system

Abstract

We provide the system. [Solution] A means of receiving text data entered by the user, A means for analyzing received text data using natural language processing and extracting the context of the message, A means of translating or interpreting text based on analyzed data and referring to the cultural background data of the recipient, To promote online interaction between different cultures, we offer a means to suggest appropriate communication styles to users and recommend conversation topics. A means of collecting user feedback and using it to improve the system, 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 persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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] In communication with people having different cultures and languages, there is a problem that misunderstandings and frictions caused by cultural differences become obstacles to communication, adversely affecting business and personal relationships. To solve this problem, there is a need for a system that provides appropriate translation and interpretation considering the cultural background to achieve smooth communication.

Means for Solving the Problems

[0005] This invention provides a means for receiving text data entered by a user and analyzing that text using natural language processing technology. Furthermore, it constructs a system that includes means for referencing the recipient's cultural background data based on the analyzed data and performing optimal translation and interpretation. In addition, by providing means for suggesting an appropriate communication style to the user and means for collecting feedback to improve the system's accuracy, it realizes effective cross-cultural communication.

[0006] A "user" is an entity that uses a system to input text data and engage in cross-cultural communication.

[0007] "Text data" refers to character information entered by a user, including the content of messages and information transmissions.

[0008] "Natural language processing" is a technology that uses machine learning to analyze text data and understand its sentence structure and meaning.

[0009] "Cultural background data" refers to data such as linguistic characteristics, customs, and values ​​associated with a particular culture or country.

[0010] Translation is the process of converting text data from one language to another.

[0011] "Interpretation" is the act of understanding the meaning of a received message and conveying the appropriate meaning according to the context.

[0012] "Communication style" is a general term for the methods of expression and communication techniques used in interacting with others.

[0013] "Feedback" refers to evaluation information provided by users regarding the usability of the system and the accuracy of translations. [Brief explanation of the drawing]

[0014] [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 multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple 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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is an advanced system for supporting intercultural communication, which handles everything from receiving and analyzing text data to translation, suggestions, and feedback collection. The processing of this system's program is described below in natural language.

[0036] The terminal retrieves text data entered by the user. This text contains a message that the user is conveying to someone from a different culture. The user's input is quickly sent to the server, and the server begins processing it.

[0037] The server first analyzes the received text. This analysis utilizes natural language processing techniques, including understanding the text's grammatical structure, sentiment, and topic. Based on the analysis results, the server references the recipient's cultural background data to perform contextually appropriate translations and interpretations. Generative AI technology is used to provide natural and culture-appropriate translation results.

[0038] The server further suggests effective communication styles to the user, including greetings in a business setting and expressions adapted to the customs of the other party's country. This allows the user to communicate smoothly while avoiding cultural misunderstandings.

[0039] For example, when a Japanese user sends an email to an American partner, they may want to convey the nuance of "I want them to understand the situation subtly." The server translates this intention into something like "I would like to explain the situation specifically and request a clear response," recommending direct communication that aligns with American culture. In this process, the server automatically generates the most appropriate expression to accurately convey the user's intention.

[0040] Finally, the terminal receives feedback from users regarding the system's translation accuracy and the usefulness of its suggestions. This feedback is sent to the server and used to improve the system. Based on user feedback, the system enhances the accuracy of its cultural background database and natural language processing algorithms, which helps support future communications.

[0041] In this way, the system of the present invention can significantly reduce misunderstandings between cultures and enable smooth and effective communication.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user uses their device to type a text message they want to send to someone from a different culture. The device receives this text data and, once ready, sends it to the server.

[0045] Step 2:

[0046] The server analyzes the text data received from the terminal. Using natural language processing techniques, it analyzes the grammatical structure, keywords, and intent of the text to understand the meaning of the message.

[0047] Step 3:

[0048] Based on the analysis results, the server consults a cultural background database. It retrieves cultural background information for both the user and the recipient, and generates appropriate translations and interpretations that are suitable for the context of the message.

[0049] Step 4:

[0050] By utilizing generative AI technology, the server creates natural-sounding translations or interpretations that are appropriate to the context. This process derives expressions that are relevant to the target culture.

[0051] Step 5:

[0052] The server offers communication style suggestions to the user. For example, it provides advice on how to greet someone and what expressions are appropriate to use in messages.

[0053] Step 6:

[0054] The server sends the generated translation results and communication style suggestions to the terminal. The terminal displays this to the user and prompts them to review and edit the message.

[0055] Step 7:

[0056] The user reviews the translation and edits the message as needed. After deciding on the final message, it is sent from the device to the recipient.

[0057] Step 8:

[0058] The terminal collects user feedback regarding system usage. This feedback is sent to the server and used for future improvements.

[0059] (Example 1)

[0060] 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."

[0061] Intercultural communication often leads to misunderstandings and friction due to differences in language and culture, making smooth and accurate information transmission difficult. This invention aims to overcome such challenges in intercultural communication and achieve better mutual understanding and information transmission.

[0062] 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.

[0063] In this invention, the server includes means for receiving information entered by a user, means for processing the received information by language analysis and extracting the context of the message, and means for translating or interpreting the information based on the analyzed information and referring to the cultural background of the recipient. This enables effective and accurate information transmission between different cultures.

[0064] A "user" is an individual or organization that uses the system to create or receive cross-cultural information.

[0065] "Information" refers to text data and other digital content that users input or submit.

[0066] "Means" refers to a device or method for performing a specific function.

[0067] A "server" is a central computer system that performs information analysis and processing.

[0068] "Linguistic analysis" is the process of analyzing information using natural language processing techniques to extract context and emotions.

[0069] "Cultural background" refers to insights into the recipient's culture that are taken into consideration to improve the accuracy of information translation and interpretation.

[0070] "Translation or interpretation" is the act of converting information into a format that the recipient can understand in order to facilitate communication between different cultures.

[0071] A "data structure" is an organized digital format for efficiently storing and managing information.

[0072] "Generative AI technology" refers to technology that uses artificial intelligence to automatically generate and process information.

[0073] This invention is an advanced system that supports intercultural communication, handling everything from information reception and analysis to translation, proposal, and feedback collection in a consistent manner.

[0074] The terminal first receives information entered by the user. The user enters the message using a text box or voice input. For example, when a user enters a business email, they use an application on their smartphone or computer. This information is sent to the server via the network.

[0075] The server processes the received information in detail through language analysis. Specifically, it uses natural language processing techniques to extract the grammatical structure, sentiment, and topic of the information. The server utilizes OpenAI® generative AI models and similar technologies to improve analysis accuracy. An example of a prompt can be used: "Analyze the sentiment and topic of this message."

[0076] Subsequently, the server performs an appropriate translation or interpretation based on the analysis results, taking into account the cultural background of the recipient. General translation services provided via the API can be used for translation, generating expressions that accurately convey the user's intent.

[0077] Furthermore, the server will suggest the optimal communication method to the user. For example, it will show the format of business letters in different cultures and specific greeting phrases. In this case as well, it will use generative AI technology to suggest the best style. For example, a prompt such as "Suggest an email style suitable for American business" might be used.

[0078] Finally, the terminal uses the system's feedback function to collect user responses regarding translation accuracy and the usefulness of suggestions. Users can easily submit their opinions through a feedback form. This feedback information is sent to the server and used to improve the system in the future.

[0079] By implementing this system, barriers to intercultural communication can be effectively reduced, enabling smooth and accurate information transfer.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The device receives information entered by the user. This information is typically text messages intended for transmission across different cultures. For example, it often includes the content of business emails. This information is temporarily stored on the device.

[0083] Step 2:

[0084] The terminal sends the received information to the server. The data is typically transmitted using a secure communication protocol. Specifically, HTTPS is used to encrypt the information and transmit it quickly to the server.

[0085] Step 3:

[0086] The server analyzes the received information. Using text data as input, a language processing engine analyzes grammatical structure and sentiment. A generative AI model is utilized in this analysis. The prompt used is "Analyze the subject and sentiment of this message." As a result, the server grasps the context and outputs the analysis results.

[0087] Step 4:

[0088] The server translates or interprets the information based on the analysis results. In doing so, it refers to cultural background data to set appropriate expressions. Analysis data and cultural background information are used as input, and translated text is generated as output. A common translation API service is used for translation.

[0089] Step 5:

[0090] The server proposes methods for communicating with the user. It provides specific examples and gives prompts to the generating AI, such as "Please tell me an appropriate email greeting for American business." The generating AI model is used as input, and a proposal document is created as output.

[0091] Step 6:

[0092] The terminal displays the translated text and proposal sent back from the server to the user. The user can review the received information and edit the message as needed.

[0093] Step 7:

[0094] The device accepts user feedback. Users fill out a displayed form with their opinions on translation accuracy and suggestions, and then submit it. The feedback is forwarded directly to the server and used as data to improve the service.

[0095] (Application Example 1)

[0096] 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."

[0097] In today's globalized society, communication with people from diverse cultural backgrounds is crucial, but cultural misunderstandings and inappropriate expressions often arise. Traditional translation systems struggle to capture cultural nuances and contexts, resulting in a decline in the quality of communication. Furthermore, effective means of facilitating real-time intercultural exchange are lacking. To improve this situation, a system is needed that deepens cultural understanding and enables smooth and effective communication.

[0098] 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.

[0099] In this invention, the server includes means for receiving text data entered by a user, means for analyzing the received text data using natural language processing and extracting the context of the message, means for translating or interpreting the text based on the analyzed data and referring to the recipient's cultural background data, means for suggesting an appropriate communication style to the user and recommending conversation topics to promote cross-cultural online communication, and means for collecting user feedback and using it to improve the system. This significantly reduces misunderstandings between cultures and enables real-time and effective communication.

[0100] A "user" refers to an individual or group that uses a system to facilitate intercultural communication.

[0101] "Text data" refers to written information that users input to engage in cross-cultural communication.

[0102] "Natural language processing" refers to computer techniques used to analyze the structure and meaning of text data.

[0103] "Message context" refers to information that includes meaning and relationships within the text data.

[0104] "Cultural background data" refers to information that includes customs and values ​​related to intercultural communication.

[0105] "Translation or interpretation" refers to the act of transforming the content of text data into a culturally appropriate form.

[0106] "Communication style" refers to the methods of expression and attitudes used to smoothly transmit information across different cultures.

[0107] "Exchange topics" refer to themes or topics offered to facilitate intercultural conversation and discussion.

[0108] "Feedback" refers to users' opinions and evaluations of system suggestions and translations.

[0109] "System improvement" refers to the process of improving the overall performance and accuracy of a system based on user feedback.

[0110] In order to implement this invention, it is necessary to build an advanced system that supports intercultural communication. This system will be implemented as follows.

[0111] The server receives text data from users via the internet. This text data contains messages that users want to convey to people from different cultures. Next, the server analyzes this text data using natural language processing techniques. Specifically, it performs grammatical structure analysis and sentiment analysis using Python libraries such as spaCy and NLTK.

[0112] Based on the analyzed data, the server refers to a cultural background database to perform translations and interpretations appropriate to the recipient's culture. Generative AI technology used includes, for example, OpenAI's GPT-3® model. Prompts are given to this model to generate natural expressions that take cultural nuances into account.

[0113] Furthermore, the server suggests effective communication styles to users. One specific application is the smartphone application "Culture Cafe," which provides users with appropriate topics and question formats for intercultural exchange.

[0114] Users receive translation results and communication style suggestions from the system, allowing them to proceed with conversations with people from different cultures based on these. For example, when a Japanese user talks to a Brazilian user about the topic of "the four seasons of Japan," the system suggests appropriate translations along with questions such as, "Which season is the Brazilian user most interested in?"

[0115] Furthermore, this system accepts user feedback and uses it to improve the system. This feedback is aggregated on the server and contributes to improving translation accuracy and the quality of recommendation features in future conversations.

[0116] As an example of a prompt sentence, the system uses a method where the AI ​​is input in the format "I want to discuss Japan's seasonal customs with my Brazilian friend," and then generates an appropriate translation and a conversation example that is relevant to the cultural context. In this way, a system that supports smooth and effective intercultural communication is realized.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The terminal receives input from the user. It receives text data as input and prepares to send that data to a server over the internet. This text data contains a message shared across different cultures.

[0120] Step 2:

[0121] The server analyzes the text data it receives. It takes text data as input and performs grammatical analysis and sentiment analysis using natural language processing libraries (e.g., spaCy, NLTK). This deepens the understanding of the message's context and topic. The output is the analysis result.

[0122] Step 3:

[0123] The server performs translation and interpretation based on the analysis results, referencing a cultural background database. Using the analyzed data and cultural background information as input, it generates contextually appropriate translations using a generative AI model (e.g., GPT-3). The output is a culturally appropriate translation.

[0124] Step 4:

[0125] The server suggests communication styles to the user. Based on the user's message and the recipient's cultural background, it generates appropriate communication methods and conversation topics as input. The output is a summary of the suggested content.

[0126] Step 5:

[0127] The device presents the user with translation results and suggestions. As input, it displays the translation results and suggestions received from the server to the user, facilitating cross-cultural conversation. This presentation prepares the user for effective communication.

[0128] Step 6:

[0129] The user provides feedback. This feedback includes comments on the quality of the translation and the usefulness of the suggestions, and the device prepares to send this information to the server.

[0130] Step 7:

[0131] The server receives user feedback and uses it to improve the system. As input, it acquires user feedback, which is used to improve cultural background data and the accuracy of algorithms. As output, it develops plans for future system improvements.

[0132] 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.

[0133] This invention is an advanced system that supports intercultural communication. It analyzes text data entered by the user and provides translations and suggestions that take cultural backgrounds and emotions into consideration. By incorporating an emotion engine, this system can recognize the user's emotions and propose a communication style that takes them into account.

[0134] First, the terminal receives text data from the user and sends that data to the server. The server analyzes the received text using natural language processing technology to extract the context and sentiment of the message. The sentiment engine built into the server detects sentiment from the user's input text and calculates sentiment scores and categories.

[0135] The analyzed data is integrated with cultural background data as needed, and the server performs optimal translation and interpretation while considering the recipient's culture and the user's emotions. Using generative AI technology, it is possible to generate natural, contextually relevant translations and construct emotionally sensitive messages.

[0136] Furthermore, the server suggests communication styles to the user based on detected emotions. For example, if the user is feeling stressed, it can suggest calm and considerate language. This kind of advice can be applied in both business settings and personal interactions.

[0137] For example, if a user wants to send an emotionally charged message to an overseas business partner stating, "Today's meeting just didn't go well," this system recognizes the user's emotions and suggests a way to provide constructive feedback while maintaining composure. This approach helps avoid misunderstandings and mitigate emotional misinterpretations.

[0138] Finally, the translation results and suggested styles are sent to the terminal and shown to the user. The user then reviews and edits the message based on these suggestions and sends it as needed. In addition, the terminal receives user feedback on the system's processing and sends it to the server. This feedback helps improve the system's accuracy.

[0139] Overall, this system will be a powerful tool for users to communicate effectively across cultures.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The user types a message into the device. This message contains what they want to convey to the recipient and their feelings at that time. The device sends the entered text data to the server.

[0143] Step 2:

[0144] The server analyzes the text data received from the terminal. Using natural language processing techniques, it extracts the grammatical structure and keywords of the message to understand its intent and theme.

[0145] Step 3:

[0146] The emotion engine on the server performs sentiment analysis on the text data. Through this analysis, it determines the type and intensity of the emotions the user is expressing and generates an emotion score.

[0147] Step 4:

[0148] The server uses the analyzed data to reference the cultural background data of the user and the recipient. This enables contextually appropriate translation or interpretation.

[0149] Step 5:

[0150] The server uses generative AI technology to create translations and interpretations that take cultural context and user emotions into consideration. These translations are then formatted to be natural and easily understood by the recipient.

[0151] Step 6:

[0152] The server utilizes the results of the emotion engine to suggest a communication style that suits the user. For example, when emotions are heightened, it recommends using calm and composed language.

[0153] Step 7:

[0154] The server sends the generated translation results and communication style suggestions to the terminal. The terminal displays this information to the user and allows them to confirm the message.

[0155] Step 8:

[0156] The user reviews the message based on the suggested translation and style, makes any necessary edits, and then sends it.

[0157] Step 9:

[0158] The terminal collects feedback from users about the system. This feedback is sent to the server and used to improve the system.

[0159] (Example 2)

[0160] 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".

[0161] Intercultural communication presents challenges due to the ease with which misunderstandings can arise from differences in cultural backgrounds and emotions. There is a need to reduce such misunderstandings and improve the ability to convey messages efficiently and accurately. Furthermore, there is a need to go beyond mere translation and propose communication styles that take emotions into consideration.

[0162] 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.

[0163] In this invention, the server includes means for receiving information input by a user, means for analyzing the received information using natural language processing to extract context and emotions, and means for detecting and quantifying emotions from the analyzed information. This enables effective communication across cultures.

[0164] "Information" refers to text data that users input into the system, as well as data related to the context, emotions, and cultural background of that text data.

[0165] "Natural language processing" refers to the technology that enables computers to understand, analyze, and generate human language, and is used to extract context and sentiment from text data.

[0166] "Emotion detection" refers to the process of identifying the type and intensity of emotions from input information and quantifying them as a specific score or category.

[0167] "Cultural background information" refers to data related to values, customs, and communication styles specific to a particular country, region, or group.

[0168] "Generative artificial intelligence technology" refers to technology that naturally generates translations and interpretations based on input data, supporting communication tailored to the user's needs.

[0169] "Communication style" refers to the way a message is expressed and its tone, and the style suggested to best convey the intended meaning to the recipient.

[0170] This invention is a system aimed at improving intercultural communication, which translates and interprets information based on user input, incorporating emotional analysis and cultural considerations. The system consists of a terminal, a server, and a generative AI model.

[0171] The terminal is responsible for receiving information from the user. This information is primarily text data and includes the user's emotions and intentions. This information is transmitted to the server using a secure communication protocol.

[0172] The server analyzes received information using natural language processing techniques. These techniques include morphological analysis, contextual understanding, and sentiment analysis, aiming to extract context and emotion from the information. Furthermore, the server incorporates an emotion engine that detects emotions from input information and quantifies them as scores or categories. This process is crucial for accurately understanding the intent of messages by quantifying the intensity of emotions.

[0173] The analyzed data is integrated with cultural background information. This is a crucial step to avoid misunderstandings with recipients from different cultures. Based on this analysis, the generative AI model generates natural and contextually appropriate translations and interpretations, constructing messages that are sensitive to emotions and culture. This goes beyond simple translation and enables information transmission optimized for the recipient's cultural context.

[0174] For example, if a user wants to send a reply to an overseas business partner that includes constructive feedback while avoiding negative feelings, this system can analyze the user's input text, "I want to convey my concerns about next week's meeting," and suggest appropriate and considerate phrasing. An example of a prompt sentence to input into the generating AI model would be, "Please suggest a reply in a business email that includes constructive feedback while avoiding negative feelings."

[0175] As described above, this system provides users with a powerful tool to support intercultural communication.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] The terminal receives text data from the user as input. This input contains information including the message and intentions the user wants to send. The terminal applies security protocols such as encryption to securely transmit this text data to the server.

[0179] Step 2:

[0180] The server receives text data sent from the terminal. This input is analyzed by a natural language processing unit to extract context, keywords, and signs of sentiment. The output of the data analysis is contextual and sentimental information of the message, which is used as foundational data for subsequent processing.

[0181] Step 3:

[0182] The emotion engine installed on the server receives analyzed contextual information as input, detects and quantifies the emotions within the text. This process outputs emotion scores and categories, forming a basis for determining how positive or negative a message is.

[0183] Step 4:

[0184] The server uses the obtained analytical and sentiment data as input and references the recipient's cultural background database. It translates and interprets messages to avoid cross-cultural misunderstandings. The output of this step is a culturally adapted, contextual, and sentiment-sensitive translation.

[0185] Step 5:

[0186] The generative AI model on the server uses the output of the translation process to construct the text. This process performs translation or interpretation in a natural way that aligns with the user's intent. The final output of this step is a natural message that is relevant to the transformed context.

[0187] Step 6:

[0188] The server, along with the generated message, suggests an appropriate communication style to the user. For example, the suggestion may include constructive language to avoid emotional misunderstandings. This suggestion is sent to the terminal as the final output.

[0189] Step 7:

[0190] The terminal displays the user the translation results and communication style suggestions sent from the server. The user reviews the message based on this output and edits it as needed. As a result of this process, the user is ready to create and send the final message.

[0191] Step 8:

[0192] The terminal collects user editing actions and feedback and sends them to the server. This feedback helps improve the system and increase its accuracy, and the accumulation of appropriate responses leads to better processing in the future.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] In modern society, intercultural communication can lead to misunderstandings and problems not only due to language differences but also to differences in cultural backgrounds and emotions. Such misunderstandings can create friction between individuals and organizations, hindering smooth communication. In particular, multinational environments demand rapid and appropriate communication, and conventional technologies offer limited means to adequately support this.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0197] In this invention, the server includes means for detecting the user's emotional state and generating communication content based on the detection results, means for suggesting an appropriate communication style to the user, and means for collecting evaluation information from the user and using it to improve the system. This makes it possible for users to achieve appropriate communication that takes into account their emotions and culture, and to reduce misunderstandings between cultures.

[0198] A "user" is an individual or organization that provides input data using an information system.

[0199] "Information data" refers to text and other forms of data entered by users that are processed by the system.

[0200] "Means of receiving" refers to a device or program that has the function of acquiring information data provided by the user.

[0201] "Language processing" refers to the techniques used to analyze natural language and understand its meaning and context.

[0202] "Means of analysis" refers to a device or program that performs language processing on information data and has the function of extracting necessary information.

[0203] "Cultural background information" refers to information that includes customs, values, and linguistic characteristics associated with a particular society or group.

[0204] "Means for translation or interpretation" refers to a device or program that has the function of transforming analyzed information data to suit another language or context.

[0205] A "communication style" is a method of selecting language and expressions to suit a specific context or purpose.

[0206] "Means of suggestion" refers to a device or program that has the function of presenting appropriate actions or options to the user.

[0207] "Means for detecting emotional states" refers to a device or program that analyzes emotions from user input data and identifies a specific emotional state.

[0208] "Evaluation information" refers to data on evaluations and feedback that users provide regarding the services offered by the system.

[0209] An "information storage device" is a device for storing information data and background information, and it is intended to make this information accessible to the system.

[0210] "Computational intelligence technology" refers to technologies that use artificial intelligence to perform specific computational processes and make decisions.

[0211] The system realizing this invention includes a server that starts operating upon user input and has the function of precisely analyzing information. Specifically, the user inputs information data (text) using a terminal and sends that information data to the server. The server analyzes the information data using a language processing program (e.g., TextBlob library) and extracts context and sentiment. Furthermore, based on the analyzed data, it refers to cultural background information and utilizes computational intelligence technology (e.g., OpenAI API) to generate an appropriate translation or interpretation.

[0212] The server also has the ability to detect the user's emotional state and suggest an appropriate communication style based on that state. These suggestions are an important element in enabling users to communicate smoothly with people from different cultural backgrounds. By providing emotionally-based suggestions, it is possible to avoid misunderstandings and promote effective communication.

[0213] Furthermore, the server collects user feedback and uses this to improve the system's accuracy and effectiveness. For example, if a traveler wants to discuss an inappropriate order at a restaurant, the server will suggest a translation that soothes the user's feelings, generating a prompt such as, "Please translate 'The order was wrong' into Italian in a gentle and calm manner."

[0214] This system enables users to engage in sophisticated communication that takes culture and emotions into account in their daily lives and business environments.

[0215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0216] Step 1:

[0217] The user inputs information data (input text) through a terminal. This input includes the user's emotions and messages. The input data is sent from the terminal to the server. Here, input involves manual user interaction, while output is raw information data received on the server side.

[0218] Step 2:

[0219] The server analyzes the received information data using a language processing program. Specifically, it uses the TextBlob library to extract context and sentiment from the information data. The input for this step is the received information data, and the output is the analyzed context information and sentiment score.

[0220] Step 3:

[0221] The server creates a translation or interpretation based on the analyzed information and references cultural background information. This process utilizes the OpenAI API as a computational intelligence technology to generate a translation that takes into account the user's emotions and the culture of the recipient. The input is the contextual information and emotion score obtained in the previous step, and the output is the proposed translation.

[0222] Step 4:

[0223] The server provides the user with a translation and suggests an appropriate communication style. This style suggestion utilizes a generative AI model to create prompts. The input is the translation, and the output is a specific recommendation of a communication style based on the translation.

[0224] Step 5:

[0225] The user reviews the translation and style suggestions provided by the server on their terminal. The user modifies the suggestions as needed and sends the final message. In this step, the input is the server's suggestions, and the output is the user's edited final message.

[0226] Step 6:

[0227] The terminal collects user feedback and sends it to the server to help improve the system. The server uses the feedback to improve the accuracy of prompt messages, update cultural background information, and so on. The input to this feedback cycle is user evaluation information, and the output is improved system performance.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] [Second Embodiment]

[0232] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0233] 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.

[0234] 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).

[0235] 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.

[0236] 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.

[0237] 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).

[0238] 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.

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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".

[0244] This invention is an advanced system for supporting intercultural communication, which handles everything from receiving and analyzing text data to translation, suggestions, and feedback collection. The processing of this system's program is described below in natural language.

[0245] The terminal retrieves text data entered by the user. This text contains a message that the user is conveying to someone from a different culture. The user's input is quickly sent to the server, and the server begins processing it.

[0246] The server first analyzes the received text. This analysis utilizes natural language processing techniques, including understanding the text's grammatical structure, sentiment, and topic. Based on the analysis results, the server references the recipient's cultural background data to perform contextually appropriate translations and interpretations. Generative AI technology is used to provide natural and culture-appropriate translation results.

[0247] The server further suggests effective communication styles to the user, including greetings in a business setting and expressions adapted to the customs of the other party's country. This allows the user to communicate smoothly while avoiding cultural misunderstandings.

[0248] For example, when a Japanese user sends an email to an American partner, they may want to convey the nuance of "I want them to understand the situation subtly." The server translates this intention into something like "I would like to explain the situation specifically and request a clear response," recommending direct communication that aligns with American culture. In this process, the server automatically generates the most appropriate expression to accurately convey the user's intention.

[0249] Finally, the terminal receives feedback from users regarding the system's translation accuracy and the usefulness of its suggestions. This feedback is sent to the server and used to improve the system. Based on user feedback, the system enhances the accuracy of its cultural background database and natural language processing algorithms, which helps support future communications.

[0250] In this way, the system of the present invention can significantly reduce misunderstandings between cultures and enable smooth and effective communication.

[0251] The following describes the processing flow.

[0252] Step 1:

[0253] The user uses their device to type a text message they want to send to someone from a different culture. The device receives this text data and, once ready, sends it to the server.

[0254] Step 2:

[0255] The server analyzes the text data received from the terminal. Using natural language processing techniques, it analyzes the grammatical structure, keywords, and intent of the text to understand the meaning of the message.

[0256] Step 3:

[0257] Based on the analysis results, the server consults a cultural background database. It retrieves cultural background information for both the user and the recipient, and generates appropriate translations and interpretations that are suitable for the context of the message.

[0258] Step 4:

[0259] By utilizing generative AI technology, the server creates natural-sounding translations or interpretations that are appropriate to the context. This process derives expressions that are relevant to the target culture.

[0260] Step 5:

[0261] The server offers communication style suggestions to the user. For example, it provides advice on how to greet someone and what expressions are appropriate to use in messages.

[0262] Step 6:

[0263] The server sends the generated translation results and communication style suggestions to the terminal. The terminal displays this to the user and prompts them to review and edit the message.

[0264] Step 7:

[0265] The user reviews the translation and edits the message as needed. After deciding on the final message, it is sent from the device to the recipient.

[0266] Step 8:

[0267] The terminal collects user feedback regarding system usage. This feedback is sent to the server and used for future improvements.

[0268] (Example 1)

[0269] 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."

[0270] Intercultural communication often leads to misunderstandings and friction due to differences in language and culture, making smooth and accurate information transmission difficult. This invention aims to overcome such challenges in intercultural communication and achieve better mutual understanding and information transmission.

[0271] 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.

[0272] In this invention, the server includes means for receiving information entered by a user, means for processing the received information by language analysis and extracting the context of the message, and means for translating or interpreting the information based on the analyzed information and referring to the cultural background of the recipient. This enables effective and accurate information transmission between different cultures.

[0273] A "user" is an individual or organization that uses the system to create or receive cross-cultural information.

[0274] "Information" refers to text data and other digital content that users input or submit.

[0275] "Means" refers to a device or method for performing a specific function.

[0276] A "server" is a central computer system that analyzes and processes information.

[0277] "Language analysis" is a process of analyzing information using natural language processing technology to extract context and sentiment.

[0278] "Cultural background" refers to knowledge about the recipient's culture that is considered to improve the accuracy of information translation and interpretation.

[0279] "Translation or interpretation" is an act of converting information into a form understandable by the recipient to facilitate communication between different cultures.

[0280] "Data structure" is an organized digital format for efficiently storing and managing information.

[0281] "Generative AI technology" refers to technology that uses artificial intelligence to automatically generate and process information.

[0282] The present invention is an advanced system that supports communication between different cultures and consistently performs operations from information reception to analysis, translation, proposal, and feedback collection.

[0283] The terminal first receives the information input by the user. The user enters a message using a text box or voice input. For example, when the user inputs a business email, they use an application on a smartphone or a personal computer. This information is transmitted to the server via a network.

[0284] The server processes the received information in more detail through language analysis. Specifically, using natural language processing technology, it extracts the grammar structure, sentiment, and topic of the information. The server utilizes OpenAI's generative AI model or similar technologies to improve the analysis accuracy. Also, as an example of a prompt sentence, "Analyze the sentiment and topic of this message" can be used.

[0285] After that, based on the analysis results, the server performs an appropriate translation or interpretation by referring to the cultural background of the recipient. For translation, it is possible to use general translation services provided through APIs. This generates an expression for accurately conveying the user's intention.

[0286] Furthermore, the server presents the user with the optimal communication method. For example, it shows the format of business letters in different cultures and specific greeting phrases. In this case as well, generative AI technology is used to propose the best style. For example, a prompt sentence such as "Propose how to write an email suitable for American business" can be considered.

[0287] Finally, the terminal uses the system's feedback function to collect the user's response regarding the accuracy of the translation and the usefulness of the proposal. The user can easily send their opinions through a feedback form. This feedback information is sent to the server and used for future system improvement.

[0288] By implementing this system, the barriers in cross-cultural communication can be effectively reduced, and smooth and accurate information transmission can be achieved.

[0289] The flow of specific processing in Example 1 will be described using FIG. 11.

[0290] Step 1:

[0291] The terminal receives the information input by the user. What is input is a text message scheduled to be sent across different cultures. For example, the content of a business email is often input. This information is temporarily stored on the terminal.

[0292] Step 2:

[0293] The terminal sends the received information to the server. The data is typically transmitted using a secure communication protocol. Specifically, HTTPS is used to encrypt the information and transmit it quickly to the server.

[0294] Step 3:

[0295] The server analyzes the received information. Using text data as input, a language processing engine analyzes grammatical structure and sentiment. A generative AI model is utilized in this analysis. The prompt used is "Analyze the subject and sentiment of this message." As a result, the server grasps the context and outputs the analysis results.

[0296] Step 4:

[0297] The server translates or interprets the information based on the analysis results. In doing so, it refers to cultural background data to set appropriate expressions. Analysis data and cultural background information are used as input, and translated text is generated as output. A common translation API service is used for translation.

[0298] Step 5:

[0299] The server proposes methods for communicating with the user. It provides specific examples and gives prompts to the generating AI, such as "Please tell me an appropriate email greeting for American business." The generating AI model is used as input, and a proposal document is created as output.

[0300] Step 6:

[0301] The terminal displays the translated text and proposal sent back from the server to the user. The user can review the received information and edit the message as needed.

[0302] Step 7:

[0303] The terminal receives feedback from the user. The user writes and sends opinions on the translation accuracy and suggestions in the displayed form. The feedback is directly transferred to the server and used as data for service improvement.

[0304] (Application Example 1)

[0305] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0306] In modern globalized society, communication with people from different cultural backgrounds is important, but cultural misunderstandings and inappropriate expressions often occur during this process. Conventional translation systems have difficulty in translating while considering cultural nuances and contexts, resulting in a problem of declining communication quality. In addition, there is also a lack of effective means to promote real-time cross-cultural communication. To improve such a situation, a system that deepens cultural understanding and realizes smooth and effective communication is required.

[0307] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0308] In this invention, the server includes means for receiving text data input by the user, means for analyzing the received text data by natural language processing to extract the context of the message, means for translating or interpreting the text by referring to the cultural background data of the destination based on the analyzed data, means for proposing an appropriate communication style to the user and recommending communication topics to promote online communication between different cultures, and means for collecting feedback from the user and using it for system improvement. Thereby, misunderstandings between different cultures can be significantly reduced, and real-time and effective communication becomes possible.

[0309] A "user" refers to an individual or group that uses a system to facilitate intercultural communication.

[0310] "Text data" refers to written information that users input to engage in cross-cultural communication.

[0311] "Natural language processing" refers to computer techniques used to analyze the structure and meaning of text data.

[0312] "Message context" refers to information that includes meaning and relationships within the text data.

[0313] "Cultural background data" refers to information that includes customs and values ​​related to intercultural communication.

[0314] "Translation or interpretation" refers to the act of transforming the content of text data into a culturally appropriate form.

[0315] "Communication style" refers to the methods of expression and attitudes used to smoothly transmit information across different cultures.

[0316] "Exchange topics" refer to themes or topics offered to facilitate intercultural conversation and discussion.

[0317] "Feedback" refers to users' opinions and evaluations of system suggestions and translations.

[0318] "System improvement" refers to the process of improving the overall performance and accuracy of a system based on user feedback.

[0319] In order to implement this invention, it is necessary to build an advanced system that supports intercultural communication. This system will be implemented as follows.

[0320] The server receives text data from users via the internet. This text data contains messages that users want to convey to people from different cultures. Next, the server analyzes this text data using natural language processing techniques. Specifically, it performs grammatical structure analysis and sentiment analysis using Python libraries such as spaCy and NLTK.

[0321] Based on the analyzed data, the server refers to a cultural background database to perform translations and interpretations appropriate to the recipient's culture. Generative AI technology used includes, for example, OpenAI's GPT-3 model. Prompts are given to this model to generate natural expressions that take cultural nuances into account.

[0322] Furthermore, the server suggests effective communication styles to users. One specific application is the smartphone application "Culture Cafe," which provides users with appropriate topics and question formats for intercultural exchange.

[0323] Users receive translation results and communication style suggestions from the system, allowing them to proceed with conversations with people from different cultures based on these. For example, when a Japanese user talks to a Brazilian user about the topic of "the four seasons of Japan," the system suggests appropriate translations along with questions such as, "Which season is the Brazilian user most interested in?"

[0324] Furthermore, this system accepts user feedback and uses it to improve the system. This feedback is aggregated on the server and contributes to improving translation accuracy and the quality of recommendation features in future conversations.

[0325] As an example of a prompt sentence, the system uses a method where the AI ​​is input in the format "I want to discuss Japan's seasonal customs with my Brazilian friend," and then generates an appropriate translation and a conversation example that is relevant to the cultural context. In this way, a system that supports smooth and effective intercultural communication is realized.

[0326] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0327] Step 1:

[0328] The terminal receives input from the user. It receives text data as input and prepares to send that data to a server over the internet. This text data contains a message shared across different cultures.

[0329] Step 2:

[0330] The server analyzes the text data it receives. It takes text data as input and performs grammatical analysis and sentiment analysis using natural language processing libraries (e.g., spaCy, NLTK). This deepens the understanding of the message's context and topic. The output is the analysis result.

[0331] Step 3:

[0332] The server performs translation and interpretation based on the analysis results, referencing a cultural background database. Using the analyzed data and cultural background information as input, it generates contextually appropriate translations using a generative AI model (e.g., GPT-3). The output is a culturally appropriate translation.

[0333] Step 4:

[0334] The server suggests communication styles to the user. Based on the user's message and the recipient's cultural background, it generates appropriate communication methods and conversation topics as input. The output is a summary of the suggested content.

[0335] Step 5:

[0336] The device presents the user with translation results and suggestions. As input, it displays the translation results and suggestions received from the server to the user, facilitating cross-cultural conversation. This presentation prepares the user for effective communication.

[0337] Step 6:

[0338] The user provides feedback. This feedback includes comments on the quality of the translation and the usefulness of the suggestions, and the device prepares to send this information to the server.

[0339] Step 7:

[0340] The server receives user feedback and uses it to improve the system. As input, it acquires user feedback, which is used to improve cultural background data and the accuracy of algorithms. As output, it develops plans for future system improvements.

[0341] 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.

[0342] This invention is an advanced system that supports intercultural communication. It analyzes text data entered by the user and provides translations and suggestions that take cultural backgrounds and emotions into consideration. By incorporating an emotion engine, this system can recognize the user's emotions and propose a communication style that takes them into account.

[0343] First, the terminal receives text data from the user and sends that data to the server. The server analyzes the received text using natural language processing technology to extract the context and sentiment of the message. The sentiment engine built into the server detects sentiment from the user's input text and calculates sentiment scores and categories.

[0344] The analyzed data is integrated with cultural background data as needed, and the server performs optimal translation and interpretation while considering the recipient's culture and the user's emotions. Using generative AI technology, it is possible to generate natural, contextually relevant translations and construct emotionally sensitive messages.

[0345] Furthermore, the server suggests communication styles to the user based on detected emotions. For example, if the user is feeling stressed, it can suggest calm and considerate language. This kind of advice can be applied in both business settings and personal interactions.

[0346] For example, if a user wants to send an emotionally charged message to an overseas business partner stating, "Today's meeting just didn't go well," this system recognizes the user's emotions and suggests a way to provide constructive feedback while maintaining composure. This approach helps avoid misunderstandings and mitigate emotional misinterpretations.

[0347] Finally, the translation results and suggested styles are sent to the terminal and shown to the user. The user then reviews and edits the message based on these suggestions and sends it as needed. In addition, the terminal receives user feedback on the system's processing and sends it to the server. This feedback helps improve the system's accuracy.

[0348] Overall, this system will be a powerful tool for users to communicate effectively across cultures.

[0349] The following describes the processing flow.

[0350] Step 1:

[0351] The user types a message into the device. This message contains what they want to convey to the recipient and their feelings at that time. The device sends the entered text data to the server.

[0352] Step 2:

[0353] The server analyzes the text data received from the terminal. Using natural language processing techniques, it extracts the grammatical structure and keywords of the message to understand its intent and theme.

[0354] Step 3:

[0355] The emotion engine on the server performs sentiment analysis on the text data. Through this analysis, it determines the type and intensity of the emotions the user is expressing and generates an emotion score.

[0356] Step 4:

[0357] The server uses the analyzed data to reference the cultural background data of the user and the recipient. This enables contextually appropriate translation or interpretation.

[0358] Step 5:

[0359] The server uses generative AI technology to create translations and interpretations that take cultural context and user emotions into consideration. These translations are then formatted to be natural and easily understood by the recipient.

[0360] Step 6:

[0361] The server utilizes the results of the emotion engine to suggest a communication style that suits the user. For example, when emotions are heightened, it recommends using calm and composed language.

[0362] Step 7:

[0363] The server sends the generated translation results and communication style suggestions to the terminal. The terminal displays this information to the user and allows them to confirm the message.

[0364] Step 8:

[0365] The user reviews the message based on the suggested translation and style, makes any necessary edits, and then sends it.

[0366] Step 9:

[0367] The terminal collects feedback from users about the system. This feedback is sent to the server and used to improve the system.

[0368] (Example 2)

[0369] 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".

[0370] Intercultural communication presents challenges due to the ease with which misunderstandings can arise from differences in cultural backgrounds and emotions. There is a need to reduce such misunderstandings and improve the ability to convey messages efficiently and accurately. Furthermore, there is a need to go beyond mere translation and propose communication styles that take emotions into consideration.

[0371] 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.

[0372] In this invention, the server includes means for receiving information input by a user, means for analyzing the received information using natural language processing to extract context and emotions, and means for detecting and quantifying emotions from the analyzed information. This enables effective communication across cultures.

[0373] "Information" refers to text data that users input into the system, as well as data related to the context, emotions, and cultural background of that text data.

[0374] "Natural language processing" refers to the technology that enables computers to understand, analyze, and generate human language, and is used to extract context and sentiment from text data.

[0375] "Emotion detection" refers to the process of identifying the type and intensity of emotions from input information and quantifying them as a specific score or category.

[0376] "Cultural background information" refers to data related to values, customs, and communication styles specific to a particular country, region, or group.

[0377] "Generative artificial intelligence technology" refers to technology that naturally generates translations and interpretations based on input data, supporting communication tailored to the user's needs.

[0378] "Communication style" refers to the way a message is expressed and its tone, and the style suggested to best convey the intended meaning to the recipient.

[0379] This invention is a system aimed at improving intercultural communication, which translates and interprets information based on user input, incorporating emotional analysis and cultural considerations. The system consists of a terminal, a server, and a generative AI model.

[0380] The terminal is responsible for receiving information from the user. This information is primarily text data and includes the user's emotions and intentions. This information is transmitted to the server using a secure communication protocol.

[0381] The server analyzes received information using natural language processing techniques. These techniques include morphological analysis, contextual understanding, and sentiment analysis, aiming to extract context and emotion from the information. Furthermore, the server incorporates an emotion engine that detects emotions from input information and quantifies them as scores or categories. This process is crucial for accurately understanding the intent of messages by quantifying the intensity of emotions.

[0382] The analyzed data is integrated with cultural background information. This is a crucial step to avoid misunderstandings with recipients from different cultures. Based on this analysis, the generative AI model generates natural and contextually appropriate translations and interpretations, constructing messages that are sensitive to emotions and culture. This goes beyond simple translation and enables information transmission optimized for the recipient's cultural context.

[0383] For example, if a user wants to send a reply to an overseas business partner that includes constructive feedback while avoiding negative feelings, this system can analyze the user's input text, "I want to convey my concerns about next week's meeting," and suggest appropriate and considerate phrasing. An example of a prompt sentence to input into the generating AI model would be, "Please suggest a reply in a business email that includes constructive feedback while avoiding negative feelings."

[0384] As described above, this system provides users with a powerful tool to support intercultural communication.

[0385] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0386] Step 1:

[0387] The terminal receives text data from the user as input. This input contains information including the message and intentions the user wants to send. The terminal applies security protocols such as encryption to securely transmit this text data to the server.

[0388] Step 2:

[0389] The server receives text data sent from the terminal. This input is analyzed by a natural language processing unit to extract context, keywords, and signs of sentiment. The output of the data analysis is contextual and sentimental information of the message, which is used as foundational data for subsequent processing.

[0390] Step 3:

[0391] The emotion engine installed on the server receives analyzed contextual information as input, detects and quantifies the emotions within the text. This process outputs emotion scores and categories, forming a basis for determining how positive or negative a message is.

[0392] Step 4:

[0393] The server uses the obtained analytical and sentiment data as input and references the recipient's cultural background database. It translates and interprets messages to avoid cross-cultural misunderstandings. The output of this step is a culturally adapted, contextual, and sentiment-sensitive translation.

[0394] Step 5:

[0395] The generative AI model on the server uses the output of the translation process to construct the text. This process performs translation or interpretation in a natural way that aligns with the user's intent. The final output of this step is a natural message that is relevant to the transformed context.

[0396] Step 6:

[0397] The server, along with the generated message, suggests an appropriate communication style to the user. For example, the suggestion may include constructive language to avoid emotional misunderstandings. This suggestion is sent to the terminal as the final output.

[0398] Step 7:

[0399] The terminal displays the user the translation results and communication style suggestions sent from the server. The user reviews the message based on this output and edits it as needed. As a result of this process, the user is ready to create and send the final message.

[0400] Step 8:

[0401] The terminal collects user editing actions and feedback and sends them to the server. This feedback helps improve the system and increase its accuracy, and the accumulation of appropriate responses leads to better processing in the future.

[0402] (Application Example 2)

[0403] 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."

[0404] In modern society, intercultural communication can lead to misunderstandings and problems not only due to language differences but also to differences in cultural backgrounds and emotions. Such misunderstandings can create friction between individuals and organizations, hindering smooth communication. In particular, multinational environments demand rapid and appropriate communication, and conventional technologies offer limited means to adequately support this.

[0405] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0406] In this invention, the server includes means for detecting the user's emotional state and generating communication content based on the detection results, means for suggesting an appropriate communication style to the user, and means for collecting evaluation information from the user and using it to improve the system. This makes it possible for users to achieve appropriate communication that takes into account their emotions and culture, and to reduce misunderstandings between cultures.

[0407] A "user" is an individual or organization that provides input data using an information system.

[0408] "Information data" refers to text and other forms of data entered by users that are processed by the system.

[0409] "Means of receiving" refers to a device or program that has the function of acquiring information data provided by the user.

[0410] "Language processing" refers to the techniques used to analyze natural language and understand its meaning and context.

[0411] "Means of analysis" refers to a device or program that performs language processing on information data and has the function of extracting necessary information.

[0412] "Cultural background information" refers to information that includes customs, values, and linguistic characteristics associated with a particular society or group.

[0413] "Means for translation or interpretation" refers to a device or program that has the function of transforming analyzed information data to suit another language or context.

[0414] A "communication style" is a method of selecting language and expressions to suit a specific context or purpose.

[0415] "Means of suggestion" refers to a device or program that has the function of presenting appropriate actions or options to the user.

[0416] "Means for detecting emotional states" refers to a device or program that analyzes emotions from user input data and identifies a specific emotional state.

[0417] "Evaluation information" refers to data on evaluations and feedback that users provide regarding the services offered by the system.

[0418] An "information storage device" is a device for storing information data and background information, and it is intended to make this information accessible to the system.

[0419] "Computational intelligence technology" refers to technologies that use artificial intelligence to perform specific computational processes and make decisions.

[0420] The system realizing this invention includes a server that starts operating upon user input and has the function of precisely analyzing information. Specifically, the user inputs information data (text) using a terminal and sends that information data to the server. The server analyzes the information data using a language processing program (e.g., TextBlob library) and extracts context and sentiment. Furthermore, based on the analyzed data, it refers to cultural background information and utilizes computational intelligence technology (e.g., OpenAI API) to generate an appropriate translation or interpretation.

[0421] The server also has the ability to detect the user's emotional state and suggest an appropriate communication style based on that state. These suggestions are an important element in enabling users to communicate smoothly with people from different cultural backgrounds. By providing emotionally-based suggestions, it is possible to avoid misunderstandings and promote effective communication.

[0422] Furthermore, the server collects user feedback and uses this to improve the system's accuracy and effectiveness. For example, if a traveler wants to discuss an inappropriate order at a restaurant, the server will suggest a translation that soothes the user's feelings, generating a prompt such as, "Please translate 'The order was wrong' into Italian in a gentle and calm manner."

[0423] This system enables users to engage in sophisticated communication that takes culture and emotions into account in their daily lives and business environments.

[0424] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0425] Step 1:

[0426] The user inputs information data (input text) through a terminal. This input includes the user's emotions and messages. The input data is sent from the terminal to the server. Here, input involves manual user interaction, while output is raw information data received on the server side.

[0427] Step 2:

[0428] The server analyzes the received information data using a language processing program. Specifically, it uses the TextBlob library to extract context and sentiment from the information data. The input for this step is the received information data, and the output is the analyzed context information and sentiment score.

[0429] Step 3:

[0430] The server creates a translation or interpretation based on the analyzed information and references cultural background information. This process utilizes the OpenAI API as a computational intelligence technology to generate a translation that takes into account the user's emotions and the culture of the recipient. The input is the contextual information and emotion score obtained in the previous step, and the output is the proposed translation.

[0431] Step 4:

[0432] The server provides the user with a translation and suggests an appropriate communication style. This style suggestion utilizes a generative AI model to create prompts. The input is the translation, and the output is a specific recommendation of a communication style based on the translation.

[0433] Step 5:

[0434] The user reviews the translation and style suggestions provided by the server on their terminal. The user modifies the suggestions as needed and sends the final message. In this step, the input is the server's suggestions, and the output is the user's edited final message.

[0435] Step 6:

[0436] The terminal collects user feedback and sends it to the server to help improve the system. The server uses the feedback to improve the accuracy of prompt messages, update cultural background information, and so on. The input to this feedback cycle is user evaluation information, and the output is improved system performance.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] [Third Embodiment]

[0441] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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".

[0453] This invention is an advanced system for supporting intercultural communication, which handles everything from receiving and analyzing text data to translation, suggestions, and feedback collection. The processing of this system's program is described below in natural language.

[0454] The terminal retrieves text data entered by the user. This text contains a message that the user is conveying to someone from a different culture. The user's input is quickly sent to the server, and the server begins processing it.

[0455] The server first analyzes the received text. This analysis utilizes natural language processing techniques, including understanding the text's grammatical structure, sentiment, and topic. Based on the analysis results, the server references the recipient's cultural background data to perform contextually appropriate translations and interpretations. Generative AI technology is used to provide natural and culture-appropriate translation results.

[0456] The server further suggests effective communication styles to the user, including greetings in a business setting and expressions adapted to the customs of the other party's country. This allows the user to communicate smoothly while avoiding cultural misunderstandings.

[0457] For example, when a Japanese user sends an email to an American partner, they may want to convey the nuance of "I want them to understand the situation subtly." The server translates this intention into something like "I would like to explain the situation specifically and request a clear response," recommending direct communication that aligns with American culture. In this process, the server automatically generates the most appropriate expression to accurately convey the user's intention.

[0458] Finally, the terminal receives feedback from users regarding the system's translation accuracy and the usefulness of its suggestions. This feedback is sent to the server and used to improve the system. Based on user feedback, the system enhances the accuracy of its cultural background database and natural language processing algorithms, which helps support future communications.

[0459] In this way, the system of the present invention can significantly reduce misunderstandings between cultures and enable smooth and effective communication.

[0460] The following describes the processing flow.

[0461] Step 1:

[0462] The user uses their device to type a text message they want to send to someone from a different culture. The device receives this text data and, once ready, sends it to the server.

[0463] Step 2:

[0464] The server analyzes the text data received from the terminal. Using natural language processing techniques, it analyzes the grammatical structure, keywords, and intent of the text to understand the meaning of the message.

[0465] Step 3:

[0466] Based on the analysis results, the server consults a cultural background database. It retrieves cultural background information for both the user and the recipient, and generates appropriate translations and interpretations that are suitable for the context of the message.

[0467] Step 4:

[0468] By utilizing generative AI technology, the server creates natural-sounding translations or interpretations that are appropriate to the context. This process derives expressions that are relevant to the target culture.

[0469] Step 5:

[0470] The server offers communication style suggestions to the user. For example, it provides advice on how to greet someone and what expressions are appropriate to use in messages.

[0471] Step 6:

[0472] The server sends the generated translation results and communication style suggestions to the terminal. The terminal displays this to the user and prompts them to review and edit the message.

[0473] Step 7:

[0474] The user reviews the translation and edits the message as needed. After deciding on the final message, it is sent from the device to the recipient.

[0475] Step 8:

[0476] The terminal collects user feedback regarding system usage. This feedback is sent to the server and used for future improvements.

[0477] (Example 1)

[0478] 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."

[0479] Intercultural communication often leads to misunderstandings and friction due to differences in language and culture, making smooth and accurate information transmission difficult. This invention aims to overcome such challenges in intercultural communication and achieve better mutual understanding and information transmission.

[0480] 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.

[0481] In this invention, the server includes means for receiving information entered by a user, means for processing the received information by language analysis and extracting the context of the message, and means for translating or interpreting the information based on the analyzed information and referring to the cultural background of the recipient. This enables effective and accurate information transmission between different cultures.

[0482] A "user" is an individual or organization that uses the system to create or receive cross-cultural information.

[0483] "Information" refers to text data and other digital content that users input or submit.

[0484] "Means" refers to a device or method for performing a specific function.

[0485] A "server" is a central computer system that performs information analysis and processing.

[0486] "Linguistic analysis" is the process of analyzing information using natural language processing techniques to extract context and emotions.

[0487] "Cultural background" refers to insights into the recipient's culture that are taken into consideration to improve the accuracy of information translation and interpretation.

[0488] "Translation or interpretation" is the act of converting information into a format that the recipient can understand in order to facilitate communication between different cultures.

[0489] A "data structure" is an organized digital format for efficiently storing and managing information.

[0490] "Generative AI technology" refers to technology that uses artificial intelligence to automatically generate and process information.

[0491] This invention is an advanced system that supports intercultural communication, handling everything from information reception and analysis to translation, proposal, and feedback collection in a consistent manner.

[0492] The terminal first receives information entered by the user. The user enters the message using a text box or voice input. For example, when a user enters a business email, they use an application on their smartphone or computer. This information is sent to the server via the network.

[0493] The server processes the received information in detail through language analysis. Specifically, it uses natural language processing techniques to extract the grammatical structure, sentiment, and topic of the information. The server utilizes OpenAI's generative AI models and similar technologies to improve the accuracy of the analysis. An example of a prompt can be used: "Analyze the sentiment and topic of this message."

[0494] Subsequently, the server performs an appropriate translation or interpretation based on the analysis results, taking into account the cultural background of the recipient. General translation services provided via the API can be used for translation, generating expressions that accurately convey the user's intent.

[0495] Furthermore, the server will suggest the optimal communication method to the user. For example, it will show the format of business letters in different cultures and specific greeting phrases. In this case as well, it will use generative AI technology to suggest the best style. For example, a prompt such as "Suggest an email style suitable for American business" might be used.

[0496] Finally, the terminal uses the system's feedback function to collect user responses regarding translation accuracy and the usefulness of suggestions. Users can easily submit their opinions through a feedback form. This feedback information is sent to the server and used to improve the system in the future.

[0497] By implementing this system, barriers to intercultural communication can be effectively reduced, enabling smooth and accurate information transfer.

[0498] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0499] Step 1:

[0500] The device receives information entered by the user. This information is typically text messages intended for transmission across different cultures. For example, it often includes the content of business emails. This information is temporarily stored on the device.

[0501] Step 2:

[0502] The terminal sends the received information to the server. The data is typically transmitted using a secure communication protocol. Specifically, HTTPS is used to encrypt the information and transmit it quickly to the server.

[0503] Step 3:

[0504] The server analyzes the received information. Using text data as input, a language processing engine analyzes grammatical structure and sentiment. A generative AI model is utilized in this analysis. The prompt used is "Analyze the subject and sentiment of this message." As a result, the server grasps the context and outputs the analysis results.

[0505] Step 4:

[0506] The server translates or interprets the information based on the analysis results. In doing so, it refers to cultural background data to set appropriate expressions. Analysis data and cultural background information are used as input, and translated text is generated as output. A common translation API service is used for translation.

[0507] Step 5:

[0508] The server proposes methods for communicating with the user. It provides specific examples and gives prompts to the generating AI, such as "Please tell me an appropriate email greeting for American business." The generating AI model is used as input, and a proposal document is created as output.

[0509] Step 6:

[0510] The terminal displays the translated text and proposal sent back from the server to the user. The user can review the received information and edit the message as needed.

[0511] Step 7:

[0512] The device accepts user feedback. Users fill out a displayed form with their opinions on translation accuracy and suggestions, and then submit it. The feedback is forwarded directly to the server and used as data to improve the service.

[0513] (Application Example 1)

[0514] 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."

[0515] In today's globalized society, communication with people from diverse cultural backgrounds is crucial, but cultural misunderstandings and inappropriate expressions often arise. Traditional translation systems struggle to capture cultural nuances and contexts, resulting in a decline in the quality of communication. Furthermore, effective means of facilitating real-time intercultural exchange are lacking. To improve this situation, a system is needed that deepens cultural understanding and enables smooth and effective communication.

[0516] 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.

[0517] In this invention, the server includes means for receiving text data entered by a user, means for analyzing the received text data using natural language processing and extracting the context of the message, means for translating or interpreting the text based on the analyzed data and referring to the recipient's cultural background data, means for suggesting an appropriate communication style to the user and recommending conversation topics to promote cross-cultural online communication, and means for collecting user feedback and using it to improve the system. This significantly reduces misunderstandings between cultures and enables real-time and effective communication.

[0518] A "user" refers to an individual or group that uses a system to facilitate intercultural communication.

[0519] "Text data" refers to written information that users input to engage in cross-cultural communication.

[0520] "Natural language processing" refers to computer techniques used to analyze the structure and meaning of text data.

[0521] "Message context" refers to information that includes meaning and relationships within the text data.

[0522] "Cultural background data" refers to information that includes customs and values ​​related to intercultural communication.

[0523] "Translation or interpretation" refers to the act of transforming the content of text data into a culturally appropriate form.

[0524] "Communication style" refers to the methods of expression and attitudes used to smoothly transmit information across different cultures.

[0525] "Exchange topics" refer to themes or topics offered to facilitate intercultural conversation and discussion.

[0526] "Feedback" refers to users' opinions and evaluations of system suggestions and translations.

[0527] "System improvement" refers to the process of improving the overall performance and accuracy of a system based on user feedback.

[0528] In order to implement this invention, it is necessary to build an advanced system that supports intercultural communication. This system will be implemented as follows.

[0529] The server receives text data from users via the internet. This text data contains messages that users want to convey to people from different cultures. Next, the server analyzes this text data using natural language processing techniques. Specifically, it performs grammatical structure analysis and sentiment analysis using Python libraries such as spaCy and NLTK.

[0530] Based on the analyzed data, the server refers to a cultural background database to perform translations and interpretations appropriate to the recipient's culture. Generative AI technology used includes, for example, OpenAI's GPT-3 model. Prompts are given to this model to generate natural expressions that take cultural nuances into account.

[0531] Furthermore, the server suggests effective communication styles to users. One specific application is the smartphone application "Culture Cafe," which provides users with appropriate topics and question formats for intercultural exchange.

[0532] Users receive translation results and communication style suggestions from the system, allowing them to proceed with conversations with people from different cultures based on these. For example, when a Japanese user talks to a Brazilian user about the topic of "the four seasons of Japan," the system suggests appropriate translations along with questions such as, "Which season is the Brazilian user most interested in?"

[0533] Furthermore, this system accepts user feedback and uses it to improve the system. This feedback is aggregated on the server and contributes to improving translation accuracy and the quality of recommendation features in future conversations.

[0534] As an example of a prompt sentence, the system uses a method where the AI ​​is input in the format "I want to discuss Japan's seasonal customs with my Brazilian friend," and then generates an appropriate translation and a conversation example that is relevant to the cultural context. In this way, a system that supports smooth and effective intercultural communication is realized.

[0535] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0536] Step 1:

[0537] The terminal receives input from the user. It receives text data as input and prepares to send that data to a server over the internet. This text data contains a message shared across different cultures.

[0538] Step 2:

[0539] The server analyzes the text data it receives. It takes text data as input and performs grammatical analysis and sentiment analysis using natural language processing libraries (e.g., spaCy, NLTK). This deepens the understanding of the message's context and topic. The output is the analysis result.

[0540] Step 3:

[0541] The server performs translation and interpretation based on the analysis results, referencing a cultural background database. Using the analyzed data and cultural background information as input, it generates contextually appropriate translations using a generative AI model (e.g., GPT-3). The output is a culturally appropriate translation.

[0542] Step 4:

[0543] The server suggests communication styles to the user. Based on the user's message and the recipient's cultural background, it generates appropriate communication methods and conversation topics as input. The output is a summary of the suggested content.

[0544] Step 5:

[0545] The device presents the user with translation results and suggestions. As input, it displays the translation results and suggestions received from the server to the user, facilitating cross-cultural conversation. This presentation prepares the user for effective communication.

[0546] Step 6:

[0547] The user provides feedback. This feedback includes comments on the quality of the translation and the usefulness of the suggestions, and the device prepares to send this information to the server.

[0548] Step 7:

[0549] The server receives user feedback and uses it to improve the system. As input, it acquires user feedback, which is used to improve cultural background data and the accuracy of algorithms. As output, it develops plans for future system improvements.

[0550] 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.

[0551] This invention is an advanced system that supports intercultural communication. It analyzes text data entered by the user and provides translations and suggestions that take cultural backgrounds and emotions into consideration. By incorporating an emotion engine, this system can recognize the user's emotions and propose a communication style that takes them into account.

[0552] First, the terminal receives text data from the user and sends that data to the server. The server analyzes the received text using natural language processing technology to extract the context and sentiment of the message. The sentiment engine built into the server detects sentiment from the user's input text and calculates sentiment scores and categories.

[0553] The analyzed data is integrated with cultural background data as needed, and the server performs optimal translation and interpretation while considering the recipient's culture and the user's emotions. Using generative AI technology, it is possible to generate natural, contextually relevant translations and construct emotionally sensitive messages.

[0554] Furthermore, the server suggests communication styles to the user based on detected emotions. For example, if the user is feeling stressed, it can suggest calm and considerate language. This kind of advice can be applied in both business settings and personal interactions.

[0555] For example, if a user wants to send an emotionally charged message to an overseas business partner stating, "Today's meeting just didn't go well," this system recognizes the user's emotions and suggests a way to provide constructive feedback while maintaining composure. This approach helps avoid misunderstandings and mitigate emotional misinterpretations.

[0556] Finally, the translation results and suggested styles are sent to the terminal and shown to the user. The user then reviews and edits the message based on these suggestions and sends it as needed. In addition, the terminal receives user feedback on the system's processing and sends it to the server. This feedback helps improve the system's accuracy.

[0557] Overall, this system will be a powerful tool for users to communicate effectively across cultures.

[0558] The following describes the processing flow.

[0559] Step 1:

[0560] The user types a message into the device. This message contains what they want to convey to the recipient and their feelings at that time. The device sends the entered text data to the server.

[0561] Step 2:

[0562] The server analyzes the text data received from the terminal. Using natural language processing techniques, it extracts the grammatical structure and keywords of the message to understand its intent and theme.

[0563] Step 3:

[0564] The emotion engine on the server performs sentiment analysis on the text data. Through this analysis, it determines the type and intensity of the emotions the user is expressing and generates an emotion score.

[0565] Step 4:

[0566] The server uses the analyzed data to reference the cultural background data of the user and the recipient. This enables contextually appropriate translation or interpretation.

[0567] Step 5:

[0568] The server uses generative AI technology to create translations and interpretations that take cultural context and user emotions into consideration. These translations are then formatted to be natural and easily understood by the recipient.

[0569] Step 6:

[0570] The server utilizes the results of the emotion engine to suggest a communication style that suits the user. For example, when emotions are heightened, it recommends using calm and composed language.

[0571] Step 7:

[0572] The server sends the generated translation results and communication style suggestions to the terminal. The terminal displays this information to the user and allows them to confirm the message.

[0573] Step 8:

[0574] The user reviews the message based on the suggested translation and style, makes any necessary edits, and then sends it.

[0575] Step 9:

[0576] The terminal collects feedback from users about the system. This feedback is sent to the server and used to improve the system.

[0577] (Example 2)

[0578] 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."

[0579] Intercultural communication presents challenges due to the ease with which misunderstandings can arise from differences in cultural backgrounds and emotions. There is a need to reduce such misunderstandings and improve the ability to convey messages efficiently and accurately. Furthermore, there is a need to go beyond mere translation and propose communication styles that take emotions into consideration.

[0580] 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.

[0581] In this invention, the server includes means for receiving information input by a user, means for analyzing the received information using natural language processing to extract context and emotions, and means for detecting and quantifying emotions from the analyzed information. This enables effective communication across cultures.

[0582] "Information" refers to text data that users input into the system, as well as data related to the context, emotions, and cultural background of that text data.

[0583] "Natural language processing" refers to the technology that enables computers to understand, analyze, and generate human language, and is used to extract context and sentiment from text data.

[0584] "Emotion detection" refers to the process of identifying the type and intensity of emotions from input information and quantifying them as a specific score or category.

[0585] "Cultural background information" refers to data related to values, customs, and communication styles specific to a particular country, region, or group.

[0586] "Generative artificial intelligence technology" refers to technology that naturally generates translations and interpretations based on input data, supporting communication tailored to the user's needs.

[0587] "Communication style" refers to the way a message is expressed and its tone, and the style suggested to best convey the intended meaning to the recipient.

[0588] This invention is a system aimed at improving intercultural communication, which translates and interprets information based on user input, incorporating emotional analysis and cultural considerations. The system consists of a terminal, a server, and a generative AI model.

[0589] The terminal is responsible for receiving information from the user. This information is primarily text data and includes the user's emotions and intentions. This information is transmitted to the server using a secure communication protocol.

[0590] The server analyzes received information using natural language processing techniques. These techniques include morphological analysis, contextual understanding, and sentiment analysis, aiming to extract context and emotion from the information. Furthermore, the server incorporates an emotion engine that detects emotions from input information and quantifies them as scores or categories. This process is crucial for accurately understanding the intent of messages by quantifying the intensity of emotions.

[0591] The analyzed data is integrated with cultural background information. This is a crucial step to avoid misunderstandings with recipients from different cultures. Based on this analysis, the generative AI model generates natural and contextually appropriate translations and interpretations, constructing messages that are sensitive to emotions and culture. This goes beyond simple translation and enables information transmission optimized for the recipient's cultural context.

[0592] For example, if a user wants to send a reply to an overseas business partner that includes constructive feedback while avoiding negative feelings, this system can analyze the user's input text, "I want to convey my concerns about next week's meeting," and suggest appropriate and considerate phrasing. An example of a prompt sentence to input into the generating AI model would be, "Please suggest a reply in a business email that includes constructive feedback while avoiding negative feelings."

[0593] As described above, this system provides users with a powerful tool to support intercultural communication.

[0594] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0595] Step 1:

[0596] The terminal receives text data from the user as input. This input contains information including the message and intentions the user wants to send. The terminal applies security protocols such as encryption to securely transmit this text data to the server.

[0597] Step 2:

[0598] The server receives text data sent from the terminal. This input is analyzed by a natural language processing unit to extract context, keywords, and signs of sentiment. The output of the data analysis is contextual and sentimental information of the message, which is used as foundational data for subsequent processing.

[0599] Step 3:

[0600] The emotion engine installed on the server receives analyzed contextual information as input, detects and quantifies the emotions within the text. This process outputs emotion scores and categories, forming a basis for determining how positive or negative a message is.

[0601] Step 4:

[0602] The server uses the obtained analytical and sentiment data as input and references the recipient's cultural background database. It translates and interprets messages to avoid cross-cultural misunderstandings. The output of this step is a culturally adapted, contextual, and sentiment-sensitive translation.

[0603] Step 5:

[0604] The generative AI model on the server uses the output of the translation process to construct the text. This process performs translation or interpretation in a natural way that aligns with the user's intent. The final output of this step is a natural message that is relevant to the transformed context.

[0605] Step 6:

[0606] The server, along with the generated message, suggests an appropriate communication style to the user. For example, the suggestion may include constructive language to avoid emotional misunderstandings. This suggestion is sent to the terminal as the final output.

[0607] Step 7:

[0608] The terminal displays the user the translation results and communication style suggestions sent from the server. The user reviews the message based on this output and edits it as needed. As a result of this process, the user is ready to create and send the final message.

[0609] Step 8:

[0610] The terminal collects user editing actions and feedback and sends them to the server. This feedback helps improve the system and increase its accuracy, and the accumulation of appropriate responses leads to better processing in the future.

[0611] (Application Example 2)

[0612] 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."

[0613] In modern society, intercultural communication can lead to misunderstandings and problems not only due to language differences but also to differences in cultural backgrounds and emotions. Such misunderstandings can create friction between individuals and organizations, hindering smooth communication. In particular, multinational environments demand rapid and appropriate communication, and conventional technologies offer limited means to adequately support this.

[0614] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0615] In this invention, the server includes means for detecting the user's emotional state and generating communication content based on the detection results, means for suggesting an appropriate communication style to the user, and means for collecting evaluation information from the user and using it to improve the system. This makes it possible for users to achieve appropriate communication that takes into account their emotions and culture, and to reduce misunderstandings between cultures.

[0616] A "user" is an individual or organization that provides input data using an information system.

[0617] "Information data" refers to text and other forms of data entered by users that are processed by the system.

[0618] "Means of receiving" refers to a device or program that has the function of acquiring information data provided by the user.

[0619] "Language processing" refers to the techniques used to analyze natural language and understand its meaning and context.

[0620] "Means of analysis" refers to a device or program that performs language processing on information data and has the function of extracting necessary information.

[0621] "Cultural background information" refers to information that includes customs, values, and linguistic characteristics associated with a particular society or group.

[0622] "Means for translation or interpretation" refers to a device or program that has the function of transforming analyzed information data to suit another language or context.

[0623] A "communication style" is a method of selecting language and expressions to suit a specific context or purpose.

[0624] "Means of suggestion" refers to a device or program that has the function of presenting appropriate actions or options to the user.

[0625] "Means for detecting emotional states" refers to a device or program that analyzes emotions from user input data and identifies a specific emotional state.

[0626] "Evaluation information" refers to data on evaluations and feedback that users provide regarding the services offered by the system.

[0627] An "information storage device" is a device for storing information data and background information, and it is intended to make this information accessible to the system.

[0628] "Computational intelligence technology" refers to technologies that use artificial intelligence to perform specific computational processes and make decisions.

[0629] The system realizing this invention includes a server that starts operating upon user input and has the function of precisely analyzing information. Specifically, the user inputs information data (text) using a terminal and sends that information data to the server. The server analyzes the information data using a language processing program (e.g., TextBlob library) and extracts context and sentiment. Furthermore, based on the analyzed data, it refers to cultural background information and utilizes computational intelligence technology (e.g., OpenAI API) to generate an appropriate translation or interpretation.

[0630] The server also has the ability to detect the user's emotional state and suggest an appropriate communication style based on that state. These suggestions are an important element in enabling users to communicate smoothly with people from different cultural backgrounds. By providing emotionally-based suggestions, it is possible to avoid misunderstandings and promote effective communication.

[0631] Furthermore, the server collects user feedback and uses this to improve the system's accuracy and effectiveness. For example, if a traveler wants to discuss an inappropriate order at a restaurant, the server will suggest a translation that soothes the user's feelings, generating a prompt such as, "Please translate 'The order was wrong' into Italian in a gentle and calm manner."

[0632] This system enables users to engage in sophisticated communication that takes culture and emotions into account in their daily lives and business environments.

[0633] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0634] Step 1:

[0635] The user inputs information data (input text) through a terminal. This input includes the user's emotions and messages. The input data is sent from the terminal to the server. Here, input involves manual user interaction, while output is raw information data received on the server side.

[0636] Step 2:

[0637] The server analyzes the received information data using a language processing program. Specifically, it uses the TextBlob library to extract context and sentiment from the information data. The input for this step is the received information data, and the output is the analyzed context information and sentiment score.

[0638] Step 3:

[0639] The server creates a translation or interpretation based on the analyzed information and references cultural background information. This process utilizes the OpenAI API as a computational intelligence technology to generate a translation that takes into account the user's emotions and the culture of the recipient. The input is the contextual information and emotion score obtained in the previous step, and the output is the proposed translation.

[0640] Step 4:

[0641] The server provides the user with a translation and suggests an appropriate communication style. This style suggestion utilizes a generative AI model to create prompts. The input is the translation, and the output is a specific recommendation of a communication style based on the translation.

[0642] Step 5:

[0643] The user reviews the translation and style suggestions provided by the server on their terminal. The user modifies the suggestions as needed and sends the final message. In this step, the input is the server's suggestions, and the output is the user's edited final message.

[0644] Step 6:

[0645] The terminal collects user feedback and sends it to the server to help improve the system. The server uses the feedback to improve the accuracy of prompt messages, update cultural background information, and so on. The input to this feedback cycle is user evaluation information, and the output is improved system performance.

[0646] 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.

[0647] 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.

[0648] 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.

[0649] [Fourth Embodiment]

[0650] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0651] 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.

[0652] 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).

[0653] 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.

[0654] 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.

[0655] 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).

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] 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.

[0662] 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".

[0663] This invention is an advanced system for supporting intercultural communication, which handles everything from receiving and analyzing text data to translation, suggestions, and feedback collection. The processing of this system's program is described below in natural language.

[0664] The terminal retrieves text data entered by the user. This text contains a message that the user is conveying to someone from a different culture. The user's input is quickly sent to the server, and the server begins processing it.

[0665] The server first analyzes the received text. This analysis utilizes natural language processing techniques, including understanding the text's grammatical structure, sentiment, and topic. Based on the analysis results, the server references the recipient's cultural background data to perform contextually appropriate translations and interpretations. Generative AI technology is used to provide natural and culture-appropriate translation results.

[0666] The server further suggests effective communication styles to the user, including greetings in a business setting and expressions adapted to the customs of the other party's country. This allows the user to communicate smoothly while avoiding cultural misunderstandings.

[0667] For example, when a Japanese user sends an email to an American partner, they may want to convey the nuance of "I want them to understand the situation subtly." The server translates this intention into something like "I would like to explain the situation specifically and request a clear response," recommending direct communication that aligns with American culture. In this process, the server automatically generates the most appropriate expression to accurately convey the user's intention.

[0668] Finally, the terminal receives feedback from users regarding the system's translation accuracy and the usefulness of its suggestions. This feedback is sent to the server and used to improve the system. Based on user feedback, the system enhances the accuracy of its cultural background database and natural language processing algorithms, which helps support future communications.

[0669] In this way, the system of the present invention can significantly reduce misunderstandings between cultures and enable smooth and effective communication.

[0670] The following describes the processing flow.

[0671] Step 1:

[0672] The user uses their device to type a text message they want to send to someone from a different culture. The device receives this text data and, once ready, sends it to the server.

[0673] Step 2:

[0674] The server analyzes the text data received from the terminal. Using natural language processing techniques, it analyzes the grammatical structure, keywords, and intent of the text to understand the meaning of the message.

[0675] Step 3:

[0676] Based on the analysis results, the server consults a cultural background database. It retrieves cultural background information for both the user and the recipient, and generates appropriate translations and interpretations that are suitable for the context of the message.

[0677] Step 4:

[0678] By utilizing generative AI technology, the server creates natural-sounding translations or interpretations that are appropriate to the context. This process derives expressions that are relevant to the target culture.

[0679] Step 5:

[0680] The server offers communication style suggestions to the user. For example, it provides advice on how to greet someone and what expressions are appropriate to use in messages.

[0681] Step 6:

[0682] The server sends the generated translation results and communication style suggestions to the terminal. The terminal displays this to the user and prompts them to review and edit the message.

[0683] Step 7:

[0684] The user reviews the translation and edits the message as needed. After deciding on the final message, it is sent from the device to the recipient.

[0685] Step 8:

[0686] The terminal collects user feedback regarding system usage. This feedback is sent to the server and used for future improvements.

[0687] (Example 1)

[0688] 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".

[0689] Intercultural communication often leads to misunderstandings and friction due to differences in language and culture, making smooth and accurate information transmission difficult. This invention aims to overcome such challenges in intercultural communication and achieve better mutual understanding and information transmission.

[0690] 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.

[0691] In this invention, the server includes means for receiving information entered by a user, means for processing the received information by language analysis and extracting the context of the message, and means for translating or interpreting the information based on the analyzed information and referring to the cultural background of the recipient. This enables effective and accurate information transmission between different cultures.

[0692] A "user" is an individual or organization that uses the system to create or receive cross-cultural information.

[0693] "Information" refers to text data and other digital content that users input or submit.

[0694] "Means" refers to a device or method for performing a specific function.

[0695] A "server" is a central computer system that performs information analysis and processing.

[0696] "Linguistic analysis" is the process of analyzing information using natural language processing techniques to extract context and emotions.

[0697] "Cultural background" refers to insights into the recipient's culture that are taken into consideration to improve the accuracy of information translation and interpretation.

[0698] "Translation or interpretation" is the act of converting information into a format that the recipient can understand in order to facilitate communication between different cultures.

[0699] A "data structure" is an organized digital format for efficiently storing and managing information.

[0700] "Generative AI technology" refers to technology that uses artificial intelligence to automatically generate and process information.

[0701] This invention is an advanced system that supports intercultural communication, handling everything from information reception and analysis to translation, proposal, and feedback collection in a consistent manner.

[0702] The terminal first receives information entered by the user. The user enters the message using a text box or voice input. For example, when a user enters a business email, they use an application on their smartphone or computer. This information is sent to the server via the network.

[0703] The server processes the received information in detail through language analysis. Specifically, it uses natural language processing techniques to extract the grammatical structure, sentiment, and topic of the information. The server utilizes OpenAI's generative AI models and similar technologies to improve the accuracy of the analysis. An example of a prompt can be used: "Analyze the sentiment and topic of this message."

[0704] Subsequently, the server performs an appropriate translation or interpretation based on the analysis results, taking into account the cultural background of the recipient. General translation services provided via the API can be used for translation, generating expressions that accurately convey the user's intent.

[0705] Furthermore, the server will suggest the optimal communication method to the user. For example, it will show the format of business letters in different cultures and specific greeting phrases. In this case as well, it will use generative AI technology to suggest the best style. For example, a prompt such as "Suggest an email style suitable for American business" might be used.

[0706] Finally, the terminal uses the system's feedback function to collect user responses regarding translation accuracy and the usefulness of suggestions. Users can easily submit their opinions through a feedback form. This feedback information is sent to the server and used to improve the system in the future.

[0707] By implementing this system, barriers to intercultural communication can be effectively reduced, enabling smooth and accurate information transfer.

[0708] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0709] Step 1:

[0710] The device receives information entered by the user. This information is typically text messages intended for transmission across different cultures. For example, it often includes the content of business emails. This information is temporarily stored on the device.

[0711] Step 2:

[0712] The terminal sends the received information to the server. The data is typically transmitted using a secure communication protocol. Specifically, HTTPS is used to encrypt the information and transmit it quickly to the server.

[0713] Step 3:

[0714] The server analyzes the received information. Using text data as input, a language processing engine analyzes grammatical structure and sentiment. A generative AI model is utilized in this analysis. The prompt used is "Analyze the subject and sentiment of this message." As a result, the server grasps the context and outputs the analysis results.

[0715] Step 4:

[0716] The server translates or interprets the information based on the analysis results. In doing so, it refers to cultural background data to set appropriate expressions. Analysis data and cultural background information are used as input, and translated text is generated as output. A common translation API service is used for translation.

[0717] Step 5:

[0718] The server proposes methods for communicating with the user. It provides specific examples and gives prompts to the generating AI, such as "Please tell me an appropriate email greeting for American business." The generating AI model is used as input, and a proposal document is created as output.

[0719] Step 6:

[0720] The terminal displays the translated text and proposal sent back from the server to the user. The user can review the received information and edit the message as needed.

[0721] Step 7:

[0722] The device accepts user feedback. Users fill out a displayed form with their opinions on translation accuracy and suggestions, and then submit it. The feedback is forwarded directly to the server and used as data to improve the service.

[0723] (Application Example 1)

[0724] 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".

[0725] In today's globalized society, communication with people from diverse cultural backgrounds is crucial, but cultural misunderstandings and inappropriate expressions often arise. Traditional translation systems struggle to capture cultural nuances and contexts, resulting in a decline in the quality of communication. Furthermore, effective means of facilitating real-time intercultural exchange are lacking. To improve this situation, a system is needed that deepens cultural understanding and enables smooth and effective communication.

[0726] 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.

[0727] In this invention, the server includes means for receiving text data entered by a user, means for analyzing the received text data using natural language processing and extracting the context of the message, means for translating or interpreting the text based on the analyzed data and referring to the recipient's cultural background data, means for suggesting an appropriate communication style to the user and recommending conversation topics to promote cross-cultural online communication, and means for collecting user feedback and using it to improve the system. This significantly reduces misunderstandings between cultures and enables real-time and effective communication.

[0728] A "user" refers to an individual or group that uses a system to facilitate intercultural communication.

[0729] "Text data" refers to written information that users input to engage in cross-cultural communication.

[0730] "Natural language processing" refers to computer techniques used to analyze the structure and meaning of text data.

[0731] "Message context" refers to information that includes meaning and relationships within the text data.

[0732] "Cultural background data" refers to information that includes customs and values ​​related to intercultural communication.

[0733] "Translation or interpretation" refers to the act of transforming the content of text data into a culturally appropriate form.

[0734] "Communication style" refers to the methods of expression and attitudes used to smoothly transmit information across different cultures.

[0735] "Exchange topics" refer to themes or topics offered to facilitate intercultural conversation and discussion.

[0736] "Feedback" refers to users' opinions and evaluations of system suggestions and translations.

[0737] "System improvement" refers to the process of improving the overall performance and accuracy of a system based on user feedback.

[0738] In order to implement this invention, it is necessary to build an advanced system that supports intercultural communication. This system will be implemented as follows.

[0739] The server receives text data from users via the internet. This text data contains messages that users want to convey to people from different cultures. Next, the server analyzes this text data using natural language processing techniques. Specifically, it performs grammatical structure analysis and sentiment analysis using Python libraries such as spaCy and NLTK.

[0740] Based on the analyzed data, the server refers to a cultural background database to perform translations and interpretations appropriate to the recipient's culture. Generative AI technology used includes, for example, OpenAI's GPT-3 model. Prompts are given to this model to generate natural expressions that take cultural nuances into account.

[0741] Furthermore, the server suggests effective communication styles to users. One specific application is the smartphone application "Culture Cafe," which provides users with appropriate topics and question formats for intercultural exchange.

[0742] Users receive translation results and communication style suggestions from the system, allowing them to proceed with conversations with people from different cultures based on these. For example, when a Japanese user talks to a Brazilian user about the topic of "the four seasons of Japan," the system suggests appropriate translations along with questions such as, "Which season is the Brazilian user most interested in?"

[0743] Furthermore, this system accepts user feedback and uses it to improve the system. This feedback is aggregated on the server and contributes to improving translation accuracy and the quality of recommendation features in future conversations.

[0744] As an example of a prompt sentence, the system uses a method where the AI ​​is input in the format "I want to discuss Japan's seasonal customs with my Brazilian friend," and then generates an appropriate translation and a conversation example that is relevant to the cultural context. In this way, a system that supports smooth and effective intercultural communication is realized.

[0745] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0746] Step 1:

[0747] The terminal receives input from the user. It receives text data as input and prepares to send that data to a server over the internet. This text data contains a message shared across different cultures.

[0748] Step 2:

[0749] The server analyzes the text data it receives. It takes text data as input and performs grammatical analysis and sentiment analysis using natural language processing libraries (e.g., spaCy, NLTK). This deepens the understanding of the message's context and topic. The output is the analysis result.

[0750] Step 3:

[0751] The server performs translation and interpretation based on the analysis results, referencing a cultural background database. Using the analyzed data and cultural background information as input, it generates contextually appropriate translations using a generative AI model (e.g., GPT-3). The output is a culturally appropriate translation.

[0752] Step 4:

[0753] The server suggests communication styles to the user. Based on the user's message and the recipient's cultural background, it generates appropriate communication methods and conversation topics as input. The output is a summary of the suggested content.

[0754] Step 5:

[0755] The device presents the user with translation results and suggestions. As input, it displays the translation results and suggestions received from the server to the user, facilitating cross-cultural conversation. This presentation prepares the user for effective communication.

[0756] Step 6:

[0757] The user provides feedback. This feedback includes comments on the quality of the translation and the usefulness of the suggestions, and the device prepares to send this information to the server.

[0758] Step 7:

[0759] The server receives user feedback and uses it to improve the system. As input, it acquires user feedback, which is used to improve cultural background data and the accuracy of algorithms. As output, it develops plans for future system improvements.

[0760] 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.

[0761] This invention is an advanced system that supports intercultural communication. It analyzes text data entered by the user and provides translations and suggestions that take cultural backgrounds and emotions into consideration. By incorporating an emotion engine, this system can recognize the user's emotions and propose a communication style that takes them into account.

[0762] First, the terminal receives text data from the user and sends that data to the server. The server analyzes the received text using natural language processing technology to extract the context and sentiment of the message. The sentiment engine built into the server detects sentiment from the user's input text and calculates sentiment scores and categories.

[0763] The analyzed data is integrated with cultural background data as needed, and the server performs optimal translation and interpretation while considering the recipient's culture and the user's emotions. Using generative AI technology, it is possible to generate natural, contextually relevant translations and construct emotionally sensitive messages.

[0764] Furthermore, the server suggests communication styles to the user based on detected emotions. For example, if the user is feeling stressed, it can suggest calm and considerate language. This kind of advice can be applied in both business settings and personal interactions.

[0765] For example, if a user wants to send an emotionally charged message to an overseas business partner stating, "Today's meeting just didn't go well," this system recognizes the user's emotions and suggests a way to provide constructive feedback while maintaining composure. This approach helps avoid misunderstandings and mitigate emotional misinterpretations.

[0766] Finally, the translation results and suggested styles are sent to the terminal and shown to the user. The user then reviews and edits the message based on these suggestions and sends it as needed. In addition, the terminal receives user feedback on the system's processing and sends it to the server. This feedback helps improve the system's accuracy.

[0767] Overall, this system will be a powerful tool for users to communicate effectively across cultures.

[0768] The following describes the processing flow.

[0769] Step 1:

[0770] The user types a message into the device. This message contains what they want to convey to the recipient and their feelings at that time. The device sends the entered text data to the server.

[0771] Step 2:

[0772] The server analyzes the text data received from the terminal. Using natural language processing techniques, it extracts the grammatical structure and keywords of the message to understand its intent and theme.

[0773] Step 3:

[0774] The emotion engine on the server performs sentiment analysis on the text data. Through this analysis, it determines the type and intensity of the emotions the user is expressing and generates an emotion score.

[0775] Step 4:

[0776] The server uses the analyzed data to reference the cultural background data of the user and the recipient. This enables contextually appropriate translation or interpretation.

[0777] Step 5:

[0778] The server uses generative AI technology to create translations and interpretations that take cultural context and user emotions into consideration. These translations are then formatted to be natural and easily understood by the recipient.

[0779] Step 6:

[0780] The server utilizes the results of the emotion engine to suggest a communication style that suits the user. For example, when emotions are heightened, it recommends using calm and composed language.

[0781] Step 7:

[0782] The server sends the generated translation results and communication style suggestions to the terminal. The terminal displays this information to the user and allows them to confirm the message.

[0783] Step 8:

[0784] The user reviews the message based on the suggested translation and style, makes any necessary edits, and then sends it.

[0785] Step 9:

[0786] The terminal collects feedback from users about the system. This feedback is sent to the server and used to improve the system.

[0787] (Example 2)

[0788] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0789] Intercultural communication presents challenges due to the ease with which misunderstandings can arise from differences in cultural backgrounds and emotions. There is a need to reduce such misunderstandings and improve the ability to convey messages efficiently and accurately. Furthermore, there is a need to go beyond mere translation and propose communication styles that take emotions into consideration.

[0790] 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.

[0791] In this invention, the server includes means for receiving information input by a user, means for analyzing the received information using natural language processing to extract context and emotions, and means for detecting and quantifying emotions from the analyzed information. This enables effective communication across cultures.

[0792] "Information" refers to text data that users input into the system, as well as data related to the context, emotions, and cultural background of that text data.

[0793] "Natural language processing" refers to the technology that enables computers to understand, analyze, and generate human language, and is used to extract context and sentiment from text data.

[0794] "Emotion detection" refers to the process of identifying the type and intensity of emotions from input information and quantifying them as a specific score or category.

[0795] "Cultural background information" refers to data related to values, customs, and communication styles specific to a particular country, region, or group.

[0796] "Generative artificial intelligence technology" refers to technology that naturally generates translations and interpretations based on input data, supporting communication tailored to the user's needs.

[0797] "Communication style" refers to the way a message is expressed and its tone, and the style suggested to best convey the intended meaning to the recipient.

[0798] This invention is a system aimed at improving intercultural communication, which translates and interprets information based on user input, incorporating emotional analysis and cultural considerations. The system consists of a terminal, a server, and a generative AI model.

[0799] The terminal is responsible for receiving information from the user. This information is primarily text data and includes the user's emotions and intentions. This information is transmitted to the server using a secure communication protocol.

[0800] The server analyzes received information using natural language processing techniques. These techniques include morphological analysis, contextual understanding, and sentiment analysis, aiming to extract context and emotion from the information. Furthermore, the server incorporates an emotion engine that detects emotions from input information and quantifies them as scores or categories. This process is crucial for accurately understanding the intent of messages by quantifying the intensity of emotions.

[0801] The analyzed data is integrated with cultural background information. This is a crucial step to avoid misunderstandings with recipients from different cultures. Based on this analysis, the generative AI model generates natural and contextually appropriate translations and interpretations, constructing messages that are sensitive to emotions and culture. This goes beyond simple translation and enables information transmission optimized for the recipient's cultural context.

[0802] For example, if a user wants to send a reply to an overseas business partner that includes constructive feedback while avoiding negative feelings, this system can analyze the user's input text, "I want to convey my concerns about next week's meeting," and suggest appropriate and considerate phrasing. An example of a prompt sentence to input into the generating AI model would be, "Please suggest a reply in a business email that includes constructive feedback while avoiding negative feelings."

[0803] As described above, this system provides users with a powerful tool to support intercultural communication.

[0804] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0805] Step 1:

[0806] The terminal receives text data from the user as input. This input contains information including the message and intentions the user wants to send. The terminal applies security protocols such as encryption to securely transmit this text data to the server.

[0807] Step 2:

[0808] The server receives text data sent from the terminal. This input is analyzed by a natural language processing unit to extract context, keywords, and signs of sentiment. The output of the data analysis is contextual and sentimental information of the message, which is used as foundational data for subsequent processing.

[0809] Step 3:

[0810] The emotion engine installed on the server receives analyzed contextual information as input, detects and quantifies the emotions within the text. This process outputs emotion scores and categories, forming a basis for determining how positive or negative a message is.

[0811] Step 4:

[0812] The server uses the obtained analytical and sentiment data as input and references the recipient's cultural background database. It translates and interprets messages to avoid cross-cultural misunderstandings. The output of this step is a culturally adapted, contextual, and sentiment-sensitive translation.

[0813] Step 5:

[0814] The generative AI model on the server uses the output of the translation process to construct the text. This process performs translation or interpretation in a natural way that aligns with the user's intent. The final output of this step is a natural message that is relevant to the transformed context.

[0815] Step 6:

[0816] The server, along with the generated message, suggests an appropriate communication style to the user. For example, the suggestion may include constructive language to avoid emotional misunderstandings. This suggestion is sent to the terminal as the final output.

[0817] Step 7:

[0818] The terminal displays the user the translation results and communication style suggestions sent from the server. The user reviews the message based on this output and edits it as needed. As a result of this process, the user is ready to create and send the final message.

[0819] Step 8:

[0820] The terminal collects user editing actions and feedback and sends them to the server. This feedback helps improve the system and increase its accuracy, and the accumulation of appropriate responses leads to better processing in the future.

[0821] (Application Example 2)

[0822] 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 robot 414 as the "terminal".

[0823] In modern society, intercultural communication can lead to misunderstandings and problems not only due to language differences but also to differences in cultural backgrounds and emotions. Such misunderstandings can create friction between individuals and organizations, hindering smooth communication. In particular, multinational environments demand rapid and appropriate communication, and conventional technologies offer limited means to adequately support this.

[0824] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0825] In this invention, the server includes means for detecting the user's emotional state and generating communication content based on the detection results, means for suggesting an appropriate communication style to the user, and means for collecting evaluation information from the user and using it to improve the system. This makes it possible for users to achieve appropriate communication that takes into account their emotions and culture, and to reduce misunderstandings between cultures.

[0826] A "user" is an individual or organization that provides input data using an information system.

[0827] "Information data" refers to text and other forms of data entered by users that are processed by the system.

[0828] "Means of receiving" refers to a device or program that has the function of acquiring information data provided by the user.

[0829] "Language processing" refers to the techniques used to analyze natural language and understand its meaning and context.

[0830] "Means of analysis" refers to a device or program that performs language processing on information data and has the function of extracting necessary information.

[0831] "Cultural background information" refers to information that includes customs, values, and linguistic characteristics associated with a particular society or group.

[0832] "Means for translation or interpretation" refers to a device or program that has the function of transforming analyzed information data to suit another language or context.

[0833] A "communication style" is a method of selecting language and expressions to suit a specific context or purpose.

[0834] "Means of suggestion" refers to a device or program that has the function of presenting appropriate actions or options to the user.

[0835] "Means for detecting emotional states" refers to a device or program that analyzes emotions from user input data and identifies a specific emotional state.

[0836] "Evaluation information" refers to data on evaluations and feedback that users provide regarding the services offered by the system.

[0837] An "information storage device" is a device for storing information data and background information, and it is intended to make this information accessible to the system.

[0838] "Computational intelligence technology" refers to technologies that use artificial intelligence to perform specific computational processes and make decisions.

[0839] The system realizing this invention includes a server that starts operating upon user input and has the function of precisely analyzing information. Specifically, the user inputs information data (text) using a terminal and sends that information data to the server. The server analyzes the information data using a language processing program (e.g., TextBlob library) and extracts context and sentiment. Furthermore, based on the analyzed data, it refers to cultural background information and utilizes computational intelligence technology (e.g., OpenAI API) to generate an appropriate translation or interpretation.

[0840] The server also has the ability to detect the user's emotional state and suggest an appropriate communication style based on that state. These suggestions are an important element in enabling users to communicate smoothly with people from different cultural backgrounds. By providing emotionally-based suggestions, it is possible to avoid misunderstandings and promote effective communication.

[0841] Furthermore, the server collects user feedback and uses this to improve the system's accuracy and effectiveness. For example, if a traveler wants to discuss an inappropriate order at a restaurant, the server will suggest a translation that soothes the user's feelings, generating a prompt such as, "Please translate 'The order was wrong' into Italian in a gentle and calm manner."

[0842] This system enables users to engage in sophisticated communication that takes culture and emotions into account in their daily lives and business environments.

[0843] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0844] Step 1:

[0845] The user inputs information data (input text) through a terminal. This input includes the user's emotions and messages. The input data is sent from the terminal to the server. Here, input involves manual user interaction, while output is raw information data received on the server side.

[0846] Step 2:

[0847] The server analyzes the received information data using a language processing program. Specifically, it uses the TextBlob library to extract context and sentiment from the information data. The input for this step is the received information data, and the output is the analyzed context information and sentiment score.

[0848] Step 3:

[0849] The server creates a translation or interpretation based on the analyzed information and references cultural background information. This process utilizes the OpenAI API as a computational intelligence technology to generate a translation that takes into account the user's emotions and the culture of the recipient. The input is the contextual information and emotion score obtained in the previous step, and the output is the proposed translation.

[0850] Step 4:

[0851] The server provides the user with a translation and suggests an appropriate communication style. This style suggestion utilizes a generative AI model to create prompts. The input is the translation, and the output is a specific recommendation of a communication style based on the translation.

[0852] Step 5:

[0853] The user reviews the translation and style suggestions provided by the server on their terminal. The user modifies the suggestions as needed and sends the final message. In this step, the input is the server's suggestions, and the output is the user's edited final message.

[0854] Step 6:

[0855] The terminal collects user feedback and sends it to the server to help improve the system. The server uses the feedback to improve the accuracy of prompt messages, update cultural background information, and so on. The input to this feedback cycle is user evaluation information, and the output is improved system performance.

[0856] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 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.

[0857] 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.

[0858] 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 robot 414.

[0859] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0860] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0861] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0862] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0863] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0864] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0865] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0866] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0867] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0868] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0869] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0870] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0871] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0872] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0873] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0874] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0875] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0876] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0877] The following is further disclosed regarding the embodiments described above.

[0878] (Claim 1)

[0879] A means of receiving text data entered by the user,

[0880] A means for analyzing received text data using natural language processing and extracting the context of the message,

[0881] A means of translating or interpreting text based on analyzed data and referring to the cultural background data of the recipient,

[0882] A means of suggesting an appropriate communication style to the user,

[0883] A means of collecting user feedback and using it to improve the system,

[0884] A system that includes this.

[0885] (Claim 2)

[0886] The system according to claim 1, comprising a database for storing user and recipient cultural background data.

[0887] (Claim 3)

[0888] The system according to claim 1, which generates translations or interpretations using generative artificial intelligence technology.

[0889] "Example 1"

[0890] (Claim 1)

[0891] A means of receiving information entered by the user,

[0892] A means of processing received information through language analysis and extracting the context of the message,

[0893] A means of translating or interpreting information based on the analyzed information and referring to the cultural background of the recipient,

[0894] A means of presenting appropriate communication methods,

[0895] A means of aggregating user feedback and using it to improve the system,

[0896] ...

[0897] A system that includes this.

[0898] (Claim 2)

[0899] The system according to claim 1, comprising a data structure for storing cultural background information of the user and the recipient.

[0900] (Claim 3)

[0901] The system according to claim 1, which generates translations or interpretations using generative AI technology.

[0902] "Application Example 1"

[0903] (Claim 1)

[0904] A means of receiving text data entered by the user,

[0905] A means for analyzing received text data using natural language processing and extracting the context of the message,

[0906] A means of translating or interpreting text based on analyzed data and referring to the cultural background data of the recipient,

[0907] To promote online interaction between different cultures, we offer a means to suggest appropriate communication styles to users and recommend conversation topics.

[0908] A means of collecting user feedback and using it to improve the system,

[0909] A system that includes this.

[0910] (Claim 2)

[0911] The system according to claim 1, which includes a database for storing user and recipient cultural background data, for processing text data in online communication in real time.

[0912] (Claim 3)

[0913] The system according to claim 1, which generates translations or interpretations using generative artificial intelligence technology and utilizes generative AI models in promoting cross-cultural exchange.

[0914] "Example 2 of combining an emotion engine"

[0915] (Claim 1)

[0916] A means of receiving information entered by the user,

[0917] A method for analyzing received information using natural language processing to extract context and emotions,

[0918] A means of detecting and quantifying emotions from analyzed information,

[0919] A means of translating or interpreting a message based on the analyzed information and referring to the recipient's cultural background information,

[0920] A means for generating translation or interpretation using artificial intelligence technology,

[0921] A means of suggesting an appropriate communication style to the user,

[0922] A means of collecting user feedback and using it to improve the accuracy of the system,

[0923] A system that includes this.

[0924] (Claim 2)

[0925] The system according to claim 1, comprising a data management function for storing cultural background information of the user and the recipient.

[0926] (Claim 3)

[0927] The system according to claim 1, which generates emotion-sensitive translations or interpretations using artificial intelligence technology.

[0928] "Application example 2 when combining with an emotional engine"

[0929] (Claim 1)

[0930] A means of receiving information data entered by the user,

[0931] A means of analyzing received information data using language processing and extracting the context of the information,

[0932] A means of translating or interpreting information based on the analyzed information and referring to the cultural background information of the recipient,

[0933] A means of suggesting an appropriate communication style to the user,

[0934] A means for detecting the user's emotional state and generating communication content based on the detection results,

[0935] A means of collecting user feedback information and using it to improve the system,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, comprising an information storage device for storing cultural background information of the user and the recipient.

[0939] (Claim 3)

[0940] The system according to claim 1, which generates translations or interpretations using computational intelligence technology. [Explanation of Symbols]

[0941] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving text data entered by the user, A means for analyzing received text data using natural language processing and extracting the context of the message, A means of translating or interpreting text based on analyzed data and referring to the cultural background data of the recipient, To promote online interaction between different cultures, we offer a means to suggest appropriate communication styles to users and recommend conversation topics. A means of collecting user feedback and using it to improve the system, A system that includes this.

2. The system according to claim 1, which includes a database for storing user and recipient cultural background data, for processing text data in online communication in real time.

3. The system according to claim 1, which generates translations or interpretations using generative artificial intelligence technology and utilizes generative AI models in promoting cross-cultural exchange.

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