storage means" is a function that receives feedback from the user, records it in a database or the like, and retains it.

Brief Description of Drawings

[0021] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7]It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0022] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0023] First, the language used in the following description will be explained.

[0024] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0025] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0026] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0027] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0029] [First Embodiment]

[0030] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0031] As shown in Figure 1, the 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.

[0032] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0034] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0035] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0037] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0041] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0042] This invention is a system that uses generative AI to help users conduct smooth business negotiations with overseas e-commerce and retail sites. The system's program processing is described in detail below.

[0043] User registration and initial setup

[0044] 1. The user launches the application and enters personal information such as age, gender, and English language skills.

[0045] 2. The terminal sends the entered information to the server.

[0046] 3. The server receives user information, validates it, and then stores it in the database. This step allows the system to manage basic profile information for each user.

[0047] Connection with e-commerce sites and retail sites

[0048] 1. Utilize an interface that allows users to select the e-commerce or retail site they wish to connect to.

[0049] 2. The device sends the selected site information (such as URL and API key) to the server.

[0050] 3. Based on the information received by the server, it establishes a connection with an external site using APIs and communication protocols.

[0051] 4. The server checks whether the connection was successful and saves the connection status to the database.

[0052] Automatic translation and business negotiation support

[0053] 1. Enter a message for the user to initiate negotiations within the application.

[0054] 2. The terminal sends the entered message to the server.

[0055] 3. The server uses generative artificial intelligence to translate the input message into appropriate business English.

[0056] 4. The server sends the translated message to the e-commerce site and proceeds with the negotiation.

[0057] 5. The server receives the reply from the e-commerce site, translates it into a language the user can understand, and notifies the user.

[0058] 6. The device displays the translated reply and waits for the user to enter their reply again. By repeating this process, the user can negotiate smoothly.

[0059] Negotiation history management

[0060] 1. The server stores the entire negotiation history in a database. This includes all sent and received messages, as well as various metadata (such as timestamps).

[0061] 2. This historical data will be stored for future analysis and training purposes.

[0062] Collecting user feedback

[0063] 1. After the negotiation is complete, the user will have access to an interface to provide feedback.

[0064] 2. The device sends feedback information (ratings and comments) to the server.

[0065] 3. The server saves the feedback to a database so that it can be used for future system improvements.

[0066] Specific example

[0067] Example 1: User Registration

[0068] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[0069] The terminal sends input information to the server, and the server stores the received information in a database.

[0070] Example 2: Negotiating with an e-commerce site

[0071] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[0072] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[0073] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[0074] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[0075] In this way, the present invention is a system that enables users to conduct business negotiations smoothly, transcending language and cultural differences.

[0076] The following describes the processing flow.

[0077] User registration and initial setup

[0078] Step 1:

[0079] The user launches the application and enters personal information such as age, gender, and English language skills.

[0080] Step 2:

[0081] The terminal sends the entered information to the server via an HTTP request.

[0082] Step 3:

[0083] The server receives user information and validates the input data, checking for any inappropriate data.

[0084] Step 4:

[0085] The server establishes a database connection and saves user information that has passed validation to the database.

[0086] Connection with e-commerce sites and retail sites

[0087] Step 1:

[0088] Users select the e-commerce or retail site they want to connect to via a web interface.

[0089] Step 2:

[0090] The device sends selected information (site URL, API key, etc.) to the server as structured data.

[0091] Step 3:

[0092] Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[0093] Step 4:

[0094] The server receives the API request response and checks whether the connection was successful.

[0095] Step 5:

[0096] The server saves the connection status to the database, and if the connection is successful, it notifies the user that the system can proceed to the next step.

[0097] Automatic translation and business negotiation support

[0098] Step 1:

[0099] The user enters a text message to initiate a business negotiation into an input form within the application.

[0100] Step 2:

[0101] The terminal sends the entered message to the server.

[0102] Step 3:

[0103] The server processes the received message and calls upon generative artificial intelligence to translate it into appropriate business English.

[0104] Step 4:

[0105] The server sends the translated message as structured data to the API endpoint of an external site.

[0106] Step 5:

[0107] The server receives replies from external sites and uses generative artificial intelligence again to translate those replies into a language that the user can understand.

[0108] Step 6:

[0109] The server sends the translated reply message to the device and displays it to the user through the UX / UI.

[0110] Negotiation history management

[0111] Step 1:

[0112] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[0113] Step 2:

[0114] The server adds metadata (such as timestamps, user IDs, and external site IDs) to the historical data and stores it for future access and analysis.

[0115] Collecting user feedback

[0116] Step 1:

[0117] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[0118] Step 2:

[0119] The device sends feedback information (ratings, comments) to the server as structured data.

[0120] Step 3:

[0121] The server validates the feedback it receives and saves it to the database.

[0122] Step 4:

[0123] The server analyzes the collected feedback and uses it to improve the system.

[0124] (Example 1)

[0125] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0126] Conducting smooth business negotiations with overseas e-commerce and retail sites can be difficult due to language and cultural differences. Furthermore, manual translation by users and subsequent negotiations with external sites is time-consuming and laborious. Managing negotiation history and feedback is also cumbersome and inefficient. This invention aims to provide a system to solve these problems.

[0127] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0128] In this invention, the server includes means for storing information received from the user, means for transmitting information entered by the terminal to the server, means for the server to receive user information, validate it, and store it in a database, means for the user to select an external site they wish to connect to, means for the terminal to transmit selected site information (such as URL and API key) to the server, means for the server to establish a connection with the external site and store the connection status in a database, means for translating user messages using a generative artificial intelligence model, means for sending the translated messages to the external site, means for translating replies from the external site into the user's native language and notifying them, means for storing the negotiation history in a database, means for the user to provide feedback after the negotiation is completed, and means for collecting and storing the feedback. This enables users to efficiently conduct business negotiations across language barriers and effectively manage negotiation history and feedback.

[0129] A "user" refers to an individual or legal entity that uses the system to conduct business negotiations with overseas e-commerce sites and retail sites.

[0130] A "terminal" refers to an electronic device used by a user to input information and send and receive data to and from a server.

[0131] A "server" refers to a computer system that processes information received from users and stores it in a database.

[0132] A "database" refers to a system for structuring and storing various types of data, such as user information, connection status, negotiation history, and feedback.

[0133] "Validation" refers to the process of verifying the validity of information entered by a user.

[0134] "External sites" refer to e-commerce sites and retail sites that users connect to and conduct business negotiations with.

[0135] A "URL" refers to address information used to establish a connection to an external website.

[0136] An "API key" refers to the authentication information required to access an API on an external website.

[0137] "Generative artificial intelligence models" refer to AI technologies used for translating user messages and replies.

[0138] "Translation" refers to the process of converting a message entered by a user into another language.

[0139] A "message" refers to the text information that a user enters to conduct negotiations.

[0140] "Connection status" refers to information regarding the success or failure of the connection to an external site.

[0141] "Negotiation history" refers to all messages sent and received during the negotiation process, along with their associated metadata.

[0142] "Feedback" refers to the evaluations and comments that users provide after the negotiation has concluded.

[0143] This invention provides a system that assists users in smoothly conducting business negotiations with overseas e-commerce and retail sites. This system enables users to efficiently conduct business negotiations through user information input and storage, connection to external sites, translation assistance using AI generation, negotiation history management, and feedback collection and storage.

[0144] User registration and initial setup

[0145] The user launches the application and enters personal information such as age, gender, and English proficiency. This information is sent to the server by the device. The server validates the received information and stores it in a database. MySQL® is a suitable database to use.

[0146] Connection with e-commerce sites and retail sites

[0147] The system utilizes an interface where the user selects the e-commerce or retail site they wish to connect to. The terminal sends the selected site information (such as URL and API key) to the server. Based on the received information, the server establishes a connection with the external site using an API or communication protocol (e.g., REST API), verifies the success or failure of the connection, and saves the connection status to a database.

[0148] Automatic translation and business negotiation support

[0149] The user enters a message to initiate negotiations within the application. The device sends the entered message to the server. The server uses generative artificial intelligence (e.g., GPT-4®) to translate the entered message into appropriate business English. The translated message is sent to the e-commerce site to proceed with the negotiations. The server receives a reply from the e-commerce site, translates it into a language the user understands, and notifies the device. The device displays the translated reply and waits for the user to enter another reply. By repeating this process, the user can conduct negotiations smoothly.

[0150] Negotiation history management

[0151] The server stores the entire negotiation history in a database. This includes all sent and received messages, as well as various metadata (such as timestamps). PostgreSQL is a suitable database. This makes the negotiation history available for future analysis and training purposes.

[0152] Collecting user feedback

[0153] After the negotiation is complete, the user accesses an interface to provide feedback. The device sends feedback information (ratings and comments) to the server. The server stores the feedback in a database and makes it available for future system improvements.

[0154] Specific example

[0155] Example 1: User Registration

[0156] When user A uses the app for the first time, they register by entering their age (e.g., 28), gender (e.g., male), and English proficiency (e.g., intermediate). The device sends this information to the server, and the server stores the received information in a database.

[0157] Example 2: Negotiating with an e-commerce site

[0158] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[0159] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[0160] The server sends a message to a generative AI (e.g., GPT-4), which translates it into appropriate business English. The translated message is then sent to the e-commerce site.

[0161] The system receives a reply from an e-commerce site (e.g., "We can offer a 10% discount.") and uses a generative AI model to translate it into the user's native language. The translated reply is sent to the device, which then displays it to the user.

[0162] Example of a prompt

[0163] "Please explain the transmission process for saving User A's personal information to the database."

[0164] "Please describe the message sending and translation process when User B initiates price negotiations on an e-commerce site."

[0165] In this way, the present invention is a system that enables users to overcome language barriers and conduct business negotiations efficiently.

[0166] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0167] Step 1:

[0168] The user launches the application and enters personal information such as age, gender, and English proficiency. Specifically, the user enters information into a form within the app and presses the "Submit" button.

[0169] Input: Personal information entered by the user (age, gender, English proficiency)

[0170] Output: Personal information sent to the server by the terminal

[0171] Step 2:

[0172] The terminal sends the entered information to the server. Specifically, it converts the input data into JSON format and sends it to the server as an HTTP request.

[0173] Input: Personal information entered by the user (in JSON format)

[0174] Output: Personal information passed to the server

[0175] Step 3:

[0176] The server receives user information and performs validation. Specifically, it checks the validity of the received information (e.g., whether age is a numerical value, whether gender is a valid option, whether English skills are within a certain range).

[0177] Input: User information sent from the device

[0178] Output: Validated user information

[0179] Step 4:

[0180] The server saves user information that has passed validation to the database. Specifically, it inserts the information into the MySQL database using an SQL query.

[0181] Input: Validated user information

[0182] Output: User information stored in the database

[0183] Step 5:

[0184] The interface utilizes a selection process where the user chooses the external site they want to connect to. Specifically, the user selects a site from a dropdown menu or search box and then clicks the "Connect" button.

[0185] Input: Information about the selected external website (URL, API key, etc.)

[0186] Output: External site information sent to the server by the terminal.

[0187] Step 6:

[0188] The device sends information from the selected external website to the server. Specifically, it sends the selected information to the server as an HTTP request in JSON format.

[0189] Input: Selected external website information (JSON format)

[0190] Output: External site information passed to the server

[0191] Step 7:

[0192] Based on the external site information received by the server, it establishes a connection with the external site using an API or communication protocol (e.g., REST API). Specifically, it sets the HTTP headers and request body using the received URL and API key, and sends a request to the API endpoint.

[0193] Input: External site information (URL, API key, etc.)

[0194] Output: Establishing a connection with an external site

[0195] Step 8:

[0196] The server checks whether the connection was successful and saves the status to the database. Specifically, it receives the response to the API request, checks the success status code (e.g., 200 OK), and records the status information in the database.

[0197] Input: API request response

[0198] Output: Connection status stored in the database

[0199] Step 9:

[0200] The user enters a message to initiate negotiations within the app. Specifically, they type a message in the chat window and press the "Send" button.

[0201] Input: Message entered by the user

[0202] Output: Message sent from the terminal to the server

[0203] Step 10:

[0204] The terminal sends the entered message to the server. Specifically, it sends the message to the server as an HTTP request in text format.

[0205] Input: User-entered message (text format)

[0206] Output: Message passed to the server

[0207] Step 11:

[0208] The server uses a generative artificial intelligence model (e.g., GPT-4) to translate the input message. Specifically, it sends the received message as a prompt to the generative AI model and obtains the translated text.

[0209] Input: Message entered by the user

[0210] Output: Translated message

[0211] Step 12:

[0212] The server sends the translated message to an external site. Specifically, it sets the translated text in the body of an API request and sends it to the external site's API endpoint.

[0213] Input: Translated message

[0214] Output: Translated message sent to an external site

[0215] Step 13:

[0216] The server receives replies from external websites, translates them into the user's native language, and notifies them. Specifically, it sends the reply message to an AI model that generates translations and retrieves the translation results.

[0217] Input: Reply message from an external site

[0218] Output: Translated reply message

[0219] Step 14:

[0220] The device displays the translated reply and waits for the user to type another reply. Specifically, it displays the translated text in the chat window and re-enables the interface for entering a new message.

[0221] Input: Translated reply message

[0222] Output: Translated message displayed to the user

[0223] Step 15:

[0224] The server saves the entire negotiation history to a database. It stores all sent messages and replies, as well as various metadata (such as timestamps). Specifically, it inserts messages and metadata into a PostgreSQL database using SQL queries.

[0225] Input: Negotiation history information (messages and metadata)

[0226] Output: Negotiation history stored in the database

[0227] Step 16:

[0228] After the negotiation is complete, the user accesses an interface to provide feedback. Specifically, they enter their rating and comments into the feedback form and press the "Submit" button.

[0229] Input: Feedback information (ratings and comments)

[0230] Output: Feedback sent from the terminal to the server

[0231] Step 17:

[0232] The device sends feedback information to the server. Specifically, it sends feedback data to the server in JSON format.

[0233] Input: Feedback information (JSON format)

[0234] Output: Feedback information passed to the server

[0235] Step 18:

[0236] The server saves the feedback to the database. Specifically, it inserts the feedback data into the database using an SQL query.

[0237] Input: Feedback Information

[0238] Output: Feedback information stored in the database

[0239] (Application Example 1)

[0240] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0241] When users conduct business negotiations with overseas e-commerce and retail sites, language barriers and communication obstacles are a major challenge. Furthermore, there is a need to efficiently manage these negotiation histories and feedback to improve the user's negotiation experience. Conventional systems have not consistently achieved these functions, placing a heavy burden on users, thus creating a need for a more efficient and smoother negotiation support system.

[0242] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0243] In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for appropriately translating user messages into business terminology using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for storing user registration information in a database and accessing it later, means for sending automatically translated messages to the site and receiving responses, and means for storing negotiation history in a database. As a result, users can overcome language barriers and smoothly conduct business negotiations with overseas e-commerce sites, and negotiation history and feedback can also be managed efficiently.

[0244] A "user" is an individual or legal entity that uses this system to conduct business negotiations with overseas e-commerce sites and retail sites.

[0245] "Information" refers to all data entered by users, including personal information, negotiation messages, and feedback.

[0246] "External sites" refer to online platforms that users use for negotiations, such as e-commerce sites and retail sites.

[0247] "Means of establishing a connection" refers to technologies that use APIs and communication protocols to initiate communication with external sites and create a state where data exchange is possible.

[0248] "Generative artificial intelligence" is an AI technology that uses natural language processing to translate user messages into appropriate business English.

[0249] "Translation methods" refer to technologies that utilize generative artificial intelligence to convert user-inputted messages into other languages.

[0250] A "database" is a system for efficiently storing and managing data such as user information, negotiation history, and feedback.

[0251] "Means for receiving responses" refers to technologies for receiving reply messages from external sites, loading them into a server, and notifying the user.

[0252] "Negotiation history" refers to a record of all business negotiations conducted by the user, including data such as sent messages, translated messages, received messages, and timestamps.

[0253] This invention is a system that uses generative artificial intelligence to help users conduct smooth business negotiations with overseas e-commerce sites and retail sites. A detailed embodiment of the system is described below.

[0254] System Configuration

[0255] This system primarily consists of three entities: servers, terminals, and users. The processes performed by each entity, as well as the hardware and software they use, are described in detail below.

[0256] User registration and initial setup

[0257] Users launch the application using their device (smartphone, PC, etc.) and enter personal information such as age, gender, and English language skills. The device sends the collected information to the server, which validates it and then stores it in a database. This allows for the management of the user's basic profile information.

[0258] Connection with e-commerce sites and retail sites

[0259] The user selects the e-commerce or retail site they wish to connect to via the terminal's interface. The selected site information (such as URL and API key) is sent from the terminal to the server, which then establishes a connection with the external site using APIs and communication protocols. The success or failure of the connection is stored in a database.

[0260] Automatic translation and business negotiation support

[0261] The user enters a message from their device to initiate negotiations. The device sends this message to the server, which uses generative artificial intelligence to translate the message into appropriate business English. The translated message is then sent to an external website. The server receives the reply from the external website, translates it into a language the user understands, and notifies the user of the reply on their device.

[0262] Negotiation history management

[0263] The server stores the entire negotiation history in a database. This history includes all sent and received messages, as well as various metadata (such as timestamps). This data is used for future analysis and system training.

[0264] Collecting user feedback

[0265] After negotiations are complete, users provide feedback through their devices. The devices send feedback information (ratings and comments) to the server, which stores it in a database. The collected feedback is used to improve the system.

[0266] Hardware and software to use

[0267] Server: Handles data storage, processing of generated AI models, API connections, and database management.

[0268] Terminal: As a user interface, it is responsible for message input and display. Smartphones and PCs are the main hardware examples.

[0269] Generative AI model: Used to translate user messages into business English. Utilizes natural language processing software such as the Google® Trans library.

[0270] Examples of specifics and prompts

[0271] Specific example 1:

[0272] When user A uses the app for the first time, they register by entering their age, gender, and English proficiency. The device sends this information to the server, and the server stores the received information in a database.

[0273] Specific example 2:

[0274] User B wants to purchase an item from an American e-commerce site and types "Can you offer a discount?". The server uses generative AI to translate the message, sends it to the e-commerce site in appropriate business English, and then translates the reply into a language the user understands and notifies them.

[0275] Example of a Generative AI Model prompt:

[0276] Original text: "What is the product's stock status?"

[0277] Prompt: Translate the following sentence into business English: 'What is the product's stock status?'

[0278] Translated text: "Could you please update me on the availability of the product?"

[0279] In this way, the system enables users to conduct business negotiations smoothly, transcending language and cultural barriers.

[0280] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0281] Step 1:

[0282] The user uses the terminal to launch an application. The user inputs personal information such as age, gender, and English skills, and sends it by clicking the save button.

[0283] Input: Personal information such as age, gender, and English skills.

[0284] Output: The sent user information.

[0285] Specific operation: After the user inputs the information and taps the "Send" button, the terminal sends the information to the server.

[0286] Step 2:

[0287] The server receives the user information sent from the terminal. The server validates the data and saves the information in the database.

[0288] Input: The sent user information.

[0289] Output: The validated and saved user information.

[0290] Specific operation: The server checks the received data to verify if there is any invalid data. Then, it saves the data in the database.

[0291] Step 3:

[0292] The user selects an external site (e.g., an e-commerce site or a retail site) to connect to using the terminal interface.

[0293] Input: Information of the external site to connect to (such as URL or API key).

[0294] Output: Information of the selected external site.

[0295] Specific operation: The user selects the external site from a dropdown list or search function and taps the "Connect" button.

[0296] Step 4:

[0297] The terminal sends the information of the selected external site to the server. Based on that information, the server establishes a connection using an API and a communication protocol.

[0298] Input: Information of the selected external site.

[0299] Output: Success or failure of the connection.

[0300] Specific operation: The server that receives the information sent from the terminal attempts to connect to the external site, determines the success or failure of the connection, and saves the success or failure in the database.

[0301] Step 5:

[0302] The user inputs a message for starting negotiation on the terminal.

[0303] Input: Message for starting negotiation.

[0304] Output: The input message.

[0305] Specific operation: The user inputs a negotiation message and taps the "Send" button.

[0306] [[ID=4I]]Step 6:

[0307] The terminal sends the input message to the server. The server translates the message into appropriate business English using a generative artificial intelligence.

[0308] Input: Message input by the user.

[0309] Output: Translated business English message.

[0310] Specific operation: The server receives the input message and performs translation using a generative AI model (e.g., Googletrans library).

[0311] Step 7:

[0312] The server sends the translated message to an external site.

[0313] Input: Translated business English message.

[0314] Output: Message sent to an external site.

[0315] Specific operation: The server sends the translated message by calling an API on an external site.

[0316] Step 8:

[0317] The server receives a reply from an external website. It translates the reply into a language the user understands and notifies the device.

[0318] Input: Reply message from an external website.

[0319] Output: Translated reply message.

[0320] Specific operation: The server receives a reply message, translates it using a generation AI model, and sends it to the terminal.

[0321] Step 9:

[0322] The server saves the entire negotiation history to a database.

[0323] Input: Negotiation history including sent messages, replied messages, and timestamps.

[0324] Output: Saved negotiation history.

[0325] Specific operation: The server records all negotiation details in a database.

[0326] Step 10:

[0327] Users provide feedback via their devices after the negotiation is complete.

[0328] Input: Feedback information such as ratings and comments.

[0329] Output: Sent feedback information.

[0330] Specific action: The user fills out a feedback form and taps the "Submit" button.

[0331] Step 11:

[0332] The device sends feedback information to the server. The server stores it in its database.

[0333] Input: Submitted feedback information.

[0334] Output: Saved feedback information.

[0335] Specific operation: The server receives feedback information sent from the terminal and saves it to the database.

[0336] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0337] This invention is a system that combines generative AI and an emotion engine to help users conduct more effective business negotiations with overseas e-commerce and retail sites. The system's program processing is described in detail below.

[0338] User registration and initial setup

[0339] 1. The user launches the application and enters personal information such as age, gender, and English language skills.

[0340] 2. The terminal sends the entered information to the server via an HTTP request.

[0341] 3. The server receives user information, validates the input data, and then saves it to the database. This step manages the basic profile information of each user.

[0342] Connection with e-commerce sites and retail sites

[0343] 1. The user selects the e-commerce or retail site they wish to connect to via the web interface.

[0344] 2. The device sends the selected information (site URL, API key, etc.) to the server as structured data.

[0345] 3. Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[0346] 4. The server receives the API request response and checks whether the connection was successful.

[0347] 5. The server saves the connection status to the database and, if the connection is successful, notifies the user that the system can proceed to the next process.

[0348] Automatic translation and business negotiation support

[0349] 1. The user enters a text message to initiate a business negotiation into an input form within the application.

[0350] 2. The terminal sends the entered message to the server.

[0351] 3. The server processes the received message and calls a generative artificial intelligence to translate it into appropriate business English.

[0352] 4. The server sends the translated message as structured data to the API endpoint of the external site.

[0353] 5. The server receives the reply from the external site and uses generative artificial intelligence again to translate the reply into a language that the user can understand.

[0354] 6. The server sends the translated reply message to the terminal and displays it to the user through the UX / UI.

[0355] Negotiation history management

[0356] 1. The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[0357] 2. The server adds metadata (timestamp, user ID, external site ID, etc.) to the historical data and stores it for future access and analysis.

[0358] Collecting user feedback

[0359] 1. After the negotiation is complete, the user accesses an interface for providing feedback and enters their rating and comments.

[0360] 2. The device sends feedback information (ratings, comments) to the server as structured data.

[0361] 3. The server validates the feedback it receives and saves it to the database.

[0362] 4. The server analyzes the collected feedback and uses it to improve the system.

[0363] Using an Emotion Engine

[0364] 1. When a user enters a message, the device also sends data representing the user's emotional state to the server (e.g., linguistic characteristics, facial recognition data).

[0365] 2. The server uses an emotion engine to analyze the user's emotional state from the received data.

[0366] 3. The server reflects the results of the emotional analysis into the generative artificial intelligence, which then performs the translation using appropriate tone and expression.

[0367] 4. The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information.

[0368] Specific example

[0369] Example 1: User Registration

[0370] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[0371] The terminal sends input information to the server, and the server stores the received information in a database.

[0372] Example 2: Negotiating with an e-commerce site

[0373] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[0374] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[0375] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[0376] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[0377] Example 3: Using an Emotion Engine

[0378] User C types "I am very frustrated with the delay" during negotiations.

[0379] The device sends facial recognition data and voice tone data to the server along with the message.

[0380] The server uses an emotion engine to recognize user C's emotional state as "frustrated."

[0381] The server considers the emotional state and translates in an appropriate tone through a generative AI.

[0382] The server generates the translation "I understand your frustration and will expedite your request." and notifies the terminal.

[0383] Thus, the present invention is a system that integrates a generative AI and an emotion engine, enabling users to conduct business negotiations more smoothly, transcending language and cultural differences.

[0384] The following describes the processing flow.

[0385] User registration and initial setup

[0386] Step 1:

[0387] The user launches the application and enters personal information such as age, gender, and English language skills.

[0388] Step 2:

[0389] The terminal sends the entered information to the server via an HTTP request.

[0390] Step 3:

[0391] The server receives user information and validates the input data, checking for any inappropriate data.

[0392] Step 4:

[0393] The server establishes a database connection and saves user information that has passed validation to the database.

[0394] Connection with e-commerce sites and retail sites

[0395] Step 1:

[0396] Users select the e-commerce or retail site they want to connect to via a web interface.

[0397] Step 2:

[0398] The device sends selected information (site URL, API key, etc.) to the server as structured data.

[0399] Step 3:

[0400] Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[0401] Step 4:

[0402] The server receives the API request response and checks whether the connection was successful.

[0403] Step 5:

[0404] The server saves the connection status to the database and, if the connection is successful, notifies the user that the system can proceed to the next process.

[0405] Automatic translation and business negotiation support

[0406] Step 1:

[0407] The user enters a text message to initiate a business negotiation into an input form within the application.

[0408] Step 2:

[0409] The terminal sends the entered message to the server.

[0410] Step 3:

[0411] The server processes the received message and calls upon generative artificial intelligence to translate it into appropriate business English.

[0412] Step 4:

[0413] The server sends the translated message as structured data to the API endpoint of an external site.

[0414] Step 5:

[0415] The server receives replies from external sites and uses generative artificial intelligence again to translate those replies into a language that the user can understand.

[0416] Step 6:

[0417] The server sends the translated reply message to the device and displays it to the user through the UX / UI.

[0418] Negotiation history management

[0419] Step 1:

[0420] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[0421] Step 2:

[0422] The server adds metadata (such as timestamps, user IDs, and external site IDs) to the historical data and stores it for future access and analysis.

[0423] Collecting user feedback

[0424] Step 1:

[0425] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[0426] Step 2:

[0427] The device sends feedback information (ratings, comments) to the server as structured data.

[0428] Step 3:

[0429] The server validates the feedback it receives and saves it to the database.

[0430] Step 4:

[0431] The server analyzes the collected feedback and uses it to improve the system.

[0432] Using an Emotion Engine

[0433] Step 1:

[0434] When a user enters a message, the device also sends data that represents the user's emotional state to the server (e.g., linguistic characteristics, facial recognition data, etc.).

[0435] Step 2:

[0436] The server uses an emotion engine to analyze the user's emotional state from the received data.

[0437] Step 3:

[0438] The server uses a generative artificial intelligence to analyze emotions and translate them using appropriate tones and expressions.

[0439] Step 4:

[0440] The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information.

[0441] Specific example

[0442] Step 1:

[0443] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[0444] Step 2:

[0445] The terminal sends input information to the server, and the server stores the received information in a database.

[0446] Step 1:

[0447] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[0448] Step 2:

[0449] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[0450] Step 3:

[0451] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[0452] Step 4:

[0453] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[0454] Step 1:

[0455] User C types "I am very frustrated with the delay" during negotiations.

[0456] Step 2:

[0457] The device sends facial recognition data and voice tone data to the server along with the message.

[0458] Step 3:

[0459] The server uses an emotion engine to recognize user C's emotional state as "frustrated."

[0460] Step 4:

[0461] The server considers the emotional state and translates in an appropriate tone through a generative AI.

[0462] Step 5:

[0463] The server generates the translation "I understand your frustration and will expedite your request." and notifies the terminal.

[0464] (Example 2)

[0465] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0466] When users conduct business negotiations with overseas e-commerce and retail sites, they face challenges such as language barriers, cultural differences, and difficulty in effectively communicating their emotional state. Furthermore, managing negotiation history and collecting feedback is cumbersome. To address these issues, a system is needed that efficiently supports negotiations with overseas sites while considering the user's language abilities and emotional state.

[0467] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0468] In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for translating user messages using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for the user to launch an application and input personal information, means for the terminal to send the input information to the server, means for the server to receive user information, validate it, and store it in a database, means for the terminal to send selection information to the server, means for the server to obtain authentication information for an external API connection based on the received information and make an API request, means for the server to receive the API response, confirm the success or failure of the connection and store it in a database, and means for the server to confirm the connection success. The system includes means for notifying the user of the next possible processing, means for the terminal to send the entered message to the server, means for the server to translate the received message using generative artificial intelligence, means for the server to send the translated message to an external site, means for the server to receive the reply, translate it again, and notify the user, means for the server to store the message history in a database, means for the server to add metadata and store it for future access, means for the terminal to send feedback information to the server, means for the server to validate the feedback and store it in a database, means for the user to also send emotion data when entering a message, means for the server to analyze the emotional state using an emotion engine, means for the server to reflect the analysis results in generative artificial intelligence and perform translation, and means for the server to record the translation result and emotional state and notify the user. This makes it possible for users to conduct business negotiations smoothly across language and cultural differences, and also makes it easier to manage negotiation history and feedback.

[0469] "User" refers to an individual or legal entity that uses the system.

[0470] "Terminal" refers to electronic devices used by users, such as computers, smartphones, and tablets.

[0471] A "server" refers to a computer system that receives requests from users, processes them, and provides the necessary data.

[0472] "Information" refers to all data processed by the system, including personal data entered by users, messages, ratings, and so on.

[0473] "Means of storage" refers to databases, file systems, and other means of temporarily or permanently storing data.

[0474] "External sites" refer to other services on the internet, including online shopping sites and retailer websites.

[0475] "Means of establishing a connection" refers to protocols and API connections used to establish communication with external sites via the internet.

[0476] "Generative artificial intelligence" refers to AI models that use natural language processing and machine learning techniques to automatically generate and translate text.

[0477] "Translation methods" refer to the process of converting text into another language using generative artificial intelligence.

[0478] "Means of transmission" refers to network protocols and communication methods used to send data to a specified destination.

[0479] "Means of notification" refers to in-application notification functions and messaging systems used to convey information to users.

[0480] "Means of saving history" refers to a mechanism for storing records of negotiations and communications within the system.

[0481] "Means of collecting feedback" refers to an interface for obtaining ratings and comments from users.

[0482] An "application" refers to software or mobile applications used by users.

[0483] "Personal information" refers to data unique to each user, such as age, gender, and skills.

[0484] "Validation" refers to the process of verifying whether the entered data conforms to specified formats and conditions.

[0485] An "API request" refers to a request message sent to use the functions of an external website.

[0486] "Response" refers to the response message returned from an external site in response to an API request.

[0487] "Metadata" refers to information about the attributes and structure of data.

[0488] An "emotion engine" refers to software or algorithms used to analyze a user's emotional state.

[0489] "Analysis results" refers to data about emotional states generated by the emotion engine.

[0490] This invention is a system that combines generative AI and an emotion engine to help users effectively conduct business negotiations with overseas e-commerce and retail sites. Communication and processing between the user, terminal, and server enable smooth business negotiations, overcoming language barriers and cultural differences.

[0491] User registration and initial setup

[0492] The user launches the application and enters personal information such as age, gender, and English proficiency. The device sends this information to the server via an HTTP request. The server receives the user information, validates it, and then stores it in a database. This step manages each user's basic profile information.

[0493] Connection with e-commerce sites and retail sites

[0494] The user selects the e-commerce or retail site they wish to connect to via a web interface. The device sends the selection information (site URL, API key, etc.) to the server. Based on the received information, the server obtains authentication information for the external API connection and makes an API request to connect to the external site. The server receives the response to the API request and checks whether the connection was successful. If the connection is successful, the server saves this status to the database and notifies the user that they can proceed to the next step.

[0495] Automatic translation and business negotiation support

[0496] The user enters a text message to initiate a business negotiation into an input form within the application. The device sends this message to the server. The server uses generative AI (e.g., GPT-4) to translate the received message into appropriate business English. The server then sends the translated message to an API endpoint on an external site. The server receives a reply from the external site and again uses generative AI to translate the reply into a language the user can understand. Finally, the server sends the translated reply message to the device to notify the user.

[0497] Negotiation history management

[0498] The server stores a database containing the transmission and reception history of all messages from the start to the end of negotiations. This historical data includes metadata such as timestamps, user IDs, and external site IDs, and is stored for future access and analysis.

[0499] Collecting user feedback

[0500] After the negotiation is complete, the user accesses an interface for providing feedback and enters ratings and comments. The terminal sends the feedback information (ratings, comments) to the server. The server validates the received feedback and stores it in a database. The collected feedback is analyzed and used to improve the system.

[0501] Using an Emotion Engine

[0502] When a user enters a message, the device also sends data representing the user's emotional state (e.g., linguistic features, facial recognition data) to the server. The server uses an emotion engine to analyze the user's emotional state from the received data. This analysis is then reflected in a generative AI, which translates the message using appropriate tone and expression. The server also records the user's emotional state along with the translation and, if necessary, notifies the user of appropriate advice or support information.

[0503] Specific example

[0504] Example 1: User Registration

[0505] When user A uses the app for the first time, they register by entering their age, gender, and English proficiency. The device sends the entered information to the server, and the server stores the received information in a database.

[0506] Example 2: Negotiating with an e-commerce site

[0507] If user B wants to purchase an item from an American e-commerce site and wants to negotiate the price, they type "Can you offer a discount?" and the device sends the message to the server. The server uses generative AI to translate the message and sends it to the e-commerce site in appropriate business English. The server receives the reply from the e-commerce site, translates it into a language the user understands, and notifies the device.

[0508] Example 3: Using an Emotion Engine

[0509] User C types "I am very frustrated with the delay" during negotiations. The device sends facial recognition data and voice tone data along with the message to the server. The server uses its emotion engine to recognize User C's emotional state as "frustrated." The server takes the emotional state into consideration and translates it in an appropriate tone through a generative AI. The server generates the translation "I understand your frustration and will expedite your request" and notifies the device.

[0510] Thus, the present invention is a system that integrates a generative AI and an emotion engine, enabling users to conduct business negotiations more smoothly, transcending language and cultural differences.

[0511] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0512] Step 1: The user launches the application and enters personal information.

[0513] The user launches the application and enters personal information such as age, gender, and English proficiency into an input form. This information is used as part of the user profile. The user's personal data is the input, and the data is passed to the terminal as the output.

[0514] Step 2: The terminal sends the input information to the server.

[0515] The terminal sends the user's entered personal information to the server using an HTTP request. The user's personal information is passed from the terminal as structured data as input, and an HTTP request is sent to the server as output. Specifically, a POST request is used.

[0516] Step 3: The server receives user information, validates it, and saves it to the database.

[0517] The server receives an HTTP request and extracts user data from the payload. Validation checks are performed to verify data format and required fields, and if successful, the data is saved to the database. The input is the HTTP request payload, and the output is the database record. Specifically, an SQL insert query is executed.

[0518] Step 4: The user selects the e-commerce or retail site they want to connect to.

[0519] The user selects the e-commerce or retail site they wish to connect to on the application's interface. This provides the necessary information for the next step.

[0520] Step 5: The device sends the selection information to the server.

[0521] The device sends the URL and API key of the selected site to the server as structured data. The input is the information of the selected site, and the output is an HTTP request sent to the server. Specifically, a POST request is used.

[0522] Step 6: The server obtains authentication information for the external API connection based on the received information and makes an API request.

[0523] The server obtains authentication information for connecting to an external API based on the received information and makes an API request. The input consists of the received information and the API request for obtaining authentication information, and the output is the returned authentication information. Specifically, protocols such as OAuth 2.0 are used.

[0524] Step 7: The server verifies the success or failure of the connection and saves the information to the database.

[0525] The server receives the API response and checks whether the connection was successful. If successful, it saves the connection information and status to the database. The input is the API response, and the output is a record in the database and permission for the next operation. Specifically, an SQL insert query is used.

[0526] Step 8: If the server connection is successful, notify the user that the next step is available.

[0527] If the server successfully connects, it notifies the user of its status. The input is the database connection status, and the output is a message to be sent to the user. Specific methods used include push notifications and email.

[0528] Step 9: The user enters a text message for the opportunity.

[0529] The user enters a text message to initiate a business negotiation into an input form within the application. This becomes the input data for the next step.

[0530] Step 10: The device sends the message to the server.

[0531] The terminal sends the entered message to the server. The input is the user's message, and the output is an HTTP request sent to the server. Specifically, a POST request is used.

[0532] Step 11: The server translates the message using generative artificial intelligence.

[0533] The server translates received messages into appropriate business English using generative artificial intelligence (e.g., GPT-4). The input is the user's message, and the output is the translated text. Specifically, a prompt is passed to the AI ​​model, and the generated response is obtained.

[0534] Step 12: The server sends the translated message to an external site.

[0535] The server sends the translated message as structured data to an API endpoint on an external site. The input is the translated text, and the output is an API request. Specifically, a POST request is used.

[0536] Step 13: The server receives the reply, translates it again, and notifies the user.

[0537] The server receives replies from external websites and uses generative artificial intelligence to translate them into a language the user can understand. The input is the reply from the external website, and the output is the translated text. Specifically, a prompt is passed to the AI ​​model, and the generated response is obtained. The result is then notified to the user.

[0538] Step 14: The server saves the message history to the database.

[0539] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations. The input is the negotiation history, and the output is the recording to the database.

[0540] Step 15: The server adds metadata and saves it for future access.

[0541] The server adds metadata such as timestamps, user IDs, and external site IDs to the stored historical data and saves it for future access and analysis. Historical data is the input, and data with metadata is stored as the output.

[0542] Step 16: Users enter feedback ratings and comments.

[0543] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[0544] Step 17: The device sends feedback information to the server.

[0545] The device sends feedback information (ratings, comments) to the server. User feedback is the input, and an HTTP request is sent to the server as output. Specifically, a POST request is used.

[0546] Step 18: The server validates the feedback and saves it to the database.

[0547] The server validates the received feedback and saves it to the database. Feedback data is the input, and the output is the recording to the database.

[0548] Step 19: Users also send sentiment data when entering messages.

[0549] When a user enters a message, the device also sends data representing the user's emotional state (e.g., linguistic characteristics, facial recognition data) to the server. The input consists of the message and emotional data, and the output is an HTTP request sent to the server.

[0550] Step 20: The server analyzes the emotional state using the emotion engine.

[0551] The server uses an emotion engine to analyze the user's emotional state from the received data. Emotional data is the input, and the analysis results are the output. Specifically, an emotion recognition algorithm is used.

[0552] Step 21: The server reflects the analysis results in the generative artificial intelligence and performs the translation.

[0553] The server incorporates the analysis results into a generative artificial intelligence system, which then performs the translation using appropriate tone and expression. The input consists of the analysis results and the message, and the output is the translated text.

[0554] Step 22: The server records the translation results and sentiment state and notifies the user.

[0555] The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information. The input consists of the translation results and emotional data, and the output generates information to be notified to the user.

[0556] (Application Example 2)

[0557] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0558] In conventional autonomous vehicles, users faced difficulties in smooth negotiation and communication when interacting with foreign e-commerce sites or support services due to language barriers and differences in how emotions are conveyed. Furthermore, the systems managing these interactions simply translated messages without considering the user's emotional state, resulting in a decline in the quality and efficiency of communication.

[0559] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for translating user messages using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for analyzing the user's emotional state using an emotion engine, and means for adjusting the tone of messages based on the analysis results. This enables the user to effectively conduct business negotiations and communication with foreign e-commerce sites and support services.

[0560] "Means of saving information received from users" refers to a function that saves data entered by the user to a storage device such as a server, making it accessible and usable later.

[0561] "Means of establishing connections with external sites" refers to a function that allows communication with external websites and services using authentication information.

[0562] "A means of translating user messages using generative artificial intelligence" refers to a function that uses generative AI to convert text entered by a user into another language.

[0563] "Means for sending translated messages to external sites" refers to a function that sends translated messages to external websites or services.

[0564] "A means of translating and notifying users of replies from external sites" refers to a function that translates messages obtained from external sites into a language that the user can understand and notifies the user of that translation.

[0565] "Means for saving negotiation history" refers to a function that records and saves the negotiation interactions that a user has had.

[0566] "Means for collecting and saving feedback" refers to a function for collecting, recording, and saving ratings and comments provided by users.

[0567] "Methods for analyzing a user's emotional state using an emotion engine" refers to technologies that identify and evaluate a user's emotions based on the user's input data and characteristics.

[0568] "Means of adjusting the tone of a message based on analysis results" refers to a function that appropriately modifies and adjusts the tone and expression of a message based on the results of the emotion engine's analysis.

[0569] System Overview

[0570] This invention is a system that enables users to smoothly conduct business negotiations and communication with overseas e-commerce sites and support services. This system is primarily composed of an application installed on the user interface of an autonomous vehicle. Specifically, it works by linking generative artificial intelligence and an emotion engine to translate and analyze the sentiment of user messages, then sends the translation results to external sites in an appropriate tone, and provides replies from external sites in a format that the user can understand.

[0571] Hardware and software configuration

[0572] hardware

[0573] Terminal: Onboard computer installed in an autonomous vehicle

[0574] Server: Information processing server located on the cloud.

[0575] Input devices: Interface devices with touch panels or voice input capabilities.

[0576] Communication device: A mobile communication device that enables internet connectivity.

[0577] software

[0578] Generative artificial intelligence (generative AI models): Natural language processing models for translating user messages (e.g., Helsinki-NLP / opus-mt-ja-en)

[0579] Emotion engine: An emotion analysis model for analyzing user emotions (e.g., the emotion analysis pipeline in Transformers).

[0580] Database Management System: A server-based RDBMS that manages user information, negotiation history, and feedback records.

[0581] API Integration Module: A program module for managing communication with external sites.

[0582] System Operation Description

[0583] 1. User information registration and initial setup

[0584] The user activates the in-car terminal and enters personal information such as age, gender, and English language skills.

[0585] The terminal sends the entered user information to the server via an HTTP request, and the server receives the information and stores it in the database.

[0586] 2. External site connection

[0587] The user selects the e-commerce site or support service they want to connect to.

[0588] The device sends the URL and API key of the selected site to the server, which receives this information, obtains authentication information to connect to the external site, and establishes the connection.

[0589] 3. Translate and send messages

[0590] The user enters "I want to change my destination midway" in Japanese.

[0591] The terminal sends this input message to the server, which then uses generative artificial intelligence (generative AI model) to translate it into English.

[0592] The translation result is analyzed using an emotion engine to reflect the user's emotional state and result in "I want to change the destination midway."

[0593] Send the translated message to an external website.

[0594] 4. Reply from an external site

[0595] The server receives replies from external websites and uses generative artificial intelligence to translate them back into Japanese.

[0596] For example, if the reply from an external site is "Sure, please provide the new destination address," it will be translated as "Of course, please provide the new destination address."

[0597] The device will notify the user of the translation result.

[0598] 5. Managing History and Feedback

[0599] The server records all negotiation interactions in a database, making them available for later reference.

[0600] Users provide feedback after the negotiation is complete, and the server collects and stores that feedback.

[0601] Specific example

[0602] User example

[0603] When a user enters "I want to change my destination midway," the following prompt is sent to the AI ​​model:

[0604] "I want to change the destination mid-way"

[0605] Example of a prompt

[0606] text

[0607] I want to change the destination mid-way

[0608] This will enable users to smoothly conduct complex negotiations and communications in foreign countries, significantly improving the experience inside autonomous vehicles.

[0609] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0610] Step 1:

[0611] User information registration and initial setup

[0612] Users enter personal information such as age, gender, and English language skills into an in-vehicle terminal.

[0613] The terminal sends the input data to the server via an HTTP request.

[0614] The server validates the received data and saves it to the database.

[0615] Input: Personal information entered by the user (age, gender, English proficiency, etc.)

[0616] Output: User information stored in the database

[0617] Function: This manages each user's basic profile information.

[0618] Step 2:

[0619] External site connection settings

[0620] The user selects the e-commerce site or support service they want to connect to using the in-car terminal.

[0621] The device sends selection information (site URL, API key, etc.) to the server.

[0622] The server obtains authentication information for connecting to an external API and makes a request to connect to the external site.

[0623] Input: User-selected site URL and API key

[0624] Output: Success or failure of external site connection

[0625] Operation: The server checks the connection status, saves it to the database, and notifies the user.

[0626] Step 3:

[0627] User message input and translation

[0628] The user enters their negotiation message into the input form on the in-vehicle terminal.

[0629] The terminal sends the input message to the server.

[0630] The server invokes a generative AI model to translate the message into business English.

[0631] Input: Negotiation message entered by the user

[0632] Output: Translated business English message

[0633] Function: Uses generative artificial intelligence to translate messages into appropriate business terminology.

[0634] Step 4:

[0635] Emotion analysis and tone adjustment

[0636] The server analyzes the user's input messages using an emotion engine to identify the user's emotional state.

[0637] Based on the emotion analysis results, the tone is adjusted and a refined message is generated.

[0638] Input: Translated business English message, analyzed sentiment

[0639] Output: A reconciled business English message

[0640] Function: Appropriately adjusts the tone and expression of the message according to the emotional state.

[0641] Step 5:

[0642] Sending a translated message

[0643] The server sends a pre-configured message to an external site.

[0644] The server retrieves the results received from external websites.

[0645] Input: A pre-formatted business English message

[0646] Output: Response message from an external site

[0647] Operation: Send a message and receive a response.

[0648] Step 6:

[0649] Translation of replies from external sites

[0650] The server generates reply messages from external websites and uses an AI model to re-translate them into Japanese.

[0651] The device receives this Japanese translated reply message and notifies the user.

[0652] Input: Reply message from an external site

[0653] Output: Reply message translated into Japanese

[0654] Function: Translates incoming messages and notifies the user.

[0655] Step 7:

[0656] History and Feedback Management

[0657] The server saves all message exchanges from the start to the end of negotiations to a database.

[0658] Users provide feedback after the negotiation is complete, and the server stores it.

[0659] Input: Negotiation history, user feedback

[0660] Output: Negotiation history and feedback stored in the database

[0661] Function: Manages history and feedback, making it available for later reference.

[0662] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0663] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0664] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0665] [Second Embodiment]

[0666] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0667] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0668] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0669] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0670] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0671] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0672] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0673] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0674] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0675] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0676] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0677] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0678] This invention is a system that uses generative AI to help users conduct smooth business negotiations with overseas e-commerce sites and retail sites. The processing of the system's program is described in detail below.

[0679] User registration and initial setup

[0680] 1. The user launches the application and enters personal information such as age, gender, and English language skills.

[0681] 2. The terminal sends the entered information to the server.

[0682] 3. The server receives user information, validates it, and then saves it to the database. This step allows the system to manage basic profile information for each user.

[0683] Connection with e-commerce sites and retail sites

[0684] 1. Utilize an interface that allows users to select the e-commerce or retail site they wish to connect to.

[0685] 2. The device sends the selected site information (such as URL and API key) to the server.

[0686] 3. Based on the information received by the server, it establishes a connection with an external site using APIs and communication protocols.

[0687] 4. The server checks whether the connection was successful and saves the connection status to the database.

[0688] Automatic translation and business negotiation support

[0689] 1. Enter a message for the user to initiate negotiations within the application.

[0690] 2. The terminal sends the entered message to the server.

[0691] 3. The server uses generative artificial intelligence to translate the input message into appropriate business English.

[0692] 4. The server sends the translated message to the e-commerce site and proceeds with the negotiation.

[0693] 5. The server receives the reply from the e-commerce site, translates it into a language the user can understand, and notifies the user.

[0694] 6. The device displays the translated reply and waits for the user to enter their reply again. By repeating this process, the user can negotiate smoothly.

[0695] Negotiation history management

[0696] 1. The server stores the entire negotiation history in a database. This includes all sent and received messages, as well as various metadata (such as timestamps).

[0697] 2. This historical data will be stored for future analysis and training purposes.

[0698] Collecting user feedback

[0699] 1. After the negotiation is complete, the user will have access to an interface to provide feedback.

[0700] 2. The device sends feedback information (ratings and comments) to the server.

[0701] 3. The server saves the feedback to a database so that it can be used for future system improvements.

[0702] Specific example

[0703] Example 1: User Registration

[0704] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[0705] The terminal sends input information to the server, and the server stores the received information in a database.

[0706] Example 2: Negotiating with an e-commerce site

[0707] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[0708] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[0709] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[0710] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[0711] In this way, the present invention is a system that enables users to conduct business negotiations smoothly, transcending language and cultural differences.

[0712] The following describes the processing flow.

[0713] User registration and initial setup

[0714] Step 1:

[0715] The user launches the application and enters personal information such as age, gender, and English language skills.

[0716] Step 2:

[0717] The terminal sends the entered information to the server via an HTTP request.

[0718] Step 3:

[0719] The server receives user information and validates the input data, checking for any inappropriate data.

[0720] Step 4:

[0721] The server establishes a database connection and saves user information that has passed validation to the database.

[0722] Connection with e-commerce sites and retail sites

[0723] Step 1:

[0724] Users select the e-commerce or retail site they want to connect to via a web interface.

[0725] Step 2:

[0726] The device sends selected information (site URL, API key, etc.) to the server as structured data.

[0727] Step 3:

[0728] Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[0729] Step 4:

[0730] The server receives the API request response and checks whether the connection was successful.

[0731] Step 5:

[0732] The server saves the connection status to the database, and if the connection is successful, it notifies the user that the system can proceed to the next step.

[0733] Automatic translation and business negotiation support

[0734] Step 1:

[0735] The user enters a text message to initiate a business negotiation into an input form within the application.

[0736] Step 2:

[0737] The terminal sends the entered message to the server.

[0738] Step 3:

[0739] The server processes the received message and calls upon generative artificial intelligence to translate it into appropriate business English.

[0740] Step 4:

[0741] The server sends the translated message as structured data to the API endpoint of an external site.

[0742] Step 5:

[0743] The server receives replies from external sites and uses generative artificial intelligence again to translate those replies into a language that the user can understand.

[0744] Step 6:

[0745] The server sends the translated reply message to the device and displays it to the user through the UX / UI.

[0746] Negotiation history management

[0747] Step 1:

[0748] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[0749] Step 2:

[0750] The server adds metadata (such as timestamps, user IDs, and external site IDs) to the historical data and stores it for future access and analysis.

[0751] Collecting user feedback

[0752] Step 1:

[0753] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[0754] Step 2:

[0755] The device sends feedback information (ratings, comments) to the server as structured data.

[0756] Step 3:

[0757] The server validates the feedback it receives and saves it to the database.

[0758] Step 4:

[0759] The server analyzes the collected feedback and uses it to improve the system.

[0760] (Example 1)

[0761] Next, we will describe Example 1. 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".

[0762] Conducting smooth business negotiations with overseas e-commerce and retail sites can be difficult due to language and cultural differences. Furthermore, manual translation by users and subsequent negotiations with external sites is time-consuming and laborious. Managing negotiation history and feedback is also cumbersome and inefficient. This invention aims to provide a system to solve these problems.

[0763] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0764] In this invention, the server includes means for storing information received from the user, means for transmitting information entered by the terminal to the server, means for the server to receive user information, validate it, and store it in a database, means for the user to select an external site they wish to connect to, means for the terminal to transmit selected site information (such as URL and API key) to the server, means for the server to establish a connection with the external site and store the connection status in a database, means for translating user messages using a generative artificial intelligence model, means for sending the translated messages to the external site, means for translating replies from the external site into the user's native language and notifying them, means for storing the negotiation history in a database, means for the user to provide feedback after the negotiation is completed, and means for collecting and storing the feedback. This enables users to efficiently conduct business negotiations across language barriers and effectively manage negotiation history and feedback.

[0765] A "user" refers to an individual or legal entity that uses the system to conduct business negotiations with overseas e-commerce sites and retail sites.

[0766] A "terminal" refers to an electronic device used by a user to input information and send and receive data to and from a server.

[0767] A "server" refers to a computer system that processes information received from users and stores it in a database.

[0768] A "database" refers to a system for structuring and storing various types of data, such as user information, connection status, negotiation history, and feedback.

[0769] "Validation" refers to the process of verifying the validity of information entered by a user.

[0770] "External sites" refer to e-commerce sites and retail sites that users connect to and conduct business negotiations with.

[0771] A "URL" refers to address information used to establish a connection to an external website.

[0772] An "API key" refers to the authentication information required to access an API on an external website.

[0773] "Generative artificial intelligence models" refer to AI technologies used for translating user messages and replies.

[0774] "Translation" refers to the process of converting a message entered by a user into another language.

[0775] A "message" refers to the text information that a user enters to conduct negotiations.

[0776] "Connection status" refers to information regarding the success or failure of the connection to an external site.

[0777] "Negotiation history" refers to all messages sent and received during the negotiation process, along with their associated metadata.

[0778] "Feedback" refers to the evaluations and comments that users provide after the negotiation has concluded.

[0779] This invention provides a system that assists users in smoothly conducting business negotiations with overseas e-commerce and retail sites. This system enables users to efficiently conduct business negotiations through user information input and storage, connection to external sites, translation assistance using AI generation, negotiation history management, and feedback collection and storage.

[0780] User registration and initial setup

[0781] The user launches the application and enters personal information such as age, gender, and English proficiency. This information is sent from the device to the server. The server validates the received information and stores it in a database. MySQL is a suitable database to use.

[0782] Connection with e-commerce sites and retail sites

[0783] The system utilizes an interface where the user selects the e-commerce or retail site they wish to connect to. The terminal sends the selected site information (such as URL and API key) to the server. Based on the received information, the server establishes a connection with the external site using an API or communication protocol (e.g., REST API), verifies the success or failure of the connection, and saves the connection status to a database.

[0784] Automatic translation and business negotiation support

[0785] The user enters a message to initiate negotiations within the application. The device sends the entered message to the server. The server uses generative artificial intelligence (e.g., GPT-4) to translate the entered message into appropriate business English. The translated message is sent to the e-commerce site to proceed with the negotiations. The server receives a reply from the e-commerce site, translates it into a language the user understands, and notifies the device. The device displays the translated reply and waits for the user to enter another reply. By repeating this process, the user can conduct negotiations smoothly.

[0786] Negotiation history management

[0787] The server stores the entire negotiation history in a database. This includes all sent and received messages, as well as various metadata (such as timestamps). PostgreSQL is a suitable database. This makes the negotiation history available for future analysis and training purposes.

[0788] Collecting user feedback

[0789] After the negotiation is complete, the user accesses an interface to provide feedback. The device sends feedback information (ratings and comments) to the server. The server stores the feedback in a database and makes it available for future system improvements.

[0790] Specific example

[0791] Example 1: User Registration

[0792] When user A uses the app for the first time, they register by entering their age (e.g., 28), gender (e.g., male), and English proficiency (e.g., intermediate). The device sends this information to the server, and the server stores the received information in a database.

[0793] Example 2: Negotiating with an e-commerce site

[0794] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[0795] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[0796] The server sends a message to a generative AI (e.g., GPT-4), which translates it into appropriate business English. The translated message is then sent to the e-commerce site.

[0797] The system receives a reply from an e-commerce site (e.g., "We can offer a 10% discount.") and uses a generative AI model to translate it into the user's native language. The translated reply is sent to the device, which then displays it to the user.

[0798] Example of a prompt

[0799] "Please explain the transmission process for saving User A's personal information to the database."

[0800] "Please describe the message sending and translation process when User B initiates price negotiations on an e-commerce site."

[0801] In this way, the present invention is a system that enables users to overcome language barriers and conduct business negotiations efficiently.

[0802] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0803] Step 1:

[0804] The user launches the application and enters personal information such as age, gender, and English proficiency. Specifically, the user enters information into a form within the app and presses the "Submit" button.

[0805] Input: Personal information entered by the user (age, gender, English proficiency)

[0806] Output: Personal information sent to the server by the terminal

[0807] Step 2:

[0808] The terminal sends the entered information to the server. Specifically, it converts the input data into JSON format and sends it to the server as an HTTP request.

[0809] Input: Personal information entered by the user (in JSON format)

[0810] Output: Personal information passed to the server

[0811] Step 3:

[0812] The server receives user information and performs validation. Specifically, it checks the validity of the received information (e.g., whether age is a numerical value, whether gender is a valid option, whether English skills are within a certain range).

[0813] Input: User information sent from the device

[0814] Output: Validated user information

[0815] Step 4:

[0816] The server saves user information that has passed validation to the database. Specifically, it inserts the information into the MySQL database using an SQL query.

[0817] Input: Validated user information

[0818] Output: User information stored in the database

[0819] Step 5:

[0820] The interface utilizes a selection process where the user chooses the external site they want to connect to. Specifically, the user selects a site from a dropdown menu or search box and then clicks the "Connect" button.

[0821] Input: Information about the selected external website (URL, API key, etc.)

[0822] Output: External site information sent to the server by the terminal.

[0823] Step 6:

[0824] The device sends information from the selected external website to the server. Specifically, it sends the selected information to the server as an HTTP request in JSON format.

[0825] Input: Selected external website information (JSON format)

[0826] Output: External site information passed to the server

[0827] Step 7:

[0828] Based on the external site information received by the server, it establishes a connection with the external site using an API or communication protocol (e.g., REST API). Specifically, it sets the HTTP headers and request body using the received URL and API key, and sends a request to the API endpoint.

[0829] Input: External site information (URL, API key, etc.)

[0830] Output: Establishing a connection with an external site

[0831] Step 8:

[0832] The server checks whether the connection was successful and saves the status to the database. Specifically, it receives the response to the API request, checks the success status code (e.g., 200 OK), and records the status information in the database.

[0833] Input: API request response

[0834] Output: Connection status stored in the database

[0835] Step 9:

[0836] The user enters a message to initiate negotiations within the app. Specifically, they type a message in the chat window and press the "Send" button.

[0837] Input: Message entered by the user

[0838] Output: Message sent from the terminal to the server

[0839] Step 10:

[0840] The terminal sends the entered message to the server. Specifically, it sends the message to the server as an HTTP request in text format.

[0841] Input: User-entered message (text format)

[0842] Output: Message passed to the server

[0843] Step 11:

[0844] The server uses a generative artificial intelligence model (e.g., GPT-4) to translate the input message. Specifically, it sends the received message as a prompt to the generative AI model and obtains the translated text.

[0845] Input: Message entered by the user

[0846] Output: Translated message

[0847] Step 12:

[0848] The server sends the translated message to an external site. Specifically, it sets the translated text in the body of an API request and sends it to the external site's API endpoint.

[0849] Input: Translated message

[0850] Output: Translated message sent to an external site

[0851] Step 13:

[0852] The server receives replies from external websites, translates them into the user's native language, and notifies them. Specifically, it sends the reply message to an AI model that generates translations and retrieves the translation results.

[0853] Input: Reply message from an external site

[0854] Output: Translated reply message

[0855] Step 14:

[0856] The device displays the translated reply and waits for the user to type another reply. Specifically, it displays the translated text in the chat window and re-enables the interface for entering a new message.

[0857] Input: Translated reply message

[0858] Output: Translated message displayed to the user

[0859] Step 15:

[0860] The server saves the entire negotiation history to a database. It stores all sent messages and replies, as well as various metadata (such as timestamps). Specifically, it inserts messages and metadata into a PostgreSQL database using SQL queries.

[0861] Input: Negotiation history information (messages and metadata)

[0862] Output: Negotiation history stored in the database

[0863] Step 16:

[0864] After the negotiation is complete, the user accesses an interface to provide feedback. Specifically, they enter their rating and comments into the feedback form and press the "Submit" button.

[0865] Input: Feedback information (ratings and comments)

[0866] Output: Feedback sent from the terminal to the server

[0867] Step 17:

[0868] The device sends feedback information to the server. Specifically, it sends feedback data to the server in JSON format.

[0869] Input: Feedback information (JSON format)

[0870] Output: Feedback information passed to the server

[0871] Step 18:

[0872] The server saves the feedback to the database. Specifically, it inserts the feedback data into the database using an SQL query.

[0873] Input: Feedback Information

[0874] Output: Feedback information stored in the database

[0875] (Application Example 1)

[0876] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0877] When users conduct business negotiations with overseas e-commerce and retail sites, language barriers and communication obstacles are a major challenge. Furthermore, there is a need to efficiently manage these negotiation histories and feedback to improve the user's negotiation experience. Conventional systems have not consistently achieved these functions, placing a heavy burden on users, thus creating a need for a more efficient and smoother negotiation support system.

[0878] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0879] In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for appropriately translating user messages into business terminology using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for storing user registration information in a database and accessing it later, means for sending automatically translated messages to the site and receiving responses, and means for storing negotiation history in a database. As a result, users can overcome language barriers and smoothly conduct business negotiations with overseas e-commerce sites, and negotiation history and feedback can also be managed efficiently.

[0880] A "user" is an individual or legal entity that uses this system to conduct business negotiations with overseas e-commerce sites and retail sites.

[0881] "Information" refers to all data entered by users, including personal information, negotiation messages, and feedback.

[0882] "External sites" refer to online platforms that users use for negotiations, such as e-commerce sites and retail sites.

[0883] "Means of establishing a connection" refers to technologies that use APIs and communication protocols to initiate communication with external sites and create a state where data exchange is possible.

[0884] "Generative artificial intelligence" is an AI technology that uses natural language processing to translate user messages into appropriate business English.

[0885] "Translation methods" refer to technologies that utilize generative artificial intelligence to convert user-inputted messages into other languages.

[0886] A "database" is a system for efficiently storing and managing data such as user information, negotiation history, and feedback.

[0887] "Means for receiving responses" refers to technologies for receiving reply messages from external sites, loading them into a server, and notifying the user.

[0888] "Negotiation history" refers to a record of all business negotiations conducted by the user, including data such as sent messages, translated messages, received messages, and timestamps.

[0889] This invention is a system that uses generative artificial intelligence to help users conduct smooth business negotiations with overseas e-commerce sites and retail sites. A detailed embodiment of the system is described below.

[0890] System Configuration

[0891] This system primarily consists of three entities: servers, terminals, and users. The processes performed by each entity, as well as the hardware and software they use, are described in detail below.

[0892] User registration and initial setup

[0893] Users launch the application using their device (smartphone, PC, etc.) and enter personal information such as age, gender, and English language skills. The device sends the collected information to the server, which validates it and then stores it in a database. This allows for the management of the user's basic profile information.

[0894] Connection with e-commerce sites and retail sites

[0895] The user selects the e-commerce or retail site they wish to connect to via the terminal's interface. The selected site information (such as URL and API key) is sent from the terminal to the server, which then establishes a connection with the external site using APIs and communication protocols. The success or failure of the connection is stored in a database.

[0896] Automatic translation and business negotiation support

[0897] The user enters a message from their device to initiate negotiations. The device sends this message to the server, which uses generative artificial intelligence to translate the message into appropriate business English. The translated message is then sent to an external website. The server receives the reply from the external website, translates it into a language the user understands, and notifies the user of the reply on their device.

[0898] Negotiation history management

[0899] The server stores the entire negotiation history in a database. This history includes all sent and received messages, as well as various metadata (such as timestamps). This data is used for future analysis and system training.

[0900] Collecting user feedback

[0901] After negotiations are complete, users provide feedback through their devices. The devices send feedback information (ratings and comments) to the server, which stores it in a database. The collected feedback is used to improve the system.

[0902] Hardware and software to use

[0903] Server: Handles data storage, processing of generated AI models, API connections, and database management.

[0904] Terminal: As a user interface, it is responsible for message input and display. Smartphones and PCs are the main hardware examples.

[0905] Generative AI model: Used to translate user messages into business English. Leverages natural language processing software such as the Google Trans library.

[0906] Examples of specifics and prompts

[0907] Specific example 1:

[0908] When user A uses the app for the first time, they register by entering their age, gender, and English proficiency. The device sends this information to the server, and the server stores the received information in a database.

[0909] Specific example 2:

[0910] User B wants to purchase an item from an American e-commerce site and types "Can you offer a discount?". The server uses generative AI to translate the message, sends it to the e-commerce site in appropriate business English, and then translates the reply into a language the user understands and notifies them.

[0911] Example of a Generative AI Model prompt:

[0912] Original text: "What is the product's stock status?"

[0913] Prompt: Translate the following sentence into business English: 'What is the product's stock status?'

[0914] Translated text: "Could you please update me on the availability of the product?"

[0915] In this way, the system enables users to conduct business negotiations smoothly, transcending language and cultural barriers.

[0916] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0917] Step 1:

[0918] The user uses their device and launches the application. The user enters personal information such as age, gender, and English proficiency, and submits it by clicking the save button.

[0919] Input: Personal information such as age, gender, and English language skills.

[0920] Output: Sent user information.

[0921] Specific operation: After the user enters information and taps the "Send" button, the device sends that information to the server.

[0922] Step 2:

[0923] The server receives user information sent from the terminal. The server validates the data and saves the information to the database.

[0924] Input: Submitted user information.

[0925] Output: User information saved as a result of validation.

[0926] Specific operation: The server checks the received data to verify that there is no invalid data. Then, it saves it to the database.

[0927] Step 3:

[0928] The user selects the external site they want to connect to (such as an e-commerce site or a retail site) using the device's interface.

[0929] Input: Information about the external website you want to connect to (such as URL or API key).

[0930] Output: Information from the selected external website.

[0931] Specific operation: The user selects an external site from a dropdown list or search function and taps the "Connect" button.

[0932] Step 4:

[0933] The device sends information about the selected external website to the server. The server then uses this information to establish a connection using APIs and communication protocols.

[0934] Input: Information from the selected external website.

[0935] Output: Success or failure of the connection.

[0936] Specific operation: The server, upon receiving information sent from the terminal, attempts to connect to an external site, determines whether the connection was successful or unsuccessful, and saves the success or failure to a database.

[0937] Step 5:

[0938] Enter a message on your device to initiate negotiations.

[0939] Input: A message to initiate negotiations.

[0940] Output: The input message.

[0941] Specific action: The user enters a negotiation message and taps the "Send" button.

[0942] Step 6:

[0943] The terminal sends the entered message to the server. The server uses generative artificial intelligence to translate the message into appropriate business English.

[0944] Input: The message entered by the user.

[0945] Output: Translated business English message.

[0946] Specific operation: The server receives the input message and performs translation using a generative AI model (e.g., the Google Trans library).

[0947] Step 7:

[0948] The server sends the translated message to an external site.

[0949] Input: Translated business English message.

[0950] Output: Message sent to an external site.

[0951] Specific operation: The server sends the translated message by calling an API on an external site.

[0952] Step 8:

[0953] The server receives a reply from an external website. It translates the reply into a language the user understands and notifies the device.

[0954] Input: Reply message from an external website.

[0955] Output: Translated reply message.

[0956] Specific operation: The server receives a reply message, translates it using a generation AI model, and sends it to the terminal.

[0957] Step 9:

[0958] The server saves the entire negotiation history to a database.

[0959] Input: Negotiation history including sent messages, replied messages, and timestamps.

[0960] Output: Saved negotiation history.

[0961] Specific operation: The server records all negotiation details in a database.

[0962] Step 10:

[0963] Users provide feedback via their devices after the negotiation is complete.

[0964] Input: Feedback information such as ratings and comments.

[0965] Output: Sent feedback information.

[0966] Specific action: The user fills out a feedback form and taps the "Submit" button.

[0967] Step 11:

[0968] The device sends feedback information to the server. The server stores it in its database.

[0969] Input: Submitted feedback information.

[0970] Output: Saved feedback information.

[0971] Specific operation: The server receives feedback information sent from the terminal and saves it to the database.

[0972] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0973] This invention is a system that combines generative AI and an emotion engine to help users conduct more effective business negotiations with overseas e-commerce and retail sites. The system's program processing is described in detail below.

[0974] User registration and initial setup

[0975] 1. The user launches the application and enters personal information such as age, gender, and English language skills.

[0976] 2. The terminal sends the entered information to the server via an HTTP request.

[0977] 3. The server receives user information, validates the input data, and then saves it to the database. This step manages the basic profile information of each user.

[0978] Connection with e-commerce sites and retail sites

[0979] 1. The user selects the e-commerce or retail site they wish to connect to via the web interface.

[0980] 2. The device sends the selected information (site URL, API key, etc.) to the server as structured data.

[0981] 3. Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[0982] 4. The server receives the API request response and checks whether the connection was successful.

[0983] 5. The server saves the connection status to the database and, if the connection is successful, notifies the user that the system can proceed to the next process.

[0984] Automatic translation and business negotiation support

[0985] 1. The user enters a text message to initiate a business negotiation into an input form within the application.

[0986] 2. The terminal sends the entered message to the server.

[0987] 3. The server processes the received message and calls a generative artificial intelligence to translate it into appropriate business English.

[0988] 4. The server sends the translated message as structured data to the API endpoint of the external site.

[0989] 5. The server receives the reply from the external site and uses generative artificial intelligence again to translate the reply into a language that the user can understand.

[0990] 6. The server sends the translated reply message to the terminal and displays it to the user through the UX / UI.

[0991] Negotiation history management

[0992] 1. The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[0993] 2. The server adds metadata (timestamp, user ID, external site ID, etc.) to the historical data and stores it for future access and analysis.

[0994] Collecting user feedback

[0995] 1. After the negotiation is complete, the user accesses an interface for providing feedback and enters their rating and comments.

[0996] 2. The device sends feedback information (ratings, comments) to the server as structured data.

[0997] 3. The server validates the feedback it receives and saves it to the database.

[0998] 4. The server analyzes the collected feedback and uses it to improve the system.

[0999] Using an Emotion Engine

[1000] 1. When a user enters a message, the device also sends data representing the user's emotional state to the server (e.g., linguistic characteristics, facial recognition data).

[1001] 2. The server uses an emotion engine to analyze the user's emotional state from the received data.

[1002] 3. The server reflects the results of the emotional analysis into the generative artificial intelligence, which then performs the translation using appropriate tone and expression.

[1003] 4. The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information.

[1004] Specific example

[1005] Example 1: User Registration

[1006] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[1007] The terminal sends input information to the server, and the server stores the received information in a database.

[1008] Example 2: Negotiating with an e-commerce site

[1009] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[1010] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[1011] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[1012] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[1013] Example 3: Using an Emotion Engine

[1014] User C types "I am very frustrated with the delay" during negotiations.

[1015] The device sends facial recognition data and voice tone data to the server along with the message.

[1016] The server uses an emotion engine to recognize user C's emotional state as "frustrated."

[1017] The server considers the emotional state and translates in an appropriate tone through a generative AI.

[1018] The server generates the translation "I understand your frustration and will expedite your request." and notifies the terminal.

[1019] Thus, the present invention is a system that integrates a generative AI and an emotion engine, enabling users to conduct business negotiations more smoothly, transcending language and cultural differences.

[1020] The following describes the processing flow.

[1021] User registration and initial setup

[1022] Step 1:

[1023] The user launches the application and enters personal information such as age, gender, and English language skills.

[1024] Step 2:

[1025] The terminal sends the entered information to the server via an HTTP request.

[1026] Step 3:

[1027] The server receives user information and validates the input data, checking for any inappropriate data.

[1028] Step 4:

[1029] The server establishes a database connection and saves user information that has passed validation to the database.

[1030] Connection with e-commerce sites and retail sites

[1031] Step 1:

[1032] Users select the e-commerce or retail site they want to connect to via a web interface.

[1033] Step 2:

[1034] The device sends selected information (site URL, API key, etc.) to the server as structured data.

[1035] Step 3:

[1036] Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[1037] Step 4:

[1038] The server receives the API request response and checks whether the connection was successful.

[1039] Step 5:

[1040] The server saves the connection status to the database and, if the connection is successful, notifies the user that the system can proceed to the next process.

[1041] Automatic translation and business negotiation support

[1042] Step 1:

[1043] The user enters a text message to initiate a business negotiation into an input form within the application.

[1044] Step 2:

[1045] The terminal sends the entered message to the server.

[1046] Step 3:

[1047] The server processes the received message and calls upon generative artificial intelligence to translate it into appropriate business English.

[1048] Step 4:

[1049] The server sends the translated message as structured data to the API endpoint of an external site.

[1050] Step 5:

[1051] The server receives replies from external sites and uses generative artificial intelligence again to translate those replies into a language that the user can understand.

[1052] Step 6:

[1053] The server sends the translated reply message to the device and displays it to the user through the UX / UI.

[1054] Negotiation history management

[1055] Step 1:

[1056] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[1057] Step 2:

[1058] The server adds metadata (such as timestamps, user IDs, and external site IDs) to the historical data and stores it for future access and analysis.

[1059] Collecting user feedback

[1060] Step 1:

[1061] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[1062] Step 2:

[1063] The device sends feedback information (ratings, comments) to the server as structured data.

[1064] Step 3:

[1065] The server validates the feedback it receives and saves it to the database.

[1066] Step 4:

[1067] The server analyzes the collected feedback and uses it to improve the system.

[1068] Using an Emotion Engine

[1069] Step 1:

[1070] When a user enters a message, the device also sends data that represents the user's emotional state to the server (e.g., linguistic characteristics, facial recognition data, etc.).

[1071] Step 2:

[1072] The server uses an emotion engine to analyze the user's emotional state from the received data.

[1073] Step 3:

[1074] The server uses a generative artificial intelligence to analyze emotions and translate them using appropriate tones and expressions.

[1075] Step 4:

[1076] The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information.

[1077] Specific example

[1078] Step 1:

[1079] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[1080] Step 2:

[1081] The terminal sends input information to the server, and the server stores the received information in a database.

[1082] Step 1:

[1083] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[1084] Step 2:

[1085] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[1086] Step 3:

[1087] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[1088] Step 4:

[1089] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[1090] Step 1:

[1091] User C types "I am very frustrated with the delay" during negotiations.

[1092] Step 2:

[1093] The device sends facial recognition data and voice tone data to the server along with the message.

[1094] Step 3:

[1095] The server uses an emotion engine to recognize user C's emotional state as "frustrated."

[1096] Step 4:

[1097] The server considers the emotional state and translates in an appropriate tone through a generative AI.

[1098] Step 5:

[1099] The server generates the translation "I understand your frustration and will expedite your request." and notifies the terminal.

[1100] (Example 2)

[1101] Next, we will describe Example 2. 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".

[1102] When users conduct business negotiations with overseas e-commerce and retail sites, they face challenges such as language barriers, cultural differences, and difficulty in effectively communicating their emotional state. Furthermore, managing negotiation history and collecting feedback is cumbersome. To address these issues, a system is needed that efficiently supports negotiations with overseas sites while considering the user's language abilities and emotional state.

[1103] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1104] In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for translating user messages using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for the user to launch an application and input personal information, means for the terminal to send the input information to the server, means for the server to receive user information, validate it, and store it in a database, means for the terminal to send selection information to the server, means for the server to obtain authentication information for an external API connection based on the received information and make an API request, means for the server to receive an API response, confirm the success or failure of the connection and store it in a database, and means for the server to confirm the connection success. The system includes means for notifying the user of the next possible processing, means for the terminal to send the entered message to the server, means for the server to translate the received message using generative artificial intelligence, means for the server to send the translated message to an external site, means for the server to receive the reply, translate it again, and notify the user, means for the server to store the message history in a database, means for the server to add metadata and store it for future access, means for the terminal to send feedback information to the server, means for the server to validate the feedback and store it in a database, means for the user to also send emotion data when entering a message, means for the server to analyze the emotional state using an emotion engine, means for the server to reflect the analysis results in generative artificial intelligence and perform translation, and means for the server to record the translation result and emotional state and notify the user. This makes it possible for users to conduct business negotiations smoothly across language and cultural differences, and also makes it easier to manage negotiation history and feedback.

[1105] "User" refers to an individual or legal entity that uses the system.

[1106] "Terminal" refers to electronic devices used by users, such as computers, smartphones, and tablets.

[1107] A "server" refers to a computer system that receives requests from users, processes them, and provides the necessary data.

[1108] "Information" refers to all data processed by the system, including personal data entered by users, messages, ratings, and so on.

[1109] "Means of storage" refers to databases, file systems, and other means of temporarily or permanently storing data.

[1110] "External sites" refer to other services on the internet, including online shopping sites and retailer websites.

[1111] "Means of establishing a connection" refers to protocols and API connections used to establish communication with external sites via the internet.

[1112] "Generative artificial intelligence" refers to AI models that use natural language processing and machine learning techniques to automatically generate and translate text.

[1113] "Translation methods" refer to the process of converting text into another language using generative artificial intelligence.

[1114] "Means of transmission" refers to network protocols and communication methods used to send data to a specified destination.

[1115] "Means of notification" refers to in-application notification functions and messaging systems used to convey information to users.

[1116] "Means of saving history" refers to a mechanism for storing records of negotiations and communications within the system.

[1117] "Means of collecting feedback" refers to an interface for obtaining ratings and comments from users.

[1118] An "application" refers to software or mobile applications used by users.

[1119] "Personal information" refers to data unique to each user, such as age, gender, and skills.

[1120] "Validation" refers to the process of verifying whether the entered data conforms to specified formats and conditions.

[1121] An "API request" refers to a request message sent to use the functions of an external website.

[1122] "Response" refers to the response message returned from an external site in response to an API request.

[1123] "Metadata" refers to information about the attributes and structure of data.

[1124] An "emotion engine" refers to software or algorithms used to analyze a user's emotional state.

[1125] "Analysis results" refers to data about emotional states generated by the emotion engine.

[1126] This invention is a system that combines generative AI and an emotion engine to help users effectively conduct business negotiations with overseas e-commerce and retail sites. Communication and processing between the user, terminal, and server enable smooth business negotiations, overcoming language barriers and cultural differences.

[1127] User registration and initial setup

[1128] The user launches the application and enters personal information such as age, gender, and English proficiency. The device sends this information to the server via an HTTP request. The server receives the user information, validates it, and then stores it in a database. This step manages each user's basic profile information.

[1129] Connection with e-commerce sites and retail sites

[1130] The user selects the e-commerce or retail site they wish to connect to via a web interface. The device sends the selection information (site URL, API key, etc.) to the server. Based on the received information, the server obtains authentication information for the external API connection and makes an API request to connect to the external site. The server receives the response to the API request and checks whether the connection was successful. If the connection is successful, the server saves this status to the database and notifies the user that they can proceed to the next step.

[1131] Automatic translation and business negotiation support

[1132] The user enters a text message to initiate a business negotiation into an input form within the application. The device sends this message to the server. The server uses generative AI (e.g., GPT-4) to translate the received message into appropriate business English. The server then sends the translated message to an API endpoint on an external site. The server receives a reply from the external site and again uses generative AI to translate the reply into a language the user can understand. Finally, the server sends the translated reply message to the device to notify the user.

[1133] Negotiation history management

[1134] The server stores a database containing the sending and receiving history of all messages from the start to the end of negotiations. This history data includes metadata such as timestamps, user IDs, and external site IDs, and is stored for future access and analysis.

[1135] Collecting user feedback

[1136] After the negotiation is complete, the user accesses an interface for providing feedback and enters ratings and comments. The terminal sends the feedback information (ratings, comments) to the server. The server validates the received feedback and stores it in a database. The collected feedback is analyzed and used to improve the system.

[1137] Using an Emotion Engine

[1138] When a user enters a message, the device also sends data representing the user's emotional state (e.g., linguistic features, facial recognition data) to the server. The server uses an emotion engine to analyze the user's emotional state from the received data. This analysis is then reflected in a generative AI, which translates the message using appropriate tone and expression. The server also records the user's emotional state along with the translation and, if necessary, notifies the user of appropriate advice or support information.

[1139] Specific example

[1140] Example 1: User Registration

[1141] When user A uses the app for the first time, they register by entering their age, gender, and English proficiency. The device sends the entered information to the server, and the server stores the received information in a database.

[1142] Example 2: Negotiating with an e-commerce site

[1143] If user B wants to purchase an item from an American e-commerce site and wants to negotiate the price, they type "Can you offer a discount?" and the device sends the message to the server. The server uses generative AI to translate the message and sends it to the e-commerce site in appropriate business English. The server receives the reply from the e-commerce site, translates it into a language the user understands, and notifies the device.

[1144] Example 3: Using an Emotion Engine

[1145] User C types "I am very frustrated with the delay" during negotiations. The device sends facial recognition data and voice tone data along with the message to the server. The server uses its emotion engine to recognize User C's emotional state as "frustrated." The server takes the emotional state into consideration and translates it in an appropriate tone through a generative AI. The server generates the translation "I understand your frustration and will expedite your request" and notifies the device.

[1146] Thus, the present invention is a system that integrates a generative AI and an emotion engine, enabling users to conduct business negotiations more smoothly, transcending language and cultural differences.

[1147] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1148] Step 1: The user launches the application and enters personal information.

[1149] The user launches the application and enters personal information such as age, gender, and English proficiency into an input form. This information is used as part of the user profile. The user's personal data is the input, and the data is passed to the terminal as the output.

[1150] Step 2: The terminal sends the input information to the server.

[1151] The terminal sends the user's entered personal information to the server using an HTTP request. The user's personal information is passed from the terminal as structured data as input, and an HTTP request is sent to the server as output. Specifically, a POST request is used.

[1152] Step 3: The server receives user information, validates it, and saves it to the database.

[1153] The server receives an HTTP request and extracts user data from the payload. Validation checks are performed to verify data format and required fields, and if successful, the data is saved to the database. The input is the HTTP request payload, and the output is the database record. Specifically, an SQL insert query is executed.

[1154] Step 4: The user selects the e-commerce or retail site they want to connect to.

[1155] The user selects the e-commerce or retail site they wish to connect to on the application's interface. This provides the necessary information for the next step.

[1156] Step 5: The device sends the selection information to the server.

[1157] The device sends the URL and API key of the selected site to the server as structured data. The input is the information of the selected site, and the output is an HTTP request sent to the server. Specifically, a POST request is used.

[1158] Step 6: The server obtains authentication information for the external API connection based on the received information and makes an API request.

[1159] The server obtains authentication information for connecting to an external API based on the received information and makes an API request. The input consists of the received information and the API request for obtaining authentication information, and the output is the returned authentication information. Specifically, protocols such as OAuth 2.0 are used.

[1160] Step 7: The server verifies the success or failure of the connection and saves the information to the database.

[1161] The server receives the API response and checks whether the connection was successful. If successful, it saves the connection information and status to the database. The input is the API response, and the output is a record in the database and permission for the next operation. Specifically, an SQL insert query is used.

[1162] Step 8: If the server connection is successful, notify the user that the next step is available.

[1163] If the server successfully connects, it notifies the user of its status. The input is the database connection status, and the output is a message to be sent to the user. Specific methods used include push notifications and email.

[1164] Step 9: The user enters a text message for the opportunity.

[1165] The user enters a text message to initiate a business negotiation into an input form within the application. This becomes the input data for the next step.

[1166] Step 10: The device sends the message to the server.

[1167] The terminal sends the entered message to the server. The input is the user's message, and the output is an HTTP request sent to the server. Specifically, a POST request is used.

[1168] Step 11: The server translates the message using generative artificial intelligence.

[1169] The server translates received messages into appropriate business English using generative artificial intelligence (e.g., GPT-4). The input is the user's message, and the output is the translated text. Specifically, a prompt is passed to the AI ​​model, and the generated response is obtained.

[1170] Step 12: The server sends the translated message to an external site.

[1171] The server sends the translated message as structured data to an API endpoint on an external site. The input is the translated text, and the output is an API request. Specifically, a POST request is used.

[1172] Step 13: The server receives the reply, translates it again, and notifies the user.

[1173] The server receives replies from external websites and uses generative artificial intelligence to translate them into a language the user can understand. The input is the reply from the external website, and the output is the translated text. Specifically, a prompt is passed to the AI ​​model, and the generated response is obtained. The result is then notified to the user.

[1174] Step 14: The server saves the message history to the database.

[1175] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations. The input is the negotiation history, and the output is the recording to the database.

[1176] Step 15: The server adds metadata and saves it for future access.

[1177] The server adds metadata such as timestamps, user IDs, and external site IDs to the stored historical data and saves it for future access and analysis. Historical data is the input, and data with metadata is stored as the output.

[1178] Step 16: Users enter feedback ratings and comments.

[1179] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[1180] Step 17: The device sends feedback information to the server.

[1181] The device sends feedback information (ratings, comments) to the server. User feedback is the input, and an HTTP request is sent to the server as output. Specifically, a POST request is used.

[1182] Step 18: The server validates the feedback and saves it to the database.

[1183] The server validates the received feedback and saves it to the database. Feedback data is the input, and the output is the recording to the database.

[1184] Step 19: Users also send sentiment data when entering messages.

[1185] When a user enters a message, the device also sends data representing the user's emotional state (e.g., linguistic characteristics, facial recognition data) to the server. The input consists of the message and emotional data, and the output is an HTTP request sent to the server.

[1186] Step 20: The server analyzes the emotional state using the emotion engine.

[1187] The server uses an emotion engine to analyze the user's emotional state from the received data. Emotional data is the input, and the analysis results are the output. Specifically, an emotion recognition algorithm is used.

[1188] Step 21: The server reflects the analysis results in the generative artificial intelligence and performs the translation.

[1189] The server incorporates the analysis results into a generative artificial intelligence system, which then performs the translation using appropriate tone and expression. The input consists of the analysis results and the message, and the output is the translated text.

[1190] Step 22: The server records the translation results and sentiment state and notifies the user.

[1191] The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information. The input consists of the translation results and emotional data, and the output generates information to be notified to the user.

[1192] (Application Example 2)

[1193] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1194] In conventional autonomous vehicles, users faced difficulties in smooth negotiation and communication when interacting with foreign e-commerce sites or support services due to language barriers and differences in how emotions are conveyed. Furthermore, the systems managing these interactions simply translated messages without considering the user's emotional state, resulting in a decline in the quality and efficiency of communication.

[1195] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for translating user messages using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for analyzing the user's emotional state using an emotion engine, and means for adjusting the tone of messages based on the analysis results. This enables the user to effectively conduct business negotiations and communication with foreign e-commerce sites and support services.

[1196] "Means of saving information received from users" refers to a function that saves data entered by the user to a storage device such as a server, making it accessible and usable later.

[1197] "Means of establishing connections with external sites" refers to a function that allows communication with external websites and services using authentication information.

[1198] "A means of translating user messages using generative artificial intelligence" refers to a function that uses generative AI to convert text entered by a user into another language.

[1199] "Means for sending translated messages to external sites" refers to a function that sends translated messages to external websites or services.

[1200] "A means of translating and notifying users of replies from external sites" refers to a function that translates messages obtained from external sites into a language that the user can understand and notifies the user of that translation.

[1201] "Means for saving negotiation history" refers to a function that records and saves the negotiation interactions that a user has had.

[1202] "Means for collecting and saving feedback" refers to a function for collecting, recording, and saving ratings and comments provided by users.

[1203] "Methods for analyzing a user's emotional state using an emotion engine" refers to technologies that identify and evaluate a user's emotions based on the user's input data and characteristics.

[1204] "Means of adjusting the tone of a message based on analysis results" refers to a function that appropriately modifies and adjusts the tone and expression of a message based on the results of the emotion engine's analysis.

[1205] System Overview

[1206] This invention is a system that enables users to smoothly conduct business negotiations and communication with overseas e-commerce sites and support services. This system is primarily composed of an application installed on the user interface of an autonomous vehicle. Specifically, it works by linking generative artificial intelligence and an emotion engine to translate and analyze the sentiment of user messages, then sends the translation results to external sites in an appropriate tone, and provides replies from external sites in a format that the user can understand.

[1207] Hardware and software configuration

[1208] hardware

[1209] Terminal: Onboard computer installed in an autonomous vehicle

[1210] Server: Information processing server located on the cloud.

[1211] Input devices: Interface devices with touch panels or voice input capabilities.

[1212] Communication device: A mobile communication device that enables internet connectivity.

[1213] software

[1214] Generative artificial intelligence (generative AI models): Natural language processing models for translating user messages (e.g., Helsinki-NLP / opus-mt-ja-en)

[1215] Emotion engine: An emotion analysis model for analyzing user emotions (e.g., the emotion analysis pipeline in Transformers).

[1216] Database Management System: A server-based RDBMS that manages user information, negotiation history, and feedback records.

[1217] API Integration Module: A program module for managing communication with external sites.

[1218] System Operation Description

[1219] 1. User information registration and initial setup

[1220] The user activates the in-car terminal and enters personal information such as age, gender, and English language skills.

[1221] The terminal sends the entered user information to the server via an HTTP request, and the server receives the information and stores it in the database.

[1222] 2. External site connection

[1223] The user selects the e-commerce site or support service they want to connect to.

[1224] The device sends the URL and API key of the selected site to the server, which receives this information, obtains authentication information to connect to the external site, and establishes the connection.

[1225] 3. Translate and send messages

[1226] The user enters "I want to change my destination midway" in Japanese.

[1227] The terminal sends this input message to the server, which then uses generative artificial intelligence (generative AI model) to translate it into English.

[1228] The translation result is analyzed using an emotion engine to reflect the user's emotional state and result in "I want to change the destination midway."

[1229] Send the translated message to an external website.

[1230] 4. Reply from an external site

[1231] The server receives replies from external websites and uses generative artificial intelligence to translate them back into Japanese.

[1232] For example, if the reply from an external site is "Sure, please provide the new destination address," it will be translated as "Of course, please provide the new destination address."

[1233] The device will notify the user of the translation result.

[1234] 5. Managing History and Feedback

[1235] The server records all negotiation interactions in a database, making them available for later reference.

[1236] Users provide feedback after the negotiation is complete, and the server collects and stores that feedback.

[1237] Specific example

[1238] User example

[1239] When a user enters "I want to change my destination midway," the following prompt is sent to the generating AI model:

[1240] "I want to change the destination mid-way"

[1241] Example of a prompt

[1242] text

[1243] I want to change the destination mid-way

[1244] This will enable users to smoothly conduct complex negotiations and communications in foreign countries, significantly improving the experience inside autonomous vehicles.

[1245] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1246] Step 1:

[1247] User information registration and initial setup

[1248] Users enter personal information such as age, gender, and English language skills into an in-vehicle terminal.

[1249] The terminal sends the input data to the server via an HTTP request.

[1250] The server validates the received data and saves it to the database.

[1251] Input: Personal information entered by the user (age, gender, English proficiency, etc.)

[1252] Output: User information stored in the database

[1253] Function: This manages each user's basic profile information.

[1254] Step 2:

[1255] External site connection settings

[1256] The user selects the e-commerce site or support service they want to connect to using the in-car terminal.

[1257] The device sends selection information (site URL, API key, etc.) to the server.

[1258] The server obtains authentication information for connecting to an external API and makes a request to connect to the external site.

[1259] Input: User-selected site URL and API key

[1260] Output: Success or failure of external site connection

[1261] Operation: The server checks the connection status, saves it to the database, and notifies the user.

[1262] Step 3:

[1263] User message input and translation

[1264] The user enters their negotiation message into the input form on the in-vehicle terminal.

[1265] The terminal sends the input message to the server.

[1266] The server invokes a generative AI model to translate the message into business English.

[1267] Input: Negotiation message entered by the user

[1268] Output: Translated business English message

[1269] Function: Uses generative artificial intelligence to translate messages into appropriate business terminology.

[1270] Step 4:

[1271] Emotion analysis and tone adjustment

[1272] The server analyzes the user's input messages using an emotion engine to identify the user's emotional state.

[1273] Based on the emotion analysis results, the tone is adjusted and a refined message is generated.

[1274] Input: Translated business English message, analyzed sentiment

[1275] Output: A reconciled business English message

[1276] Function: Appropriately adjusts the tone and expression of the message according to the emotional state.

[1277] Step 5:

[1278] Sending a translated message

[1279] The server sends a pre-configured message to an external site.

[1280] The server retrieves the results received from external websites.

[1281] Input: A pre-formatted business English message

[1282] Output: Response message from an external site

[1283] Operation: Send a message and receive a response.

[1284] Step 6:

[1285] Translation of replies from external sites

[1286] The server generates reply messages from external websites and uses an AI model to re-translate them into Japanese.

[1287] The device receives this Japanese translated reply message and notifies the user.

[1288] Input: Reply message from an external site

[1289] Output: Reply message translated into Japanese

[1290] Function: Translates incoming messages and notifies the user.

[1291] Step 7:

[1292] History and Feedback Management

[1293] The server saves all message exchanges from the start to the end of negotiations to a database.

[1294] Users provide feedback after the negotiation is complete, and the server stores it.

[1295] Input: Negotiation history, user feedback

[1296] Output: Negotiation history and feedback stored in the database

[1297] Function: Manages history and feedback, making it available for later reference.

[1298] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1299] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1300] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1301] [Third Embodiment]

[1302] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1303] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1304] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1305] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1306] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1307] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1308] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1309] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1310] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1311] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1312] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1313] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1314] This invention is a system that uses generative AI to help users conduct smooth business negotiations with overseas e-commerce sites and retail sites. The processing of the system's program is described in detail below.

[1315] User registration and initial setup

[1316] 1. The user launches the application and enters personal information such as age, gender, and English language skills.

[1317] 2. The terminal sends the entered information to the server.

[1318] 3. The server receives user information, validates it, and then saves it to the database. This step allows the system to manage basic profile information for each user.

[1319] Connection with e-commerce sites and retail sites

[1320] 1. Utilize an interface that allows users to select the e-commerce or retail site they wish to connect to.

[1321] 2. The device sends the selected site information (such as URL and API key) to the server.

[1322] 3. Based on the information received by the server, it establishes a connection with an external site using APIs and communication protocols.

[1323] 4. The server checks whether the connection was successful and saves the connection status to the database.

[1324] Automatic translation and business negotiation support

[1325] 1. Enter a message for the user to initiate negotiations within the application.

[1326] 2. The terminal sends the entered message to the server.

[1327] 3. The server uses generative artificial intelligence to translate the input message into appropriate business English.

[1328] 4. The server sends the translated message to the e-commerce site and proceeds with the negotiation.

[1329] 5. The server receives the reply from the e-commerce site, translates it into a language the user can understand, and notifies the user.

[1330] 6. The device displays the translated reply and waits for the user to enter their reply again. By repeating this process, the user can negotiate smoothly.

[1331] Negotiation history management

[1332] 1. The server stores the entire negotiation history in a database. This includes all sent and received messages, as well as various metadata (such as timestamps).

[1333] 2. This historical data will be stored for future analysis and training purposes.

[1334] Collecting user feedback

[1335] 1. After the negotiation is complete, the user will have access to an interface to provide feedback.

[1336] 2. The device sends feedback information (ratings and comments) to the server.

[1337] 3. The server saves the feedback to a database so that it can be used for future system improvements.

[1338] Specific example

[1339] Example 1: User Registration

[1340] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[1341] The terminal sends input information to the server, and the server stores the received information in a database.

[1342] Example 2: Negotiating with an e-commerce site

[1343] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[1344] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[1345] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[1346] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[1347] In this way, the present invention is a system that enables users to conduct business negotiations smoothly, transcending language and cultural differences.

[1348] The following describes the processing flow.

[1349] User registration and initial setup

[1350] Step 1:

[1351] The user launches the application and enters personal information such as age, gender, and English language skills.

[1352] Step 2:

[1353] The terminal sends the entered information to the server via an HTTP request.

[1354] Step 3:

[1355] The server receives user information and validates the input data, checking for any inappropriate data.

[1356] Step 4:

[1357] The server establishes a database connection and saves user information that has passed validation to the database.

[1358] Connection with e-commerce sites and retail sites

[1359] Step 1:

[1360] Users select the e-commerce or retail site they want to connect to via a web interface.

[1361] Step 2:

[1362] The device sends selected information (site URL, API key, etc.) to the server as structured data.

[1363] Step 3:

[1364] Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[1365] Step 4:

[1366] The server receives the API request response and checks whether the connection was successful.

[1367] Step 5:

[1368] The server saves the connection status to the database, and if the connection is successful, it notifies the user that the system can proceed to the next step.

[1369] Automatic translation and business negotiation support

[1370] Step 1:

[1371] The user enters a text message to initiate a business negotiation into an input form within the application.

[1372] Step 2:

[1373] The terminal sends the entered message to the server.

[1374] Step 3:

[1375] The server processes the received message and calls upon generative artificial intelligence to translate it into appropriate business English.

[1376] Step 4:

[1377] The server sends the translated message as structured data to the API endpoint of an external site.

[1378] Step 5:

[1379] The server receives replies from external sites and uses generative artificial intelligence again to translate those replies into a language that the user can understand.

[1380] Step 6:

[1381] The server sends the translated reply message to the device and displays it to the user through the UX / UI.

[1382] Negotiation history management

[1383] Step 1:

[1384] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[1385] Step 2:

[1386] The server adds metadata (such as timestamps, user IDs, and external site IDs) to the historical data and stores it for future access and analysis.

[1387] Collecting user feedback

[1388] Step 1:

[1389] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[1390] Step 2:

[1391] The device sends feedback information (ratings, comments) to the server as structured data.

[1392] Step 3:

[1393] The server validates the feedback it receives and saves it to the database.

[1394] Step 4:

[1395] The server analyzes the collected feedback and uses it to improve the system.

[1396] (Example 1)

[1397] Next, we will describe Example 1. 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."

[1398] Conducting smooth business negotiations with overseas e-commerce and retail sites can be difficult due to language and cultural differences. Furthermore, manual translation by users and subsequent negotiations with external sites is time-consuming and laborious. Managing negotiation history and feedback is also cumbersome and inefficient. This invention aims to provide a system to solve these problems.

[1399] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1400] In this invention, the server includes means for storing information received from the user, means for transmitting information entered by the terminal to the server, means for the server to receive user information, validate it, and store it in a database, means for the user to select an external site they wish to connect to, means for the terminal to transmit selected site information (such as URL and API key) to the server, means for the server to establish a connection with the external site and store the connection status in a database, means for translating user messages using a generative artificial intelligence model, means for sending the translated messages to the external site, means for translating replies from the external site into the user's native language and notifying them, means for storing the negotiation history in a database, means for the user to provide feedback after the negotiation is completed, and means for collecting and storing the feedback. This enables users to efficiently conduct business negotiations across language barriers and effectively manage negotiation history and feedback.

[1401] A "user" refers to an individual or legal entity that uses the system to conduct business negotiations with overseas e-commerce sites and retail sites.

[1402] A "terminal" refers to an electronic device used by a user to input information and send and receive data to and from a server.

[1403] A "server" refers to a computer system that processes information received from users and stores it in a database.

[1404] A "database" refers to a system for structuring and storing various types of data, such as user information, connection status, negotiation history, and feedback.

[1405] "Validation" refers to the process of verifying the validity of information entered by a user.

[1406] "External sites" refer to e-commerce sites and retail sites that users connect to and conduct business negotiations with.

[1407] A "URL" refers to address information used to establish a connection to an external website.

[1408] An "API key" refers to the authentication information required to access an API on an external website.

[1409] "Generative artificial intelligence models" refer to AI technologies used for translating user messages and replies.

[1410] "Translation" refers to the process of converting a message entered by a user into another language.

[1411] A "message" refers to the text information that a user enters to conduct negotiations.

[1412] "Connection status" refers to information regarding the success or failure of the connection to an external site.

[1413] "Negotiation history" refers to all messages sent and received during the negotiation process, along with their associated metadata.

[1414] "Feedback" refers to the evaluations and comments that users provide after the negotiation has concluded.

[1415] This invention provides a system that assists users in smoothly conducting business negotiations with overseas e-commerce and retail sites. This system enables users to efficiently conduct business negotiations through user information input and storage, connection to external sites, translation assistance using AI generation, negotiation history management, and feedback collection and storage.

[1416] User registration and initial setup

[1417] The user launches the application and enters personal information such as age, gender, and English proficiency. This information is sent from the device to the server. The server validates the received information and stores it in a database. MySQL is a suitable database to use.

[1418] Connection with e-commerce sites and retail sites

[1419] The system utilizes an interface where the user selects the e-commerce or retail site they wish to connect to. The terminal sends the selected site information (such as URL and API key) to the server. Based on the received information, the server establishes a connection with the external site using an API or communication protocol (e.g., REST API), verifies the success or failure of the connection, and saves the connection status to a database.

[1420] Automatic translation and business negotiation support

[1421] The user enters a message to initiate negotiations within the application. The device sends the entered message to the server. The server uses generative artificial intelligence (e.g., GPT-4) to translate the entered message into appropriate business English. The translated message is sent to the e-commerce site to proceed with the negotiations. The server receives a reply from the e-commerce site, translates it into a language the user understands, and notifies the device. The device displays the translated reply and waits for the user to enter another reply. By repeating this process, the user can conduct negotiations smoothly.

[1422] Negotiation history management

[1423] The server stores the entire negotiation history in a database. This includes all sent and received messages, as well as various metadata (such as timestamps). PostgreSQL is a suitable database. This makes the negotiation history available for future analysis and training purposes.

[1424] Collecting user feedback

[1425] After the negotiation is complete, the user accesses an interface to provide feedback. The device sends feedback information (ratings and comments) to the server. The server stores the feedback in a database and makes it available for future system improvements.

[1426] Specific example

[1427] Example 1: User Registration

[1428] When user A uses the app for the first time, they register by entering their age (e.g., 28), gender (e.g., male), and English proficiency (e.g., intermediate). The device sends this information to the server, and the server stores the received information in a database.

[1429] Example 2: Negotiating with an e-commerce site

[1430] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[1431] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[1432] The server sends a message to a generative AI (e.g., GPT-4), which translates it into appropriate business English. The translated message is then sent to the e-commerce site.

[1433] The system receives a reply from an e-commerce site (e.g., "We can offer a 10% discount.") and uses a generative AI model to translate it into the user's native language. The translated reply is sent to the device, which then displays it to the user.

[1434] Example of a prompt

[1435] "Please explain the transmission process for saving User A's personal information to the database."

[1436] "Please describe the message sending and translation process when User B initiates price negotiations on an e-commerce site."

[1437] In this way, the present invention is a system that enables users to overcome language barriers and conduct business negotiations efficiently.

[1438] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1439] Step 1:

[1440] The user launches the application and enters personal information such as age, gender, and English proficiency. Specifically, the user enters information into a form within the app and presses the "Submit" button.

[1441] Input: Personal information entered by the user (age, gender, English proficiency)

[1442] Output: Personal information sent to the server by the terminal

[1443] Step 2:

[1444] The terminal sends the entered information to the server. Specifically, it converts the input data into JSON format and sends it to the server as an HTTP request.

[1445] Input: Personal information entered by the user (in JSON format)

[1446] Output: Personal information passed to the server

[1447] Step 3:

[1448] The server receives user information and performs validation. Specifically, it checks the validity of the received information (e.g., whether age is a numerical value, whether gender is a valid option, whether English skills are within a certain range).

[1449] Input: User information sent from the device

[1450] Output: Validated user information

[1451] Step 4:

[1452] The server saves user information that has passed validation to the database. Specifically, it inserts the information into the MySQL database using an SQL query.

[1453] Input: Validated user information

[1454] Output: User information stored in the database

[1455] Step 5:

[1456] The interface utilizes a selection process where the user chooses the external site they want to connect to. Specifically, the user selects a site from a dropdown menu or search box and then clicks the "Connect" button.

[1457] Input: Information about the selected external website (URL, API key, etc.)

[1458] Output: External site information sent to the server by the terminal.

[1459] Step 6:

[1460] The device sends information from the selected external website to the server. Specifically, it sends the selected information to the server as an HTTP request in JSON format.

[1461] Input: Selected external website information (JSON format)

[1462] Output: External site information passed to the server

[1463] Step 7:

[1464] Based on the external site information received by the server, it establishes a connection with the external site using an API or communication protocol (e.g., REST API). Specifically, it sets the HTTP headers and request body using the received URL and API key, and sends a request to the API endpoint.

[1465] Input: External site information (URL, API key, etc.)

[1466] Output: Establishing a connection with an external site

[1467] Step 8:

[1468] The server checks whether the connection was successful and saves the status to the database. Specifically, it receives the response to the API request, checks the success status code (e.g., 200 OK), and records the status information in the database.

[1469] Input: API request response

[1470] Output: Connection status stored in the database

[1471] Step 9:

[1472] The user enters a message to initiate negotiations within the app. Specifically, they type a message in the chat window and press the "Send" button.

[1473] Input: Message entered by the user

[1474] Output: Message sent from the terminal to the server

[1475] Step 10:

[1476] The terminal sends the entered message to the server. Specifically, it sends the message to the server as an HTTP request in text format.

[1477] Input: User-entered message (text format)

[1478] Output: Message passed to the server

[1479] Step 11:

[1480] The server uses a generative artificial intelligence model (e.g., GPT-4) to translate the input message. Specifically, it sends the received message as a prompt to the generative AI model and obtains the translated text.

[1481] Input: Message entered by the user

[1482] Output: Translated message

[1483] Step 12:

[1484] The server sends the translated message to an external site. Specifically, it sets the translated text in the body of an API request and sends it to the external site's API endpoint.

[1485] Input: Translated message

[1486] Output: Translated message sent to an external site

[1487] Step 13:

[1488] The server receives replies from external websites, translates them into the user's native language, and notifies them. Specifically, it sends the reply message to an AI model that generates translations and retrieves the translation results.

[1489] Input: Reply message from an external site

[1490] Output: Translated reply message

[1491] Step 14:

[1492] The device displays the translated reply and waits for the user to type another reply. Specifically, it displays the translated text in the chat window and re-enables the interface for entering a new message.

[1493] Input: Translated reply message

[1494] Output: Translated message displayed to the user

[1495] Step 15:

[1496] The server saves the entire negotiation history to a database. It stores all sent messages and replies, as well as various metadata (such as timestamps). Specifically, it inserts messages and metadata into a PostgreSQL database using SQL queries.

[1497] Input: Negotiation history information (messages and metadata)

[1498] Output: Negotiation history stored in the database

[1499] Step 16:

[1500] After the negotiation is complete, the user accesses an interface to provide feedback. Specifically, they enter their rating and comments into the feedback form and press the "Submit" button.

[1501] Input: Feedback information (ratings and comments)

[1502] Output: Feedback sent from the terminal to the server

[1503] Step 17:

[1504] The device sends feedback information to the server. Specifically, it sends feedback data to the server in JSON format.

[1505] Input: Feedback information (JSON format)

[1506] Output: Feedback information passed to the server

[1507] Step 18:

[1508] The server saves the feedback to the database. Specifically, it inserts the feedback data into the database using an SQL query.

[1509] Input: Feedback Information

[1510] Output: Feedback information stored in the database

[1511] (Application Example 1)

[1512] Next, we will explain Application Example 1. In the following explanation, 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."

[1513] When users conduct business negotiations with overseas e-commerce and retail sites, language barriers and communication obstacles are a major challenge. Furthermore, there is a need to efficiently manage these negotiation histories and feedback to improve the user's negotiation experience. Conventional systems have not consistently achieved these functions, placing a heavy burden on users, thus creating a need for a more efficient and smoother negotiation support system.

[1514] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1515] In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for appropriately translating user messages into business terminology using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for storing user registration information in a database and accessing it later, means for sending automatically translated messages to the site and receiving responses, and means for storing negotiation history in a database. As a result, users can overcome language barriers and smoothly conduct business negotiations with overseas e-commerce sites, and negotiation history and feedback can also be managed efficiently.

[1516] A "user" is an individual or legal entity that uses this system to conduct business negotiations with overseas e-commerce sites and retail sites.

[1517] "Information" refers to all data entered by users, including personal information, negotiation messages, and feedback.

[1518] "External sites" refer to online platforms that users use for negotiations, such as e-commerce sites and retail sites.

[1519] "Means of establishing a connection" refers to technologies that use APIs and communication protocols to initiate communication with external sites and create a state where data exchange is possible.

[1520] "Generative artificial intelligence" is an AI technology that uses natural language processing to translate user messages into appropriate business English.

[1521] "Translation methods" refer to technologies that utilize generative artificial intelligence to convert user-inputted messages into other languages.

[1522] A "database" is a system for efficiently storing and managing data such as user information, negotiation history, and feedback.

[1523] "Means for receiving responses" refers to technologies for receiving reply messages from external sites, loading them into a server, and notifying the user.

[1524] "Negotiation history" refers to a record of all business negotiations conducted by the user, including data such as sent messages, translated messages, received messages, and timestamps.

[1525] This invention is a system that uses generative artificial intelligence to help users conduct smooth business negotiations with overseas e-commerce sites and retail sites. A detailed embodiment of the system is described below.

[1526] System Configuration

[1527] This system primarily consists of three entities: servers, terminals, and users. The processes performed by each entity, as well as the hardware and software they use, are described in detail below.

[1528] User registration and initial setup

[1529] Users launch the application using their device (smartphone, PC, etc.) and enter personal information such as age, gender, and English language skills. The device sends the collected information to the server, which validates it and then stores it in a database. This allows for the management of the user's basic profile information.

[1530] Connection with e-commerce sites and retail sites

[1531] The user selects the e-commerce or retail site they wish to connect to via the terminal's interface. The selected site information (such as URL and API key) is sent from the terminal to the server, which then establishes a connection with the external site using APIs and communication protocols. The success or failure of the connection is stored in a database.

[1532] Automatic translation and business negotiation support

[1533] The user enters a message from their device to initiate negotiations. The device sends this message to the server, which uses generative artificial intelligence to translate the message into appropriate business English. The translated message is then sent to an external website. The server receives the reply from the external website, translates it into a language the user understands, and notifies the user of the reply on their device.

[1534] Negotiation history management

[1535] The server stores the entire negotiation history in a database. This history includes all sent and received messages, as well as various metadata (such as timestamps). This data is used for future analysis and system training.

[1536] Collecting user feedback

[1537] After negotiations are complete, users provide feedback through their devices. The devices send feedback information (ratings and comments) to the server, which stores it in a database. The collected feedback is used to improve the system.

[1538] Hardware and software to use

[1539] Server: Handles data storage, processing of generated AI models, API connections, and database management.

[1540] Terminal: As a user interface, it is responsible for message input and display. Smartphones and PCs are the main hardware examples.

[1541] Generative AI model: Used to translate user messages into business English. Leverages natural language processing software such as the Google Trans library.

[1542] Examples of specifics and prompts

[1543] Specific example 1:

[1544] When user A uses the app for the first time, they register by entering their age, gender, and English proficiency. The device sends this information to the server, and the server stores the received information in a database.

[1545] Specific example 2:

[1546] User B wants to purchase an item from an American e-commerce site and types "Can you offer a discount?". The server uses generative AI to translate the message, sends it to the e-commerce site in appropriate business English, and then translates the reply into a language the user understands and notifies them.

[1547] Example of a Generative AI Model prompt:

[1548] Original text: "What is the product's stock status?"

[1549] Prompt: Translate the following sentence into business English: 'What is the product's stock status?'

[1550] Translated text: "Could you please update me on the availability of the product?"

[1551] In this way, the system enables users to conduct business negotiations smoothly, transcending language and cultural barriers.

[1552] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1553] Step 1:

[1554] The user uses their device and launches the application. The user enters personal information such as age, gender, and English proficiency, and submits it by clicking the save button.

[1555] Input: Personal information such as age, gender, and English language skills.

[1556] Output: Sent user information.

[1557] Specific operation: After the user enters information and taps the "Send" button, the device sends that information to the server.

[1558] Step 2:

[1559] The server receives user information sent from the terminal. The server validates the data and saves the information to the database.

[1560] Input: Submitted user information.

[1561] Output: User information saved as a result of validation.

[1562] Specific operation: The server checks the received data to verify that there is no invalid data. Then, it saves it to the database.

[1563] Step 3:

[1564] The user selects the external site they want to connect to (such as an e-commerce site or a retail site) using the device's interface.

[1565] Input: Information about the external website you want to connect to (such as URL or API key).

[1566] Output: Information from the selected external website.

[1567] Specific operation: The user selects an external site from a dropdown list or search function and taps the "Connect" button.

[1568] Step 4:

[1569] The device sends information about the selected external website to the server. The server then uses this information to establish a connection using APIs and communication protocols.

[1570] Input: Information from the selected external website.

[1571] Output: Success or failure of the connection.

[1572] Specific operation: The server, upon receiving information sent from the terminal, attempts to connect to an external site, determines whether the connection was successful or unsuccessful, and saves the success or failure to a database.

[1573] Step 5:

[1574] Enter a message on your device to initiate negotiations.

[1575] Input: A message to initiate negotiations.

[1576] Output: The input message.

[1577] Specific action: The user enters a negotiation message and taps the "Send" button.

[1578] Step 6:

[1579] The terminal sends the entered message to the server. The server uses generative artificial intelligence to translate the message into appropriate business English.

[1580] Input: The message entered by the user.

[1581] Output: Translated business English message.

[1582] Specific operation: The server receives the input message and performs translation using a generative AI model (e.g., the Google Trans library).

[1583] Step 7:

[1584] The server sends the translated message to an external site.

[1585] Input: Translated business English message.

[1586] Output: Message sent to an external site.

[1587] Specific operation: The server sends the translated message by calling an API on an external site.

[1588] Step 8:

[1589] The server receives a reply from an external website. It translates the reply into a language the user understands and notifies the device.

[1590] Input: Reply message from an external website.

[1591] Output: Translated reply message.

[1592] Specific operation: The server receives a reply message, translates it using a generation AI model, and sends it to the terminal.

[1593] Step 9:

[1594] The server saves the entire negotiation history to a database.

[1595] Input: Negotiation history including sent messages, replied messages, and timestamps.

[1596] Output: Saved negotiation history.

[1597] Specific operation: The server records all negotiation details in a database.

[1598] Step 10:

[1599] Users provide feedback via their devices after the negotiation is complete.

[1600] Input: Feedback information such as ratings and comments.

[1601] Output: Sent feedback information.

[1602] Specific action: The user fills out a feedback form and taps the "Submit" button.

[1603] Step 11:

[1604] The device sends feedback information to the server. The server stores it in its database.

[1605] Input: Submitted feedback information.

[1606] Output: Saved feedback information.

[1607] Specific operation: The server receives feedback information sent from the terminal and saves it to the database.

[1608] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1609] This invention is a system that combines generative AI and an emotion engine to help users conduct more effective business negotiations with overseas e-commerce and retail sites. The system's program processing is described in detail below.

[1610] User registration and initial setup

[1611] 1. The user launches the application and enters personal information such as age, gender, and English language skills.

[1612] 2. The terminal sends the entered information to the server via an HTTP request.

[1613] 3. The server receives user information, validates the input data, and then saves it to the database. This step manages the basic profile information of each user.

[1614] Connection with e-commerce sites and retail sites

[1615] 1. The user selects the e-commerce or retail site they wish to connect to via the web interface.

[1616] 2. The device sends the selected information (site URL, API key, etc.) to the server as structured data.

[1617] 3. Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[1618] 4. The server receives the API request response and checks whether the connection was successful.

[1619] 5. The server saves the connection status to the database and, if the connection is successful, notifies the user that the system can proceed to the next process.

[1620] Automatic translation and business negotiation support

[1621] 1. The user enters a text message to initiate a business negotiation into an input form within the application.

[1622] 2. The terminal sends the entered message to the server.

[1623] 3. The server processes the received message and calls a generative artificial intelligence to translate it into appropriate business English.

[1624] 4. The server sends the translated message as structured data to the API endpoint of the external site.

[1625] 5. The server receives the reply from the external site and uses generative artificial intelligence again to translate the reply into a language that the user can understand.

[1626] 6. The server sends the translated reply message to the terminal and displays it to the user through the UX / UI.

[1627] Negotiation history management

[1628] 1. The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[1629] 2. The server adds metadata (timestamp, user ID, external site ID, etc.) to the historical data and stores it for future access and analysis.

[1630] Collecting user feedback

[1631] 1. After the negotiation is complete, the user accesses an interface for providing feedback and enters their rating and comments.

[1632] 2. The device sends feedback information (ratings, comments) to the server as structured data.

[1633] 3. The server validates the feedback it receives and saves it to the database.

[1634] 4. The server analyzes the collected feedback and uses it to improve the system.

[1635] Using an Emotion Engine

[1636] 1. When a user enters a message, the device also sends data representing the user's emotional state to the server (e.g., linguistic characteristics, facial recognition data).

[1637] 2. The server uses an emotion engine to analyze the user's emotional state from the received data.

[1638] 3. The server reflects the results of the emotional analysis into the generative artificial intelligence, which then performs the translation using appropriate tone and expression.

[1639] 4. The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information.

[1640] Specific example

[1641] Example 1: User Registration

[1642] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[1643] The terminal sends input information to the server, and the server stores the received information in a database.

[1644] Example 2: Negotiating with an e-commerce site

[1645] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[1646] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[1647] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[1648] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[1649] Example 3: Using an Emotion Engine

[1650] User C types "I am very frustrated with the delay" during negotiations.

[1651] The device sends facial recognition data and voice tone data to the server along with the message.

[1652] The server uses an emotion engine to recognize user C's emotional state as "frustrated."

[1653] The server considers the emotional state and translates in an appropriate tone through a generative AI.

[1654] The server generates the translation "I understand your frustration and will expedite your request." and notifies the terminal.

[1655] Thus, the present invention is a system that integrates a generative AI and an emotion engine, enabling users to conduct business negotiations more smoothly, transcending language and cultural differences.

[1656] The following describes the processing flow.

[1657] User registration and initial setup

[1658] Step 1:

[1659] The user launches the application and enters personal information such as age, gender, and English language skills.

[1660] Step 2:

[1661] The terminal sends the entered information to the server via an HTTP request.

[1662] Step 3:

[1663] The server receives user information and validates the input data, checking for any inappropriate data.

[1664] Step 4:

[1665] The server establishes a database connection and saves user information that has passed validation to the database.

[1666] Connection with e-commerce sites and retail sites

[1667] Step 1:

[1668] Users select the e-commerce or retail site they want to connect to via a web interface.

[1669] Step 2:

[1670] The device sends selected information (site URL, API key, etc.) to the server as structured data.

[1671] Step 3:

[1672] Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[1673] Step 4:

[1674] The server receives the API request response and checks whether the connection was successful.

[1675] Step 5:

[1676] The server saves the connection status to the database and, if the connection is successful, notifies the user that the system can proceed to the next process.

[1677] Automatic translation and business negotiation support

[1678] Step 1:

[1679] The user enters a text message to initiate a business negotiation into an input form within the application.

[1680] Step 2:

[1681] The terminal sends the entered message to the server.

[1682] Step 3:

[1683] The server processes the received message and calls upon generative artificial intelligence to translate it into appropriate business English.

[1684] Step 4:

[1685] The server sends the translated message as structured data to the API endpoint of an external site.

[1686] Step 5:

[1687] The server receives replies from external sites and uses generative artificial intelligence again to translate those replies into a language that the user can understand.

[1688] Step 6:

[1689] The server sends the translated reply message to the device and displays it to the user through the UX / UI.

[1690] Negotiation history management

[1691] Step 1:

[1692] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[1693] Step 2:

[1694] The server adds metadata (such as timestamps, user IDs, and external site IDs) to the historical data and stores it for future access and analysis.

[1695] Collecting user feedback

[1696] Step 1:

[1697] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[1698] Step 2:

[1699] The device sends feedback information (ratings, comments) to the server as structured data.

[1700] Step 3:

[1701] The server validates the feedback it receives and saves it to the database.

[1702] Step 4:

[1703] The server analyzes the collected feedback and uses it to improve the system.

[1704] Using an Emotion Engine

[1705] Step 1:

[1706] When a user enters a message, the device also sends data that represents the user's emotional state to the server (e.g., linguistic characteristics, facial recognition data, etc.).

[1707] Step 2:

[1708] The server uses an emotion engine to analyze the user's emotional state from the received data.

[1709] Step 3:

[1710] The server uses a generative artificial intelligence to analyze emotions and translate them using appropriate tones and expressions.

[1711] Step 4:

[1712] The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information.

[1713] Specific example

[1714] Step 1:

[1715] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[1716] Step 2:

[1717] The terminal sends input information to the server, and the server stores the received information in a database.

[1718] Step 1:

[1719] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[1720] Step 2:

[1721] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[1722] Step 3:

[1723] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[1724] Step 4:

[1725] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[1726] Step 1:

[1727] User C types "I am very frustrated with the delay" during negotiations.

[1728] Step 2:

[1729] The device sends facial recognition data and voice tone data to the server along with the message.

[1730] Step 3:

[1731] The server uses an emotion engine to recognize user C's emotional state as "frustrated."

[1732] Step 4:

[1733] The server considers the emotional state and translates in an appropriate tone through a generative AI.

[1734] Step 5:

[1735] The server generates the translation "I understand your frustration and will expedite your request." and notifies the terminal.

[1736] (Example 2)

[1737] Next, we will describe Example 2. 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."

[1738] When users conduct business negotiations with overseas e-commerce and retail sites, they face challenges such as language barriers, cultural differences, and difficulty in effectively communicating their emotional state. Furthermore, managing negotiation history and collecting feedback is cumbersome. To address these issues, a system is needed that efficiently supports negotiations with overseas sites while considering the user's language abilities and emotional state.

[1739] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1740] In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for translating user messages using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for the user to launch an application and input personal information, means for the terminal to send the input information to the server, means for the server to receive user information, validate it, and store it in a database, means for the terminal to send selection information to the server, means for the server to obtain authentication information for an external API connection based on the received information and make an API request, means for the server to receive an API response, confirm the success or failure of the connection and store it in a database, and means for the server to confirm the connection success. The system includes means for notifying the user of the next possible processing, means for the terminal to send the entered message to the server, means for the server to translate the received message using generative artificial intelligence, means for the server to send the translated message to an external site, means for the server to receive the reply, translate it again, and notify the user, means for the server to store the message history in a database, means for the server to add metadata and store it for future access, means for the terminal to send feedback information to the server, means for the server to validate the feedback and store it in a database, means for the user to also send emotion data when entering a message, means for the server to analyze the emotional state using an emotion engine, means for the server to reflect the analysis results in generative artificial intelligence and perform translation, and means for the server to record the translation result and emotional state and notify the user. This makes it possible for users to conduct business negotiations smoothly across language and cultural differences, and also makes it easier to manage negotiation history and feedback.

[1741] "User" refers to an individual or legal entity that uses the system.

[1742] "Terminal" refers to electronic devices used by users, such as computers, smartphones, and tablets.

[1743] A "server" refers to a computer system that receives requests from users, processes them, and provides the necessary data.

[1744] "Information" refers to all data processed by the system, including personal data entered by users, messages, ratings, and so on.

[1745] "Means of storage" refers to databases, file systems, and other means of temporarily or permanently storing data.

[1746] "External sites" refer to other services on the internet, including online shopping sites and retailer websites.

[1747] "Means of establishing a connection" refers to protocols and API connections used to establish communication with external sites via the internet.

[1748] "Generative artificial intelligence" refers to AI models that use natural language processing and machine learning techniques to automatically generate and translate text.

[1749] "Translation methods" refer to the process of converting text into another language using generative artificial intelligence.

[1750] "Means of transmission" refers to network protocols and communication methods used to send data to a specified destination.

[1751] "Means of notification" refers to in-application notification functions and messaging systems used to convey information to users.

[1752] "Means of saving history" refers to a mechanism for storing records of negotiations and communications within the system.

[1753] "Means of collecting feedback" refers to an interface for obtaining ratings and comments from users.

[1754] An "application" refers to software or mobile applications used by users.

[1755] "Personal information" refers to data unique to each user, such as age, gender, and skills.

[1756] "Validation" refers to the process of verifying whether the entered data conforms to specified formats and conditions.

[1757] An "API request" refers to a request message sent to use the functions of an external website.

[1758] "Response" refers to the response message returned from an external site in response to an API request.

[1759] "Metadata" refers to information about the attributes and structure of data.

[1760] An "emotion engine" refers to software or algorithms used to analyze a user's emotional state.

[1761] "Analysis results" refers to data about emotional states generated by the emotion engine.

[1762] This invention is a system that combines generative AI and an emotion engine to help users effectively conduct business negotiations with overseas e-commerce and retail sites. Communication and processing between the user, terminal, and server enable smooth business negotiations, overcoming language barriers and cultural differences.

[1763] User registration and initial setup

[1764] The user launches the application and enters personal information such as age, gender, and English proficiency. The device sends this information to the server via an HTTP request. The server receives the user information, validates it, and then stores it in a database. This step manages each user's basic profile information.

[1765] Connection with e-commerce sites and retail sites

[1766] The user selects the e-commerce or retail site they wish to connect to via a web interface. The device sends the selection information (site URL, API key, etc.) to the server. Based on the received information, the server obtains authentication information for the external API connection and makes an API request to connect to the external site. The server receives the response to the API request and checks whether the connection was successful. If the connection is successful, the server saves this status to the database and notifies the user that they can proceed to the next step.

[1767] Automatic translation and business negotiation support

[1768] The user enters a text message to initiate a business negotiation into an input form within the application. The device sends this message to the server. The server uses generative AI (e.g., GPT-4) to translate the received message into appropriate business English. The server then sends the translated message to an API endpoint on an external site. The server receives a reply from the external site and again uses generative AI to translate the reply into a language the user can understand. Finally, the server sends the translated reply message to the device to notify the user.

[1769] Negotiation history management

[1770] The server stores a database containing the sending and receiving history of all messages from the start to the end of negotiations. This history data includes metadata such as timestamps, user IDs, and external site IDs, and is stored for future access and analysis.

[1771] Collecting user feedback

[1772] After the negotiation is complete, the user accesses an interface for providing feedback and enters ratings and comments. The terminal sends the feedback information (ratings, comments) to the server. The server validates the received feedback and stores it in a database. The collected feedback is analyzed and used to improve the system.

[1773] Using an Emotion Engine

[1774] When a user enters a message, the device also sends data representing the user's emotional state (e.g., linguistic features, facial recognition data) to the server. The server uses an emotion engine to analyze the user's emotional state from the received data. This analysis is then reflected in a generative AI, which translates the message using appropriate tone and expression. The server also records the user's emotional state along with the translation and, if necessary, notifies the user of appropriate advice or support information.

[1775] Specific example

[1776] Example 1: User Registration

[1777] When user A uses the app for the first time, they register by entering their age, gender, and English proficiency. The device sends the entered information to the server, and the server stores the received information in a database.

[1778] Example 2: Negotiating with an e-commerce site

[1779] If user B wants to purchase an item from an American e-commerce site and wants to negotiate the price, they type "Can you offer a discount?" and the device sends the message to the server. The server uses generative AI to translate the message and sends it to the e-commerce site in appropriate business English. The server receives the reply from the e-commerce site, translates it into a language the user understands, and notifies the device.

[1780] Example 3: Using an Emotion Engine

[1781] User C types "I am very frustrated with the delay" during negotiations. The device sends facial recognition data and voice tone data along with the message to the server. The server uses its emotion engine to recognize User C's emotional state as "frustrated." The server takes the emotional state into consideration and translates it in an appropriate tone through a generative AI. The server generates the translation "I understand your frustration and will expedite your request" and notifies the device.

[1782] Thus, the present invention is a system that integrates a generative AI and an emotion engine, enabling users to conduct business negotiations more smoothly, transcending language and cultural differences.

[1783] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1784] Step 1: The user launches the application and enters personal information.

[1785] The user launches the application and enters personal information such as age, gender, and English proficiency into an input form. This information is used as part of the user profile. The user's personal data is the input, and the data is passed to the terminal as the output.

[1786] Step 2: The terminal sends the input information to the server.

[1787] The terminal sends the user's entered personal information to the server using an HTTP request. The user's personal information is passed from the terminal as structured data as input, and an HTTP request is sent to the server as output. Specifically, a POST request is used.

[1788] Step 3: The server receives user information, validates it, and saves it to the database.

[1789] The server receives an HTTP request and extracts user data from the payload. Validation checks are performed to verify data format and required fields, and if successful, the data is saved to the database. The input is the HTTP request payload, and the output is the database record. Specifically, an SQL insert query is executed.

[1790] Step 4: The user selects the e-commerce or retail site they want to connect to.

[1791] The user selects the e-commerce or retail site they wish to connect to on the application's interface. This provides the necessary information for the next step.

[1792] Step 5: The device sends the selection information to the server.

[1793] The device sends the URL and API key of the selected site to the server as structured data. The input is the information of the selected site, and the output is an HTTP request sent to the server. Specifically, a POST request is used.

[1794] Step 6: The server obtains authentication information for the external API connection based on the received information and makes an API request.

[1795] The server obtains authentication information for connecting to an external API based on the received information and makes an API request. The input consists of the received information and the API request for obtaining authentication information, and the output is the returned authentication information. Specifically, protocols such as OAuth 2.0 are used.

[1796] Step 7: The server verifies the success or failure of the connection and saves the information to the database.

[1797] The server receives the API response and checks whether the connection was successful. If successful, it saves the connection information and status to the database. The input is the API response, and the output is a record in the database and permission for the next operation. Specifically, an SQL insert query is used.

[1798] Step 8: If the server connection is successful, notify the user that the next step is available.

[1799] If the server successfully connects, it notifies the user of its status. The input is the database connection status, and the output is a message to be sent to the user. Specific methods used include push notifications and email.

[1800] Step 9: The user enters a text message for the opportunity.

[1801] The user enters a text message to initiate a business negotiation into an input form within the application. This becomes the input data for the next step.

[1802] Step 10: The device sends the message to the server.

[1803] The terminal sends the entered message to the server. The input is the user's message, and the output is an HTTP request sent to the server. Specifically, a POST request is used.

[1804] Step 11: The server translates the message using generative artificial intelligence.

[1805] The server translates received messages into appropriate business English using generative artificial intelligence (e.g., GPT-4). The input is the user's message, and the output is the translated text. Specifically, a prompt is passed to the AI ​​model, and the generated response is obtained.

[1806] Step 12: The server sends the translated message to an external site.

[1807] The server sends the translated message as structured data to an API endpoint on an external site. The input is the translated text, and the output is an API request. Specifically, a POST request is used.

[1808] Step 13: The server receives the reply, translates it again, and notifies the user.

[1809] The server receives replies from external websites and uses generative artificial intelligence to translate them into a language the user can understand. The input is the reply from the external website, and the output is the translated text. Specifically, a prompt is passed to the AI ​​model, and the generated response is obtained. The result is then notified to the user.

[1810] Step 14: The server saves the message history to the database.

[1811] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations. The input is the negotiation history, and the output is the recording to the database.

[1812] Step 15: The server adds metadata and saves it for future access.

[1813] The server adds metadata such as timestamps, user IDs, and external site IDs to the stored historical data and saves it for future access and analysis. Historical data is the input, and data with metadata is stored as the output.

[1814] Step 16: Users enter feedback ratings and comments.

[1815] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[1816] Step 17: The device sends feedback information to the server.

[1817] The device sends feedback information (ratings, comments) to the server. User feedback is the input, and an HTTP request is sent to the server as output. Specifically, a POST request is used.

[1818] Step 18: The server validates the feedback and saves it to the database.

[1819] The server validates the received feedback and saves it to the database. Feedback data is the input, and the output is the recording to the database.

[1820] Step 19: Users also send sentiment data when entering messages.

[1821] When a user enters a message, the device also sends data representing the user's emotional state (e.g., linguistic characteristics, facial recognition data) to the server. The input consists of the message and emotional data, and the output is an HTTP request sent to the server.

[1822] Step 20: The server analyzes the emotional state using the emotion engine.

[1823] The server uses an emotion engine to analyze the user's emotional state from the received data. Emotional data is the input, and the analysis results are the output. Specifically, an emotion recognition algorithm is used.

[1824] Step 21: The server reflects the analysis results in the generative artificial intelligence and performs the translation.

[1825] The server incorporates the analysis results into a generative artificial intelligence system, which then performs the translation using appropriate tone and expression. The input consists of the analysis results and the message, and the output is the translated text.

[1826] Step 22: The server records the translation results and sentiment state and notifies the user.

[1827] The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information. The input consists of the translation results and emotional data, and the output generates information to be notified to the user.

[1828] (Application Example 2)

[1829] Next, we will explain application example 2. In the following explanation, 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."

[1830] In conventional autonomous vehicles, users faced difficulties in smooth negotiation and communication when interacting with foreign e-commerce sites or support services due to language barriers and differences in how emotions are conveyed. Furthermore, the systems managing these interactions simply translated messages without considering the user's emotional state, resulting in a decline in the quality and efficiency of communication.

[1831] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for translating user messages using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for analyzing the user's emotional state using an emotion engine, and means for adjusting the tone of messages based on the analysis results. This enables the user to effectively conduct business negotiations and communication with foreign e-commerce sites and support services.

[1832] "Means of saving information received from users" refers to a function that saves data entered by the user to a storage device such as a server, making it accessible and usable later.

[1833] "Means of establishing connections with external sites" refers to a function that allows communication with external websites and services using authentication information.

[1834] "A means of translating user messages using generative artificial intelligence" refers to a function that uses generative AI to convert text entered by a user into another language.

[1835] "Means for sending translated messages to external sites" refers to a function that sends translated messages to external websites or services.

[1836] "A means of translating and notifying users of replies from external sites" refers to a function that translates messages obtained from external sites into a language that the user can understand and notifies the user of that translation.

[1837] "Means for saving negotiation history" refers to a function that records and saves the negotiation interactions that a user has had.

[1838] "Means for collecting and saving feedback" refers to a function for collecting, recording, and saving ratings and comments provided by users.

[1839] "Methods for analyzing a user's emotional state using an emotion engine" refers to technologies that identify and evaluate a user's emotions based on the user's input data and characteristics.

[1840] "Means of adjusting the tone of a message based on analysis results" refers to a function that appropriately modifies and adjusts the tone and expression of a message based on the results of the emotion engine's analysis.

[1841] System Overview

[1842] This invention is a system that enables users to smoothly conduct business negotiations and communication with overseas e-commerce sites and support services. This system is primarily composed of an application installed on the user interface of an autonomous vehicle. Specifically, it works by linking generative artificial intelligence and an emotion engine to translate and analyze the sentiment of user messages, then sends the translation results to external sites in an appropriate tone, and provides replies from external sites in a format that the user can understand.

[1843] Hardware and software configuration

[1844] hardware

[1845] Terminal: Onboard computer installed in an autonomous vehicle

[1846] Server: Information processing server located on the cloud.

[1847] Input devices: Interface devices with touch panels or voice input capabilities.

[1848] Communication device: A mobile communication device that enables internet connectivity.

[1849] software

[1850] Generative artificial intelligence (generative AI models): Natural language processing models for translating user messages (e.g., Helsinki-NLP / opus-mt-ja-en)

[1851] Emotion engine: An emotion analysis model for analyzing user emotions (e.g., the emotion analysis pipeline in Transformers).

[1852] Database Management System: A server-based RDBMS that manages user information, negotiation history, and feedback records.

[1853] API Integration Module: A program module for managing communication with external sites.

[1854] System Operation Description

[1855] 1. User information registration and initial setup

[1856] The user activates the in-car terminal and enters personal information such as age, gender, and English language skills.

[1857] The terminal sends the entered user information to the server via an HTTP request, and the server receives the information and stores it in the database.

[1858] 2. External site connection

[1859] The user selects the e-commerce site or support service they want to connect to.

[1860] The device sends the URL and API key of the selected site to the server, which receives this information, obtains authentication information to connect to the external site, and establishes the connection.

[1861] 3. Translate and send messages

[1862] The user enters "I want to change my destination midway" in Japanese.

[1863] The terminal sends this input message to the server, which then uses generative artificial intelligence (generative AI model) to translate it into English.

[1864] The translation result is analyzed using an emotion engine to reflect the user's emotional state and result in "I want to change the destination midway."

[1865] Send the translated message to an external website.

[1866] 4. Reply from an external site

[1867] The server receives replies from external websites and uses generative artificial intelligence to translate them back into Japanese.

[1868] For example, if the reply from an external site is "Sure, please provide the new destination address," it will be translated as "Of course, please provide the new destination address."

[1869] The device will notify the user of the translation result.

[1870] 5. Managing History and Feedback

[1871] The server records all negotiation interactions in a database, making them available for later reference.

[1872] Users provide feedback after the negotiation is complete, and the server collects and stores that feedback.

[1873] Specific example

[1874] User example

[1875] When a user enters "I want to change my destination midway," the following prompt is sent to the generating AI model:

[1876] "I want to change the destination mid-way"

[1877] Example of a prompt

[1878] text

[1879] I want to change the destination mid-way

[1880] This will enable users to smoothly conduct complex negotiations and communications in foreign countries, significantly improving the experience inside autonomous vehicles.

[1881] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1882] Step 1:

[1883] User information registration and initial setup

[1884] Users enter personal information such as age, gender, and English language skills into an in-vehicle terminal.

[1885] The terminal sends the input data to the server via an HTTP request.

[1886] The server validates the received data and saves it to the database.

[1887] Input: Personal information entered by the user (age, gender, English proficiency, etc.)

[1888] Output: User information stored in the database

[1889] Function: This manages each user's basic profile information.

[1890] Step 2:

[1891] External site connection settings

[1892] The user selects the e-commerce site or support service they want to connect to using the in-car terminal.

[1893] The device sends selection information (site URL, API key, etc.) to the server.

[1894] The server obtains authentication information for connecting to an external API and makes a request to connect to the external site.

[1895] Input: User-selected site URL and API key

[1896] Output: Success or failure of external site connection

[1897] Operation: The server checks the connection status, saves it to the database, and notifies the user.

[1898] Step 3:

[1899] User message input and translation

[1900] The user enters their negotiation message into the input form on the in-vehicle terminal.

[1901] The terminal sends the input message to the server.

[1902] The server invokes a generative AI model to translate the message into business English.

[1903] Input: Negotiation message entered by the user

[1904] Output: Translated business English message

[1905] Function: Uses generative artificial intelligence to translate messages into appropriate business terminology.

[1906] Step 4:

[1907] Emotion analysis and tone adjustment

[1908] The server analyzes the user's input messages using an emotion engine to identify the user's emotional state.

[1909] Based on the emotion analysis results, the tone is adjusted and a refined message is generated.

[1910] Input: Translated business English message, analyzed sentiment

[1911] Output: A reconciled business English message

[1912] Function: Appropriately adjusts the tone and expression of the message according to the emotional state.

[1913] Step 5:

[1914] Sending a translated message

[1915] The server sends a pre-configured message to an external site.

[1916] The server retrieves the results received from external websites.

[1917] Input: A pre-formatted business English message

[1918] Output: Response message from an external site

[1919] Operation: Send a message and receive a response.

[1920] Step 6:

[1921] Translation of replies from external sites

[1922] The server generates reply messages from external websites and uses an AI model to re-translate them into Japanese.

[1923] The device receives this Japanese translated reply message and notifies the user.

[1924] Input: Reply message from an external site

[1925] Output: Reply message translated into Japanese

[1926] Function: Translates incoming messages and notifies the user.

[1927] Step 7:

[1928] History and Feedback Management

[1929] The server saves all message exchanges from the start to the end of negotiations to a database.

[1930] Users provide feedback after the negotiation is complete, and the server stores it.

[1931] Input: Negotiation history, user feedback

[1932] Output: Negotiation history and feedback stored in the database

[1933] Function: Manages history and feedback, making it available for later reference.

[1934] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1935] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1936] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1937] [Fourth Embodiment]

[1938] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1939] As shown in Figure 7, the 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.

[1940] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1941] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1942] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1943] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1944] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1945] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1946] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1947] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1948] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1949] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1950] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1951] This invention is a system that uses generative AI to help users conduct smooth business negotiations with overseas e-commerce sites and retail sites. The processing of the system's program is described in detail below.

[1952] User registration and initial setup

[1953] 1. The user launches the application and enters personal information such as age, gender, and English language skills.

[1954] 2. The terminal sends the entered information to the server.

[1955] 3. The server receives user information, validates it, and then saves it to the database. This step allows the system to manage basic profile information for each user.

[1956] Connection with e-commerce sites and retail sites

[1957] 1. Utilize an interface that allows users to select the e-commerce or retail site they wish to connect to.

[1958] 2. The device sends the selected site information (such as URL and API key) to the server.

[1959] 3. Based on the information received by the server, it establishes a connection with an external site using APIs and communication protocols.

[1960] 4. The server checks whether the connection was successful and saves the connection status to the database.

[1961] Automatic translation and business negotiation support

[1962] 1. Enter a message for the user to initiate negotiations within the application.

[1963] 2. The terminal sends the entered message to the server.

[1964] 3. The server uses generative artificial intelligence to translate the input message into appropriate business English.

[1965] 4. The server sends the translated message to the e-commerce site and proceeds with the negotiation.

[1966] 5. The server receives the reply from the e-commerce site, translates it into a language the user can understand, and notifies the user.

[1967] 6. The device displays the translated reply and waits for the user to enter their reply again. By repeating this process, the user can negotiate smoothly.

[1968] Negotiation history management

[1969] 1. The server stores the entire negotiation history in a database. This includes all sent and received messages, as well as various metadata (such as timestamps).

[1970] 2. This historical data will be stored for future analysis and training purposes.

[1971] Collecting user feedback

[1972] 1. After the negotiation is complete, the user will have access to an interface to provide feedback.

[1973] 2. The device sends feedback information (ratings and comments) to the server.

[1974] 3. The server saves the feedback to a database so that it can be used for future system improvements.

[1975] Specific example

[1976] Example 1: User Registration

[1977] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[1978] The terminal sends input information to the server, and the server stores the received information in a database.

[1979] Example 2: Negotiating with an e-commerce site

[1980] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[1981] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[1982] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[1983] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[1984] In this way, the present invention is a system that enables users to conduct business negotiations smoothly, transcending language and cultural differences.

[1985] The following describes the processing flow.

[1986] User registration and initial setup

[1987] Step 1:

[1988] The user launches the application and enters personal information such as age, gender, and English language skills.

[1989] Step 2:

[1990] The terminal sends the entered information to the server via an HTTP request.

[1991] Step 3:

[1992] The server receives user information and validates the input data, checking for any inappropriate data.

[1993] Step 4:

[1994] The server establishes a database connection and saves user information that has passed validation to the database.

[1995] Connection with e-commerce sites and retail sites

[1996] Step 1:

[1997] Users select the e-commerce or retail site they want to connect to via a web interface.

[1998] Step 2:

[1999] The device sends selected information (site URL, API key, etc.) to the server as structured data.

[2000] Step 3:

[2001] Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[2002] Step 4:

[2003] The server receives the API request response and checks whether the connection was successful.

[2004] Step 5:

[2005] The server saves the connection status to the database, and if the connection is successful, it notifies the user that the system can proceed to the next step.

[2006] Automatic translation and business negotiation support

[2007] Step 1:

[2008] The user enters a text message to initiate a business negotiation into an input form within the application.

[2009] Step 2:

[2010] The terminal sends the entered message to the server.

[2011] Step 3:

[2012] The server processes the received message and calls upon generative artificial intelligence to translate it into appropriate business English.

[2013] Step 4:

[2014] The server sends the translated message as structured data to the API endpoint of an external site.

[2015] Step 5:

[2016] The server receives replies from external sites and uses generative artificial intelligence again to translate those replies into a language that the user can understand.

[2017] Step 6:

[2018] The server sends the translated reply message to the device and displays it to the user through the UX / UI.

[2019] Negotiation history management

[2020] Step 1:

[2021] The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[2022] Step 2:

[2023] The server adds metadata (such as timestamps, user IDs, and external site IDs) to the historical data and stores it for future access and analysis.

[2024] Collecting user feedback

[2025] Step 1:

[2026] After the negotiation is complete, the user accesses an interface to provide feedback and enters ratings and comments.

[2027] Step 2:

[2028] The device sends feedback information (ratings, comments) to the server as structured data.

[2029] Step 3:

[2030] The server validates the feedback it receives and saves it to the database.

[2031] Step 4:

[2032] The server analyzes the collected feedback and uses it to improve the system.

[2033] (Example 1)

[2034] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2035] Conducting smooth business negotiations with overseas e-commerce and retail sites can be difficult due to language and cultural differences. Furthermore, manual translation by users and subsequent negotiations with external sites is time-consuming and laborious. Managing negotiation history and feedback is also cumbersome and inefficient. This invention aims to provide a system to solve these problems.

[2036] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[2037] In this invention, the server includes means for storing information received from the user, means for transmitting information entered by the terminal to the server, means for the server to receive user information, validate it, and store it in a database, means for the user to select an external site they wish to connect to, means for the terminal to transmit selected site information (such as URL and API key) to the server, means for the server to establish a connection with the external site and store the connection status in a database, means for translating user messages using a generative artificial intelligence model, means for sending the translated messages to the external site, means for translating replies from the external site into the user's native language and notifying them, means for storing the negotiation history in a database, means for the user to provide feedback after the negotiation is completed, and means for collecting and storing the feedback. This enables users to efficiently conduct business negotiations across language barriers and effectively manage negotiation history and feedback.

[2038] A "user" refers to an individual or legal entity that uses the system to conduct business negotiations with overseas e-commerce sites and retail sites.

[2039] A "terminal" refers to an electronic device used by a user to input information and send and receive data to and from a server.

[2040] A "server" refers to a computer system that processes information received from users and stores it in a database.

[2041] A "database" refers to a system for structuring and storing various types of data, such as user information, connection status, negotiation history, and feedback.

[2042] "Validation" refers to the process of verifying the validity of information entered by a user.

[2043] "External sites" refer to e-commerce sites and retail sites that users connect to and conduct business negotiations with.

[2044] A "URL" refers to address information used to establish a connection to an external website.

[2045] An "API key" refers to the authentication information required to access an API on an external website.

[2046] "Generative artificial intelligence models" refer to AI technologies used for translating user messages and replies.

[2047] "Translation" refers to the process of converting a message entered by a user into another language.

[2048] A "message" refers to the text information that a user enters to conduct negotiations.

[2049] "Connection status" refers to information regarding the success or failure of the connection to an external site.

[2050] "Negotiation history" refers to all messages sent and received during the negotiation process, along with their associated metadata.

[2051] "Feedback" refers to the evaluations and comments that users provide after the negotiation has concluded.

[2052] This invention provides a system that assists users in smoothly conducting business negotiations with overseas e-commerce and retail sites. This system enables users to efficiently conduct business negotiations through user information input and storage, connection to external sites, translation assistance using AI generation, negotiation history management, and feedback collection and storage.

[2053] User registration and initial setup

[2054] The user launches the application and enters personal information such as age, gender, and English proficiency. This information is sent from the device to the server. The server validates the received information and stores it in a database. MySQL is a suitable database to use.

[2055] Connection with e-commerce sites and retail sites

[2056] The system utilizes an interface where the user selects the e-commerce or retail site they wish to connect to. The terminal sends the selected site information (such as URL and API key) to the server. Based on the received information, the server establishes a connection with the external site using an API or communication protocol (e.g., REST API), verifies the success or failure of the connection, and saves the connection status to a database.

[2057] Automatic translation and business negotiation support

[2058] The user enters a message to initiate negotiations within the application. The device sends the entered message to the server. The server uses generative artificial intelligence (e.g., GPT-4) to translate the entered message into appropriate business English. The translated message is sent to the e-commerce site to proceed with the negotiations. The server receives a reply from the e-commerce site, translates it into a language the user understands, and notifies the device. The device displays the translated reply and waits for the user to enter another reply. By repeating this process, the user can conduct negotiations smoothly.

[2059] Negotiation history management

[2060] The server stores the entire negotiation history in a database. This includes all sent and received messages, as well as various metadata (such as timestamps). PostgreSQL is a suitable database. This makes the negotiation history available for future analysis and training purposes.

[2061] Collecting user feedback

[2062] After the negotiation is complete, the user accesses an interface to provide feedback. The device sends feedback information (ratings and comments) to the server. The server stores the feedback in a database and makes it available for future system improvements.

[2063] Specific example

[2064] Example 1: User Registration

[2065] When user A uses the app for the first time, they register by entering their age (e.g., 28), gender (e.g., male), and English proficiency (e.g., intermediate). The device sends this information to the server, and the server stores the received information in a database.

[2066] Example 2: Negotiating with an e-commerce site

[2067] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[2068] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[2069] The server sends a message to a generative AI (e.g., GPT-4), which translates it into appropriate business English. The translated message is then sent to the e-commerce site.

[2070] The system receives a reply from an e-commerce site (e.g., "We can offer a 10% discount.") and uses a generative AI model to translate it into the user's native language. The translated reply is sent to the device, which then displays it to the user.

[2071] Example of a prompt

[2072] "Please explain the transmission process for saving User A's personal information to the database."

[2073] "Please describe the message sending and translation process when User B initiates price negotiations on an e-commerce site."

[2074] In this way, the present invention is a system that enables users to overcome language barriers and conduct business negotiations efficiently.

[2075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2076] Step 1:

[2077] The user launches the application and enters personal information such as age, gender, and English proficiency. Specifically, the user enters information into a form within the app and presses the "Submit" button.

[2078] Input: Personal information entered by the user (age, gender, English proficiency)

[2079] Output: Personal information sent to the server by the terminal

[2080] Step 2:

[2081] The terminal sends the entered information to the server. Specifically, it converts the input data into JSON format and sends it to the server as an HTTP request.

[2082] Input: Personal information entered by the user (in JSON format)

[2083] Output: Personal information passed to the server

[2084] Step 3:

[2085] The server receives user information and performs validation. Specifically, it checks the validity of the received information (e.g., whether age is a numerical value, whether gender is a valid option, whether English skills are within a certain range).

[2086] Input: User information sent from the device

[2087] Output: Validated user information

[2088] Step 4:

[2089] The server saves user information that has passed validation to the database. Specifically, it inserts the information into the MySQL database using an SQL query.

[2090] Input: Validated user information

[2091] Output: User information stored in the database

[2092] Step 5:

[2093] The interface utilizes a selection process where the user chooses the external site they want to connect to. Specifically, the user selects a site from a dropdown menu or search box and then clicks the "Connect" button.

[2094] Input: Information about the selected external website (URL, API key, etc.)

[2095] Output: External site information sent to the server by the terminal.

[2096] Step 6:

[2097] The device sends information from the selected external website to the server. Specifically, it sends the selected information to the server as an HTTP request in JSON format.

[2098] Input: Selected external website information (JSON format)

[2099] Output: External site information passed to the server

[2100] Step 7:

[2101] Based on the external site information received by the server, it establishes a connection with the external site using an API or communication protocol (e.g., REST API). Specifically, it sets the HTTP headers and request body using the received URL and API key, and sends a request to the API endpoint.

[2102] Input: External site information (URL, API key, etc.)

[2103] Output: Establishing a connection with an external site

[2104] Step 8:

[2105] The server checks whether the connection was successful and saves the status to the database. Specifically, it receives the response to the API request, checks the success status code (e.g., 200 OK), and records the status information in the database.

[2106] Input: API request response

[2107] Output: Connection status stored in the database

[2108] Step 9:

[2109] The user enters a message to initiate negotiations within the app. Specifically, they type a message in the chat window and press the "Send" button.

[2110] Input: Message entered by the user

[2111] Output: Message sent from the terminal to the server

[2112] Step 10:

[2113] The terminal sends the entered message to the server. Specifically, it sends the message to the server as an HTTP request in text format.

[2114] Input: User-entered message (text format)

[2115] Output: Message passed to the server

[2116] Step 11:

[2117] The server uses a generative artificial intelligence model (e.g., GPT-4) to translate the input message. Specifically, it sends the received message as a prompt to the generative AI model and obtains the translated text.

[2118] Input: Message entered by the user

[2119] Output: Translated message

[2120] Step 12:

[2121] The server sends the translated message to an external site. Specifically, it sets the translated text in the body of an API request and sends it to the external site's API endpoint.

[2122] Input: Translated message

[2123] Output: Translated message sent to an external site

[2124] Step 13:

[2125] The server receives replies from external websites, translates them into the user's native language, and notifies them. Specifically, it sends the reply message to an AI model that generates translations and retrieves the translation results.

[2126] Input: Reply message from an external site

[2127] Output: Translated reply message

[2128] Step 14:

[2129] The device displays the translated reply and waits for the user to type another reply. Specifically, it displays the translated text in the chat window and re-enables the interface for entering a new message.

[2130] Input: Translated reply message

[2131] Output: Translated message displayed to the user

[2132] Step 15:

[2133] The server saves the entire negotiation history to a database. It stores all sent messages and replies, as well as various metadata (such as timestamps). Specifically, it inserts messages and metadata into a PostgreSQL database using SQL queries.

[2134] Input: Negotiation history information (messages and metadata)

[2135] Output: Negotiation history stored in the database

[2136] Step 16:

[2137] After the negotiation is complete, the user accesses an interface to provide feedback. Specifically, they enter their rating and comments into the feedback form and press the "Submit" button.

[2138] Input: Feedback information (ratings and comments)

[2139] Output: Feedback sent from the terminal to the server

[2140] Step 17:

[2141] The device sends feedback information to the server. Specifically, it sends feedback data to the server in JSON format.

[2142] Input: Feedback information (JSON format)

[2143] Output: Feedback information passed to the server

[2144] Step 18:

[2145] The server saves the feedback to the database. Specifically, it inserts the feedback data into the database using an SQL query.

[2146] Input: Feedback Information

[2147] Output: Feedback information stored in the database

[2148] (Application Example 1)

[2149] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2150] When users conduct business negotiations with overseas e-commerce and retail sites, language barriers and communication obstacles are a major challenge. Furthermore, there is a need to efficiently manage these negotiation histories and feedback to improve the user's negotiation experience. Conventional systems have not consistently achieved these functions, placing a heavy burden on users, thus creating a need for a more efficient and smoother negotiation support system.

[2151] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2152] In this invention, the server includes means for storing information received from the user, means for establishing a connection with an external site, means for appropriately translating user messages into business terminology using generative artificial intelligence, means for sending the translated messages to the external site, means for translating and notifying the user of replies from the external site, means for storing negotiation history, means for collecting and storing feedback, means for storing user registration information in a database and accessing it later, means for sending automatically translated messages to the site and receiving responses, and means for storing negotiation history in a database. As a result, users can overcome language barriers and smoothly conduct business negotiations with overseas e-commerce sites, and negotiation history and feedback can also be managed efficiently.

[2153] A "user" is an individual or legal entity that uses this system to conduct business negotiations with overseas e-commerce sites and retail sites.

[2154] "Information" refers to all data entered by users, including personal information, negotiation messages, and feedback.

[2155] "External sites" refer to online platforms that users use for negotiations, such as e-commerce sites and retail sites.

[2156] "Means of establishing a connection" refers to technologies that use APIs and communication protocols to initiate communication with external sites and create a state where data exchange is possible.

[2157] "Generative artificial intelligence" is an AI technology that uses natural language processing to translate user messages into appropriate business English.

[2158] "Translation methods" refer to technologies that utilize generative artificial intelligence to convert user-inputted messages into other languages.

[2159] A "database" is a system for efficiently storing and managing data such as user information, negotiation history, and feedback.

[2160] "Means for receiving responses" refers to technologies for receiving reply messages from external sites, loading them into a server, and notifying the user.

[2161] "Negotiation history" refers to a record of all business negotiations conducted by the user, including data such as sent messages, translated messages, received messages, and timestamps.

[2162] This invention is a system that uses generative artificial intelligence to help users conduct smooth business negotiations with overseas e-commerce sites and retail sites. A detailed embodiment of the system is described below.

[2163] System Configuration

[2164] This system primarily consists of three entities: servers, terminals, and users. The processes performed by each entity, as well as the hardware and software they use, are described in detail below.

[2165] User registration and initial setup

[2166] Users launch the application using their device (smartphone, PC, etc.) and enter personal information such as age, gender, and English language skills. The device sends the collected information to the server, which validates it and then stores it in a database. This allows for the management of the user's basic profile information.

[2167] Connection with e-commerce sites and retail sites

[2168] The user selects the e-commerce or retail site they wish to connect to via the terminal's interface. The selected site information (such as URL and API key) is sent from the terminal to the server, which then establishes a connection with the external site using APIs and communication protocols. The success or failure of the connection is stored in a database.

[2169] Automatic translation and business negotiation support

[2170] The user enters a message from their device to initiate negotiations. The device sends this message to the server, which uses generative artificial intelligence to translate the message into appropriate business English. The translated message is then sent to an external website. The server receives the reply from the external website, translates it into a language the user understands, and notifies the user of the reply on their device.

[2171] Negotiation history management

[2172] The server stores the entire negotiation history in a database. This history includes all sent and received messages, as well as various metadata (such as timestamps). This data is used for future analysis and system training.

[2173] Collecting user feedback

[2174] After negotiations are complete, users provide feedback through their devices. The devices send feedback information (ratings and comments) to the server, which stores it in a database. The collected feedback is used to improve the system.

[2175] Hardware and software to use

[2176] Server: Handles data storage, processing of generated AI models, API connections, and database management.

[2177] Terminal: As a user interface, it is responsible for message input and display. Smartphones and PCs are the main hardware examples.

[2178] Generative AI model: Used to translate user messages into business English. Leverages natural language processing software such as the Google Trans library.

[2179] Examples of specifics and prompts

[2180] Specific example 1:

[2181] When user A uses the app for the first time, they register by entering their age, gender, and English proficiency. The device sends this information to the server, and the server stores the received information in a database.

[2182] Specific example 2:

[2183] User B wants to purchase an item from an American e-commerce site and types "Can you offer a discount?". The server uses generative AI to translate the message, sends it to the e-commerce site in appropriate business English, and then translates the reply into a language the user understands and notifies them.

[2184] Example of a Generative AI Model prompt:

[2185] Original text: "What is the product's stock status?"

[2186] Prompt: Translate the following sentence into business English: 'What is the product's stock status?'

[2187] Translated text: "Could you please update me on the availability of the product?"

[2188] In this way, the system enables users to conduct business negotiations smoothly, transcending language and cultural barriers.

[2189] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2190] Step 1:

[2191] The user uses their device and launches the application. The user enters personal information such as age, gender, and English proficiency, and submits it by clicking the save button.

[2192] Input: Personal information such as age, gender, and English language skills.

[2193] Output: Sent user information.

[2194] Specific operation: After the user enters information and taps the "Send" button, the device sends that information to the server.

[2195] Step 2:

[2196] The server receives user information sent from the terminal. The server validates the data and saves the information to the database.

[2197] Input: Submitted user information.

[2198] Output: User information saved as a result of validation.

[2199] Specific operation: The server checks the received data to verify that there is no invalid data. Then, it saves it to the database.

[2200] Step 3:

[2201] The user selects the external site they want to connect to (such as an e-commerce site or a retail site) using the device's interface.

[2202] Input: Information about the external website you want to connect to (such as URL or API key).

[2203] Output: Information from the selected external website.

[2204] Specific operation: The user selects an external site from a dropdown list or search function and taps the "Connect" button.

[2205] Step 4:

[2206] The device sends information about the selected external website to the server. The server then uses this information to establish a connection using APIs and communication protocols.

[2207] Input: Information from the selected external website.

[2208] Output: Success or failure of the connection.

[2209] Specific operation: The server, upon receiving information sent from the terminal, attempts to connect to an external site, determines whether the connection was successful or unsuccessful, and saves the success or failure to a database.

[2210] Step 5:

[2211] Enter a message on your device to initiate negotiations.

[2212] Input: A message to initiate negotiations.

[2213] Output: The input message.

[2214] Specific action: The user enters a negotiation message and taps the "Send" button.

[2215] Step 6:

[2216] The terminal sends the entered message to the server. The server uses generative artificial intelligence to translate the message into appropriate business English.

[2217] Input: The message entered by the user.

[2218] Output: Translated business English message.

[2219] Specific operation: The server receives the input message and performs translation using a generative AI model (e.g., the Google Trans library).

[2220] Step 7:

[2221] The server sends the translated message to an external site.

[2222] Input: Translated business English message.

[2223] Output: Message sent to an external site.

[2224] Specific operation: The server sends the translated message by calling an API on an external site.

[2225] Step 8:

[2226] The server receives a reply from an external website. It translates the reply into a language the user understands and notifies the device.

[2227] Input: Reply message from an external website.

[2228] Output: Translated reply message.

[2229] Specific operation: The server receives a reply message, translates it using a generation AI model, and sends it to the terminal.

[2230] Step 9:

[2231] The server saves the entire negotiation history to a database.

[2232] Input: Negotiation history including sent messages, replied messages, and timestamps.

[2233] Output: Saved negotiation history.

[2234] Specific operation: The server records all negotiation details in a database.

[2235] Step 10:

[2236] Users provide feedback via their devices after the negotiation is complete.

[2237] Input: Feedback information such as ratings and comments.

[2238] Output: Sent feedback information.

[2239] Specific action: The user fills out a feedback form and taps the "Submit" button.

[2240] Step 11:

[2241] The device sends feedback information to the server. The server stores it in its database.

[2242] Input: Submitted feedback information.

[2243] Output: Saved feedback information.

[2244] Specific operation: The server receives feedback information sent from the terminal and saves it to the database.

[2245] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2246] This invention is a system that combines generative AI and an emotion engine to help users conduct more effective business negotiations with overseas e-commerce and retail sites. The system's program processing is described in detail below.

[2247] User registration and initial setup

[2248] 1. The user launches the application and enters personal information such as age, gender, and English language skills.

[2249] 2. The terminal sends the entered information to the server via an HTTP request.

[2250] 3. The server receives user information, validates the input data, and then saves it to the database. This step manages the basic profile information of each user.

[2251] Connection with e-commerce sites and retail sites

[2252] 1. The user selects the e-commerce or retail site they wish to connect to via the web interface.

[2253] 2. The device sends the selected information (site URL, API key, etc.) to the server as structured data.

[2254] 3. Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[2255] 4. The server receives the API request response and checks whether the connection was successful.

[2256] 5. The server saves the connection status to the database and, if the connection is successful, notifies the user that the system can proceed to the next process.

[2257] Automatic translation and business negotiation support

[2258] 1. The user enters a text message to initiate a business negotiation into an input form within the application.

[2259] 2. The terminal sends the entered message to the server.

[2260] 3. The server processes the received message and calls a generative artificial intelligence to translate it into appropriate business English.

[2261] 4. The server sends the translated message as structured data to the API endpoint of the external site.

[2262] 5. The server receives the reply from the external site and uses generative artificial intelligence again to translate the reply into a language that the user can understand.

[2263] 6. The server sends the translated reply message to the terminal and displays it to the user through the UX / UI.

[2264] Negotiation history management

[2265] 1. The server stores a database containing the history of all messages sent and received from the start to the end of negotiations.

[2266] 2. The server adds metadata (timestamp, user ID, external site ID, etc.) to the historical data and stores it for future access and analysis.

[2267] Collecting user feedback

[2268] 1. After the negotiation is complete, the user accesses an interface for providing feedback and enters their rating and comments.

[2269] 2. The device sends feedback information (ratings, comments) to the server as structured data.

[2270] 3. The server validates the feedback it receives and saves it to the database.

[2271] 4. The server analyzes the collected feedback and uses it to improve the system.

[2272] Using an Emotion Engine

[2273] 1. When a user enters a message, the device also sends data representing the user's emotional state to the server (e.g., linguistic characteristics, facial recognition data).

[2274] 2. The server uses an emotion engine to analyze the user's emotional state from the received data.

[2275] 3. The server reflects the results of the emotional analysis into the generative artificial intelligence, which then performs the translation using appropriate tone and expression.

[2276] 4. The server records the user's emotional state along with the translation results, and, if necessary, notifies the user of appropriate advice or support information.

[2277] Specific example

[2278] Example 1: User Registration

[2279] When User A uses the app for the first time, they register by entering their age, gender, and English proficiency.

[2280] The terminal sends input information to the server, and the server stores the received information in a database.

[2281] Example 2: Negotiating with an e-commerce site

[2282] User B wants to purchase a product from an American e-commerce site and wants to negotiate the price.

[2283] User B types "Can you offer a discount?" and the terminal sends the message to the server.

[2284] The server uses generative AI to translate and send the message to the e-commerce site in appropriate business English.

[2285] The server receives replies from e-commerce sites, translates them into a language the user understands, and notifies the user's device.

[2286] Example 3: Using an Emotion Engine

[2287] User C types "I am very frustrated with the delay" during negotiations.

[2288] The device sends facial recognition data and voice tone data to the server along with the message.

[2289] The server uses an emotion engine to recognize user C's emotional state as "frustrated."

[2290] The server considers the emotional state and translates in an appropriate tone through a generative AI.

[2291] The server generates the translation "I understand your frustration and will expedite your request." and notifies the terminal.

[2292] Thus, the present invention is a system that integrates a generative AI and an emotion engine, enabling users to conduct business negotiations more smoothly, transcending language and cultural differences.

[2293] The following describes the processing flow.

[2294] User registration and initial setup

[2295] Step 1:

[2296] The user launches the application and enters personal information such as age, gender, and English language skills.

[2297] Step 2:

[2298] The terminal sends the entered information to the server via an HTTP request.

[2299] Step 3:

[2300] The server receives user information and validates the input data, checking for any inappropriate data.

[2301] Step 4:

[2302] The server establishes a database connection and saves user information that has passed validation to the database.

[2303] Connection with e-commerce sites and retail sites

[2304] Step 1:

[2305] Users select the e-commerce or retail site they want to connect to via a web interface.

[2306] Step 2:

[2307] The device sends selected information (site URL, API key, etc.) to the server as structured data.

[2308] Step 3:

[2309] Based on the information received by the server, it obtains authentication information for connecting to an external API and makes an API request to connect to the external site.

[2310] Step 4:

[2311] The server receives the API request response and checks whether the connection was successful.

[2312] Step 5:

[2313] ...

Claims

1. A means of storing information received from the user, Means for establishing connections with external sites, A method for translating user messages using generative artificial intelligence, A means of sending the translated message to an external site, A means of translating and notifying users of replies from external sites, A means of saving the negotiation history, A means of collecting and storing feedback, A system that includes this.

2. The system according to claim 1, comprising means for translating user messages into appropriate business terms using generative artificial intelligence.

3. The system according to claim 1, comprising means for confirming the success or failure of an external site connection and saving the connection status.

Images