system

Abstract

We provide the system. [Solution] A means of analyzing user-inputted text data to identify language, grammatical structure, and cultural nuances, A means of estimating the cultural background of the other party based on analyzed text data, Taking into account the estimated cultural background, means of performing appropriate translation and interpretation, A means of proposing appropriate communication styles and methods of expression to users, A means of displaying the results to the user, 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 in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a global society where people with different cultural backgrounds and languages communicate, cultural misunderstandings and communication frictions may occur. Such problems are factors that impede trust relationships and efficient communication, especially in international business negotiations and multicultural communication settings. The present invention aims to solve these problems and smooth communication between different cultures.

Means for Solving the Problems

[0005] This invention provides a means for analyzing text data entered by a user and identifying language, grammatical structure, and cultural nuances. Based on this analysis, it includes means for estimating the cultural background of the other party and performing appropriate translation and interpretation considering the estimation results. Furthermore, it provides a system that supports effective cross-cultural communication by suggesting appropriate communication styles and expressions to the user and displaying the results. This enables smooth communication with minimal misunderstandings, even in international business settings and situations where multiple cultures intersect.

[0006] A "user" refers to a person who uses the system to input text data and receive translation and communication assistance.

[0007] "Text data" refers to the written information entered by users, which is the subject of translation and cultural interpretation.

[0008] "Analysis" refers to the process of identifying and understanding features such as language, grammatical structure, and cultural nuances from text data.

[0009] "Cultural background" refers to information that constitutes an individual's or group's culture, including language, region, history, and customs, and that has a significant impact on communication.

[0010] "Translation" refers to the process of converting text data written in one language into a different language.

[0011] "Interpretation" refers to explanations and semantic interpretations made to clarify the meaning and intent of text data and to aid understanding.

[0012] "Communication style" refers to the way language is used and expressed in interactions with others, and includes methods for effective communication.

[0013] "Display" refers to the visual presentation of translated or suggested information so that the user can review it.

[0014] A "system" refers to a collection of technologies that provide a set of means and functions to support intercultural communication. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This 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 Embodiment 2 when the 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 the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0018] In the following embodiments, the numbered 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.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the numbered 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, and the like.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] 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."

[0023] [First Embodiment]

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

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

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

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is specifically implemented as a system to support intercultural communication. The initial operation performed by the user is to input text data through a terminal. This could be, for example, an email to a business partner with a different cultural background, or preparation for a presentation at a meeting. The user then uses a dedicated application on the terminal to send the text to the system.

[0037] The terminal sends the input text data to the server, which then analyzes the text using advanced natural language processing (NLP) techniques. During the analysis, the server identifies the language, interprets the grammatical structure, and recognizes subtle nuances between languages ​​and cultures. Based on the information obtained from this analysis, the server estimates the cultural background behind the input text. This estimation of cultural background utilizes cultural knowledge of the target language and its region.

[0038] Furthermore, the server utilizes a generative AI model to translate input text based on its estimated cultural context. This translation includes not only simple semantic conversions but also culturally conscious and appropriate expressions. For example, "a modest expression in accordance with the spirit of the Japanese tea ceremony" might be translated as "a direct and clear expression for an audience from American culture."

[0039] After the translation is complete, the server also suggests communication styles appropriate for different cultural backgrounds to the user. This suggestion is particularly useful in business and public communication to avoid misunderstandings. For example, it may offer suggestions on the use of honorifics and the order of self-introductions.

[0040] Ultimately, the terminal displays the translation results and suggestions sent from the server to the user. Based on these results, the user can then proceed with optimized communication. This system enables smooth communication in international business negotiations and multicultural exchange settings.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users input text data containing what they want to communicate using their device. This includes business emails and presentation scripts.

[0044] Step 2:

[0045] The terminal sends the entered text data to the server. At this stage, metadata such as the user ID and language selection are also sent.

[0046] Step 3:

[0047] The server analyzes the received text data. This includes language identification, grammatical structure analysis, and extraction of specific cultural nuances.

[0048] Step 4:

[0049] The server uses the analysis results to estimate the cultural background behind the input text. This estimation utilizes available database information.

[0050] Step 5:

[0051] The server uses a generated AI model to consider the estimated cultural background and perform appropriate translation and interpretation. In doing so, it selects culturally appropriate expressions.

[0052] Step 6:

[0053] The server suggests a communication style appropriate to the user's estimated cultural background. This includes suggestions for greetings and expressions.

[0054] Step 7:

[0055] The terminal receives the translation results and communication style suggestions sent from the server and displays them to the user.

[0056] Step 8:

[0057] Users review the displayed translation results and suggestions, make adjustments as needed, and communicate effectively with the other party.

[0058] (Example 1)

[0059] 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."

[0060] In intercultural communication, misunderstandings and the use of inappropriate expressions stemming from differences in language and cultural background are problematic. Under these circumstances, ensuring smooth and effective communication is essential in international business transactions, conferences, and multicultural exchanges. Traditional translation methods are limited to simple language conversion, making it difficult to appropriately consider cultural nuances and backgrounds in translation.

[0061] 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.

[0062] In this invention, the server includes means for analyzing user-input data using natural language processing technology to identify linguistic and cultural nuances, means for estimating the other party's cultural characteristics based on the analysis results, and means for performing appropriate translation and interpretation that takes cultural characteristics into account using generative AI technology. This enables smooth intercultural communication.

[0063] "User-input data" refers to information provided by the user via the device, such as text data necessary to support cross-cultural communication.

[0064] A "terminal" is a device used by a user to input data and send it to a server, and includes, for example, computers and smartphones.

[0065] A "server" refers to an information processing device that receives data transmitted from a terminal and performs processing such as analysis, translation, and suggestions.

[0066] "Natural language processing technology" refers to technologies that enable computers to understand and process language data, and includes functions such as language identification, grammatical structure analysis, and nuance recognition.

[0067] "Generative AI technology" refers to techniques that use artificial intelligence to generate data, and specifically to methods used for generating translations and expressions that take cultural characteristics into consideration.

[0068] "Cultural characteristics" refer to cultural elements and background information specific to a language or region, and play an important role in communication.

[0069] "Translation and interpretation" refers to the process of re-expressing text from one language in a way that is appropriate for another language or culture, taking into account not only word-level details but also context and cultural nuances.

[0070] "Communication style" refers to the manner in which information is transmitted between different cultures, including appropriate vocabulary, phrasing, and methods of expression.

[0071] This invention provides a system for effectively supporting intercultural communication. The user uses a terminal to input text data for communication with someone from a specific cultural or linguistic background. The terminal sends this data to a server, which analyzes the received data using natural language processing techniques. This analysis utilizes language models and cultural knowledge databases and includes processes for identifying language, grammatical structures, and cultural nuances.

[0072] The server estimates the cultural characteristics of the input text based on the analysis results. This estimation refers to a database containing pre-prepared cultural data. Furthermore, it utilizes generative AI technology to perform translation and interpretation that takes cultural characteristics into account. The generative AI technology generates appropriate vocabulary and expressions using prompt sentences, and guarantees that the generated translation is culturally sensitive.

[0073] As a concrete example, if a user inputs the polite greeting "Osewa ni natte orimasu" (Thank you for your continued support), which is used in Japanese business settings, the system will translate this into the expression "Hello, I hope you are doing well," which is appropriate for American business settings. In this case, the generation AI model will use the prompt "Translate the following text to an American business context: Osewa ni natte orimasu."

[0074] Ultimately, the translation results and suggested communication style are displayed on the device, allowing the user to communicate effectively. In this way, the present invention contributes to preventing misunderstandings between cultures and facilitating smooth dialogue.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] Users input text data for the purpose of cross-cultural communication through a dedicated application on their terminal. This text is used, for example, in business emails or presentations at meetings. The terminal sends the input text data to the server. The output from the terminal is the transmission of text data to the server.

[0078] Step 2:

[0079] The server analyzes text data received from the terminal using natural language processing (NLP) techniques. Based on the text data as input, the server performs language identification, grammatical analysis, and recognition of cultural nuances. This results in outputting linguistic and cultural background information of the text.

[0080] Step 3:

[0081] The server references the analysis data and estimates the cultural characteristics of the subject. To perform this estimation, the server uses a cultural knowledge database. The input is the analysis data of language and cultural background, and the output is the estimated cultural characteristics. This process takes into account culture-specific expressions and customs.

[0082] Step 4:

[0083] The server uses a generative AI model to translate and interpret text based on estimated cultural characteristics. Here, the input is the cultural characteristics, which are used to instruct the generative AI model through prompt sentences. The output is the translated text in a culturally appropriate format.

[0084] Step 5:

[0085] The server provides the user with translation results and suggests appropriate communication styles and expressions for different cultures. These suggestions include hints on specific communication methods, such as the use of honorifics and the order of statements. The input is the translation result, and the output is the suggested communication style.

[0086] Step 6:

[0087] The terminal displays the translation results and suggestions sent from the server to the user. The user can review this and edit it as needed. The terminal's output is the screen display that should be shown to the user. Based on this result, the user can further optimize cross-cultural communication.

[0088] (Application Example 1)

[0089] 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."

[0090] In communication between individuals from different cultural backgrounds, differences in language and cultural nuances can lead to misunderstandings, sometimes resulting in misinterpretations of intended meanings. Furthermore, interactions with multinational customers, particularly at physical sales locations, require prompt and appropriate responses. In these situations, support is needed to enable staff to handle customer interactions efficiently and accurately.

[0091] 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.

[0092] In this invention, the server includes means for analyzing language data entered by a user and identifying linguistic characteristics, grammatical structure, and cultural nuances; means for estimating the recipient's cultural background based on the analyzed language data; and means for performing appropriate translation or interpretation while taking the estimated cultural background into consideration. This enables staff at physical sales locations to more smoothly respond to and communicate with multinational customers.

[0093] A "user" is an individual or group that operates the system and seeks support for culturally appropriate communication.

[0094] "Linguistic data" refers to the content of documents and conversations entered by users, and is the subject of cultural meaning analysis based on this data.

[0095] "Analysis" is the process of understanding the structure and meaning of input linguistic data and identifying the cultural elements behind it.

[0096] "Linguistic characteristics" refer to the unique grammar and expressions of a particular language.

[0097] "Grammar structure" refers to the arrangement and construction of words in a language, and plays an important role in understanding that language.

[0098] "Cultural nuances" refer to the subtle cultural nuances and backgrounds contained within linguistic expressions.

[0099] "Recipient" refers to the person with whom a user communicates.

[0100] "Cultural background" refers to the social, historical, and cultural context that lies behind language and expression.

[0101] Translation refers to the act of changing content expressed in one language into another language, and cultural considerations are essential for accurate transmission.

[0102] "Interpretation" is the act of understanding a language or cultural expression and grasping its meaning.

[0103] A "physical sales location" refers to a physical store or service location where direct customer service and product provision take place.

[0104] "Multinational customers" refer to customers from multiple countries and cultures, who often have different cultural expectations and linguistic backgrounds.

[0105] The implementation of this invention is primarily carried out through data exchange between the user, terminal, and server. The user, acting as a store staff member, uses a terminal such as a smartphone and utilizes the cross-cultural communication support system by inputting information obtained during conversations with customers.

[0106] The terminal sends the input language data to the server, which analyzes this data using advanced natural language processing techniques. In this process, the server identifies linguistic characteristics, grammatical structures, and cultural nuances. Furthermore, based on this, the server estimates the cultural background of the recipient (the customer) and utilizes a generative AI model to perform appropriate translation and interpretation. Translation considers cultural relevance beyond simple language conversion.

[0107] Users receive translations and communication style suggestions from the server on their devices, enabling them to communicate more smoothly with multinational customers. For example, this could be used when staff working at a physical store in Japan instantly translate a Japanese inquiry into a polite English response for a customer from an English-speaking country.

[0108] The server operates via a dedicated application running on portable devices such as smartphones and tablets. The overall system's performance is maximized through the collaboration of natural language processing software and generative AI models.

[0109] An example of a prompt would be: "To facilitate intercultural communication, please generate a response that includes a translation and communication suggestions that take cultural backgrounds into consideration."

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The user inputs information obtained from conversations with customers into a dedicated application on their smartphone. The input data is text information, including the content of the conversation and hypotheses about the customer's cultural background. The device receives this data and prepares to send it to the server.

[0113] Step 2:

[0114] The terminal sends the entered text data to the server. The transmitted data is then analyzed on the server using natural language processing techniques. Specifically, it undergoes processing to identify linguistic characteristics, grammatical structures, and cultural nuances. This enables a structural understanding of the data.

[0115] Step 3:

[0116] The server estimates the cultural background of the recipient customer based on the analysis results. This estimation uses a pre-trained cultural information database and a generative AI model. This process involves data computations that compare the characteristics of the input data with known cultural information to identify the appropriate cultural context.

[0117] Step 4:

[0118] The server translates and interprets the input text based on the estimated cultural background. Using a generative AI model, it performs translations that reflect not only the semantic conversion of words but also cultural relevance within the context. The results are generated in a format that is easy for the user to understand.

[0119] Step 5:

[0120] The server sends the translation results and a suggested communication style based on the cultural context to the terminal. In this process, the server selects the most suitable option from the generated text and suggestions, and sends it to the user as practical information.

[0121] Step 6:

[0122] The user's device displays the translation results and suggestions received from the server. Based on the displayed information, the user can respond appropriately to multinational customers. In this way, cross-cultural communication proceeds smoothly.

[0123] 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.

[0124] This invention is implemented as a cross-cultural communication support system that takes user emotions into consideration. This system has a function that recognizes the user's emotions using an emotion engine based on text data entered by the user on a terminal. When a user uses their terminal to input, for example, business emails or negotiation details, that data is sent to the server along with the emotion engine.

[0125] On the server, the received text data is first subjected to linguistic analysis. This includes language identification, grammatical structure analysis, and extraction of cultural nuances. These analyses clarify the context of the text and the user's intent. The sentiment engine also determines whether the user is experiencing any emotion—for example, joy, anger, or sadness—based on the word choice, expressions, and tone of the sentences within the text.

[0126] The analyzed data is then used by a generative AI model to estimate the cultural context, and culturally appropriate translation and interpretation are performed. The translation process here is performed based on adjustments made by the server, particularly taking sentiment recognition into account, and considers both the cultural context and the user's emotional state. For example, if the user is feeling stressed or tense, the translation will reflect a more relaxed tone and considerate expression.

[0127] The server then suggests a communication style that is appropriate for the user. Since the suggestions reflect the emotional state recognized by the emotion engine, the user can choose an appropriate communication method based on their own emotional state.

[0128] Ultimately, the device displays the translation results and suggestions to the user. Based on these results, the user can engage in effective communication that takes emotions into account. For example, in cross-cultural negotiations, the user can communicate confidently while utilizing the system's suggestions to prevent their own tension or anxiety from being conveyed to the other party.

[0129] The following describes the processing flow.

[0130] Step 1:

[0131] The user inputs text data containing emotions using a device. For example, the user might input something like, "I've been feeling anxious about my recent presentations."

[0132] Step 2:

[0133] The terminal sends the entered text data to the server. Metadata, including the user ID and language information, is also sent along with the data.

[0134] Step 3:

[0135] The server analyzes the received text data using natural language processing (NLP) techniques. This involves language identification, grammatical structure analysis, and extraction of cultural nuances.

[0136] Step 4:

[0137] The server uses an emotion engine to recognize the user's emotions from text data. This process determines what emotions the user is experiencing based on keywords and context.

[0138] Step 5:

[0139] The server estimates the cultural context of the text based on the analysis results. This estimation process takes into account standard communication patterns in different regions and cultures.

[0140] Step 6:

[0141] The server utilizes a generated AI model to consider the estimated cultural background and user emotions, and then performs appropriate translation and interpretation. In this case, the translation selects expressions that reflect the user's emotions.

[0142] Step 7:

[0143] The server takes the user's emotional state into account and suggests a communication style that suits them. For example, it might recommend calm language or a structured approach to alleviate anxiety.

[0144] Step 8:

[0145] The device receives translation results and style suggestions sent from the server and displays them to the user. Based on this, the user engages in optimal communication to accurately convey their intentions.

[0146] (Example 2)

[0147] 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".

[0148] In intercultural communication, misunderstandings and friction arise due to differences in language, cultural nuances, and a lack of emotional transmission. This problem is particularly evident in international business negotiations and multicultural exchanges, where facilitating smoother communication is essential. To address these challenges, an appropriate information transmission method that takes into account cultural backgrounds and user emotions is necessary.

[0149] 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.

[0150] In this invention, the server includes means for analyzing information entered by the user and identifying linguistic characteristics, grammatical structure, and cultural features; means for estimating the cultural context of others based on the analyzed information; and means for determining the user's emotional state using an emotion analysis function. This enables translation and interpretation that takes cultural background and emotions into account, as well as the proposal of appropriate information transmission methods.

[0151] A "user" is an individual or organization that inputs information into a system and utilizes its output.

[0152] "Information" refers to the text and data that users input into the system, which may include business messages and negotiation details.

[0153] "Analysis" is a procedure for processing input information and understanding its structure and content.

[0154] "Language characteristics" refer to grammatical rules and expressions specific to a particular language.

[0155] "Grammar structure" refers to the rules governing the arrangement and relationships of the elements (words and phrases) that make up a text.

[0156] "Cultural characteristics" refer to values, customs, or social norms that are specific to a particular region or group.

[0157] "Estimation" is the process of drawing conclusions with a certain degree of confidence based on incomplete information.

[0158] "Cultural context" refers to the cultural background and current state of affairs within a particular society or group.

[0159] "Sentiment analysis" is a technique that identifies and evaluates emotions based on the context and tone of text data.

[0160] Translation is the act of accurately converting information written in one language into another language.

[0161] "Interpretation" is the process of understanding and explaining the meaning and importance of given information.

[0162] "Information transmission methods" refer to the means and methods for effectively conveying information to others.

[0163] This invention is a system that supports intercultural communication. Users input business documents and messages using their own terminals. This information is first sent from the terminal to a server. The server has powerful data analysis capabilities and uses natural language processing libraries to identify the linguistic characteristics, grammatical structure, and cultural features of the received information.

[0164] The server then uses sentiment analysis technology to determine the emotional state the user is expressing in the text. This allows for the identification of emotions such as joy, anger, and sadness. The analyzed data is processed by a generative AI model, such as a large-scale language model, to estimate the cultural context and provide appropriate translations and interpretations. This entire process adjusts the tone and choice of expressions in the text, enabling communication that takes cultural context and emotions into account.

[0165] Furthermore, the server suggests a communication style suitable for the user. For example, by inputting a prompt sentence such as "Please suggest expressions that will give the user a relaxed impression to their negotiating partner," the AI ​​model can elicit an appropriate response.

[0166] Ultimately, the terminal displays the translation results and suggestions received from the server to the user. Based on this information, the user can engage in smooth and effective cross-cultural communication. This invention is envisioned for use in specific examples such as international business negotiations and multicultural exchanges, and is expected to reduce barriers to information transmission and promote better mutual understanding.

[0167] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0168] Step 1:

[0169] Users input text data, such as work-related documents and messages, using their own devices. This input includes the user's intended message and the emotions they wish to express. The device recognizes this as digital data and prepares it for transmission to the server.

[0170] Step 2:

[0171] The terminal sends the entered text data to the server. During this transmission, a communication protocol (e.g., HTTPS) is used to ensure data integrity and security. This allows the server to receive the data accurately and securely.

[0172] Step 3:

[0173] The server analyzes the received text data using a natural language processing library. Specifically, it processes the data to identify linguistic characteristics, grammatical structure, and cultural features. This analysis outputs the basic structure and contextual information of the text.

[0174] Step 4:

[0175] The server utilizes sentiment analysis capabilities to identify emotions within text. By evaluating the vocabulary and tone of the input text, it identifies the user's emotional state and assigns emotion tags such as joy, anger, and sadness. This provides important output for understanding the emotional nuances within the text.

[0176] Step 5:

[0177] The server inputs the analysis data into an AI model that generates the data, estimates the cultural background, and performs appropriate translation and interpretation. In this process, the AI ​​model considers the cultural context and provides a translation that is adjusted to match the user's emotions. As a result, content that is considerate of culture and emotions is output.

[0178] Step 6:

[0179] The server suggests a communication style that suits the user. Here, based on the results of sentiment analysis, a generative AI model selects appropriate expressions and tones in response to the prompt text and presents them to the user as suggestions.

[0180] Step 7:

[0181] The terminal displays the translation results and suggestions received from the server to the user. Based on this information, the user can confidently engage in cross-cultural communication while utilizing the system's advice.

[0182] (Application Example 2)

[0183] 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".

[0184] In intercultural communication, differing cultural backgrounds and emotional states can lead to misunderstandings, hindering smooth dialogue. Furthermore, interactions within families and multicultural environments tend to be complex, making it challenging to promote mutual understanding.

[0185] 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.

[0186] In this invention, the server includes means for analyzing text information entered by a user, means for estimating the cultural background of others based on the analyzed text information, and means for performing appropriate translation and interpretation while taking into account the estimated cultural background and emotional state. This makes it possible to promote interaction within families and multicultural environments and reduce misunderstandings in intercultural communication.

[0187] "User-input text information" refers to language data entered by users through their devices, intended for the purpose of cross-cultural communication.

[0188] "Means of analysis" refers to the process of understanding and organizing the structure, language, and cultural elements of received text information.

[0189] "Means for estimating the cultural background of others" refers to methods for determining the cultural background of a communication partner based on analyzed data, and for deepening one's understanding of that background.

[0190] "Means of appropriate translation and interpretation" refers to the process of performing translation and interpretation necessary to convey information to others, taking into account not only the meaning of the language but also the culture and emotions involved.

[0191] "Emotional state" refers to the psychological state that a user is experiencing when entering text information, including the type and intensity of the emotions they are feeling at that time.

[0192] "Home and multicultural environments" refer to places where people with diverse cultural backgrounds live together and interact with one another.

[0193] "Promoting communication" refers to initiatives aimed at deepening mutual understanding and exchanging information more smoothly and effectively.

[0194] In the system implementing this invention, the user first inputs their speech or message using a terminal. The server receives this input and first performs language analysis. This process uses software such as Google® Speech-to-Text API and DeepL API to organize the language structure and cultural interpretation based on the input information. After obtaining the analyzed text information, the server then runs an emotion analysis model using TENSORFLOW® to extract the user's emotional state. This makes it possible to identify whether the user is experiencing any particular emotion.

[0195] The server also has the ability to estimate the cultural background of others based on the analysis results. This utilizes generative AI technology, specifically the OpenAI® GPT model, to perform appropriate translations and interpretations that take culture and emotions into account. For example, it can consider the tone of conversation and insert more amiable expressions as needed.

[0196] Finally, the translation results and communication style suggestions are displayed on the device. This enables users to engage in smooth and effective communication within their homes and in multicultural environments.

[0197] As a concrete example, when a guest from France visits a Japanese host family, the robot recognizes the guest's statement, "I'm having a great time today!", and suggests to the host, "It seems our French guest is enjoying themselves. How about we talk about French home cooking next?" This suggestion is generated using a generative AI model with the prompt, "Based on this user's emotions, suggest an appropriate communication style. As a Japanese household robot interacting with a guest from overseas, indicate how you should lead the conversation."

[0198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0199] Step 1:

[0200] The user inputs text information into the terminal. The input data can be in voice or text format. The terminal sends this input as digital data to the server.

[0201] Step 2:

[0202] The server uses the Google Speech-to-Text API to convert audio data into text. During this process, the input audio data is automatically analyzed and output as text data.

[0203] Step 3:

[0204] The server uses the DeepL API to perform linguistic analysis on text information. From the text received as input data, it extracts the linguistic structure and cultural nuances, reveals the grammatical structure, and outputs it as text data.

[0205] Step 4:

[0206] The server uses a TensorFlow-based sentiment analysis model to extract the emotional state from analyzed text information. Text data is input, and the server outputs the user's emotions (joy, surprise, sadness, etc.) as numerical data.

[0207] Step 5:

[0208] The server uses OpenAI's GPT as its generative AI model to perform translation and interpretation that takes cultural background and emotional states into account. It takes prompt sentences that take emotions and culture into account as input and outputs text that suggests the optimal translation and communication style.

[0209] Step 6:

[0210] Translation results and suggestions are sent from the server to the terminal. The terminal displays the received data to the user, who then engages in smooth communication based on that information. For example, the terminal can select a dialogue based on the displayed suggestions.

[0211] 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.

[0212] Data generation model 58 is a 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.

[0213] 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.

[0214] [Second Embodiment]

[0215] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0216] 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.

[0217] 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).

[0218] 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.

[0219] 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.

[0220] 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).

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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".

[0227] This invention is specifically implemented as a system to support intercultural communication. The initial operation performed by the user is to input text data through a terminal. This could be, for example, an email to a business partner with a different cultural background, or preparation for a presentation at a meeting. The user then uses a dedicated application on the terminal to send the text to the system.

[0228] The terminal sends the input text data to the server, which then analyzes the text using advanced natural language processing (NLP) techniques. During the analysis, the server identifies the language, interprets the grammatical structure, and recognizes subtle nuances between languages ​​and cultures. Based on the information obtained from this analysis, the server estimates the cultural background behind the input text. This estimation of cultural background utilizes cultural knowledge of the target language and its region.

[0229] Furthermore, the server utilizes a generative AI model to translate input text based on its estimated cultural context. This translation includes not only simple semantic conversions but also culturally conscious and appropriate expressions. For example, "a modest expression in accordance with the spirit of the Japanese tea ceremony" might be translated as "a direct and clear expression for an audience from American culture."

[0230] After the translation is complete, the server also suggests communication styles appropriate for different cultural backgrounds to the user. This suggestion is particularly useful in business and public communication to avoid misunderstandings. For example, it may offer suggestions on the use of honorifics and the order of self-introductions.

[0231] Ultimately, the terminal displays the translation results and suggestions sent from the server to the user. Based on these results, the user can then proceed with optimized communication. This system enables smooth communication in international business negotiations and multicultural exchange settings.

[0232] The following describes the processing flow.

[0233] Step 1:

[0234] Users input text data containing what they want to communicate using their device. This includes business emails and presentation scripts.

[0235] Step 2:

[0236] The terminal sends the entered text data to the server. At this stage, metadata such as the user ID and language selection are also sent.

[0237] Step 3:

[0238] The server analyzes the received text data. This includes language identification, grammatical structure analysis, and extraction of specific cultural nuances.

[0239] Step 4:

[0240] The server uses the analysis results to estimate the cultural background behind the input text. This estimation utilizes available database information.

[0241] Step 5:

[0242] The server uses a generated AI model to consider the estimated cultural background and perform appropriate translation and interpretation. In doing so, it selects culturally appropriate expressions.

[0243] Step 6:

[0244] The server suggests a communication style appropriate to the user's estimated cultural background. This includes suggestions for greetings and expressions.

[0245] Step 7:

[0246] The terminal receives the translation results and communication style suggestions sent from the server and displays them to the user.

[0247] Step 8:

[0248] Users review the displayed translation results and suggestions, make adjustments as needed, and communicate effectively with the other party.

[0249] (Example 1)

[0250] 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."

[0251] In intercultural communication, misunderstandings and the use of inappropriate expressions stemming from differences in language and cultural background are problematic. Under these circumstances, ensuring smooth and effective communication is essential in international business transactions, conferences, and multicultural exchanges. Traditional translation methods are limited to simple language conversion, making it difficult to appropriately consider cultural nuances and backgrounds in translation.

[0252] 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.

[0253] In this invention, the server includes means for analyzing user-input data using natural language processing technology to identify linguistic and cultural nuances, means for estimating the other party's cultural characteristics based on the analysis results, and means for performing appropriate translation and interpretation that takes cultural characteristics into account using generative AI technology. This enables smooth intercultural communication.

[0254] "User-input data" refers to information provided by the user via the device, such as text data necessary to support cross-cultural communication.

[0255] A "terminal" is a device used by a user to input data and send it to a server, and includes, for example, computers and smartphones.

[0256] A "server" refers to an information processing device that receives data transmitted from a terminal and performs processing such as analysis, translation, and suggestions.

[0257] "Natural language processing technology" refers to technologies that enable computers to understand and process language data, and includes functions such as language identification, grammatical structure analysis, and nuance recognition.

[0258] "Generative AI technology" refers to techniques that use artificial intelligence to generate data, and specifically to methods used for generating translations and expressions that take cultural characteristics into consideration.

[0259] "Cultural characteristics" refer to cultural elements and background information specific to a language or region, and play an important role in communication.

[0260] "Translation and interpretation" refers to the process of re-expressing text from one language in a way that is appropriate for another language or culture, taking into account not only word-level details but also context and cultural nuances.

[0261] "Communication style" refers to the manner in which information is transmitted between different cultures, including appropriate vocabulary, phrasing, and methods of expression.

[0262] This invention provides a system for effectively supporting intercultural communication. The user uses a terminal to input text data for communication with someone from a specific cultural or linguistic background. The terminal sends this data to a server, which analyzes the received data using natural language processing techniques. This analysis utilizes language models and cultural knowledge databases and includes processes for identifying language, grammatical structures, and cultural nuances.

[0263] The server estimates the cultural characteristics of the input text based on the analysis results. This estimation refers to a database containing pre-prepared cultural data. Furthermore, it utilizes generative AI technology to perform translation and interpretation that takes cultural characteristics into account. The generative AI technology generates appropriate vocabulary and expressions using prompt sentences, and guarantees that the generated translation is culturally sensitive.

[0264] As a concrete example, if a user inputs the polite greeting "Osewa ni natte orimasu" (Thank you for your continued support), which is used in Japanese business settings, the system will translate this into the expression "Hello, I hope you are doing well," which is appropriate for American business settings. In this case, the generation AI model will use the prompt "Translate the following text to an American business context: Osewa ni natte orimasu."

[0265] Ultimately, the translation results and suggested communication style are displayed on the device, allowing the user to communicate effectively. In this way, the present invention contributes to preventing misunderstandings between cultures and facilitating smooth dialogue.

[0266] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0267] Step 1:

[0268] Users input text data for the purpose of cross-cultural communication through a dedicated application on their terminal. This text is used, for example, in business emails or presentations at meetings. The terminal sends the input text data to the server. The output from the terminal is the transmission of text data to the server.

[0269] Step 2:

[0270] The server analyzes text data received from the terminal using natural language processing (NLP) techniques. Based on the text data as input, the server performs language identification, grammatical analysis, and recognition of cultural nuances. This results in outputting linguistic and cultural background information of the text.

[0271] Step 3:

[0272] The server references the analysis data and estimates the cultural characteristics of the subject. To perform this estimation, the server uses a cultural knowledge database. The input is the analysis data of language and cultural background, and the output is the estimated cultural characteristics. This process takes into account culture-specific expressions and customs.

[0273] Step 4:

[0274] The server uses a generative AI model to translate and interpret text based on estimated cultural characteristics. Here, the input is the cultural characteristics, which are used to instruct the generative AI model through prompt sentences. The output is the translated text in a culturally appropriate format.

[0275] Step 5:

[0276] The server provides the user with translation results and suggests appropriate communication styles and expressions for different cultures. These suggestions include hints on specific communication methods, such as the use of honorifics and the order of statements. The input is the translation result, and the output is the suggested communication style.

[0277] Step 6:

[0278] The terminal displays the translation results and suggestions sent from the server to the user. The user can review this and edit it as needed. The terminal's output is the screen display that should be shown to the user. Based on this result, the user can further optimize cross-cultural communication.

[0279] (Application Example 1)

[0280] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0281] In communication between individuals with different cultural backgrounds, differences in language and cultural nuances may cause misunderstandings, and the original intention may not be accurately conveyed. Also, especially in interactions with multinational customers at physical sales bases, prompt and appropriate responses are required. In such situations, support is needed for staff to efficiently and accurately handle customer interactions.

[0282] 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.

[0283] In this invention, the server includes means for analyzing language data input by a user to identify language characteristics, grammatical structures, and cultural nuances, means for estimating the cultural background of the recipient based on the analyzed language data, and means for performing appropriate translation and interpretation in consideration of the estimated cultural background. As a result, at physical sales bases, it becomes possible for staff to more smoothly handle appropriate responses and communication with multinational customers.

[0284] A "user" is an individual or group that operates a system and seeks support for culturally appropriate communication.

[0285] "Language data" refers to the content of documents or conversations input by a user, and is the object for analyzing cultural meaning based on this.

[0286] "Analysis" is a process of understanding the structure and meaning of the input language data and identifying the cultural elements behind it.

[0287] "Language characteristics" refer to the uniqueness of grammar and expressions of a specific language.

[0288] "Grammatical structure" refers to the arrangement and assembly of words in a language, and plays an important role in language understanding.

[0289] "Cultural nuances" refer to the subtle cultural nuances and backgrounds contained within linguistic expressions.

[0290] "Recipient" refers to the person with whom a user communicates.

[0291] "Cultural background" refers to the social, historical, and cultural context that lies behind language and expression.

[0292] Translation refers to the act of changing content expressed in one language into another language, and cultural considerations are essential for accurate transmission.

[0293] "Interpretation" is the act of understanding a language or cultural expression and grasping its meaning.

[0294] A "physical sales location" refers to a physical store or service location where direct customer service and product provision take place.

[0295] "Multinational customers" refer to customers from multiple countries and cultures, who often have different cultural expectations and linguistic backgrounds.

[0296] The implementation of this invention is primarily carried out through data exchange between the user, terminal, and server. The user, acting as a store staff member, uses a terminal such as a smartphone and utilizes the cross-cultural communication support system by inputting information obtained during conversations with customers.

[0297] The terminal sends the input language data to the server, which analyzes this data using advanced natural language processing techniques. In this process, the server identifies linguistic characteristics, grammatical structures, and cultural nuances. Furthermore, based on this, the server estimates the cultural background of the recipient (the customer) and utilizes a generative AI model to perform appropriate translation and interpretation. Translation considers cultural relevance beyond simple language conversion.

[0298] Users receive translations and communication style suggestions from the server on their devices, enabling them to communicate more smoothly with multinational customers. For example, this could be used when staff working at a physical store in Japan instantly translate a Japanese inquiry into a polite English response for a customer from an English-speaking country.

[0299] The server operates via a dedicated application running on portable devices such as smartphones and tablets. The overall system's performance is maximized through the collaboration of natural language processing software and generative AI models.

[0300] An example of a prompt would be: "To facilitate intercultural communication, please generate a response that includes a translation and communication suggestions that take cultural backgrounds into consideration."

[0301] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0302] Step 1:

[0303] The user inputs information obtained from conversations with customers into a dedicated application on their smartphone. The input data is text information, including the content of the conversation and hypotheses about the customer's cultural background. The device receives this data and prepares to send it to the server.

[0304] Step 2:

[0305] The terminal sends the entered text data to the server. The transmitted data is then analyzed on the server using natural language processing techniques. Specifically, it undergoes processing to identify linguistic characteristics, grammatical structures, and cultural nuances. This enables a structural understanding of the data.

[0306] Step 3:

[0307] The server estimates the cultural background of the customer, who is the recipient, based on the analysis results. For the estimation, a pre-trained cultural information database and a generative AI model are used. This process involves data operations that compare the characteristics of the input data with known cultural information and identify the appropriate cultural context.

[0308] Step 4:

[0309] Based on the estimated cultural background, the server translates and interprets the input text. Using the generative AI model, it performs translations that not only convert the meaning of words but also reflect the cultural appropriateness in the context. The results are generated in a form that is easy for the user to understand.

[0310] Step 5:

[0311] The server sends the translation result and the proposed communication style based on the cultural background to the terminal. In this process, the most suitable one is selected from the generated text and the proposals and sent as practical information for the user.

[0312] Step 6:

[0313] The user's terminal displays the translation result and the proposals received from the server. Based on the displayed content, the user can appropriately respond to multinational customers. Thus, cross-cultural communication proceeds smoothly.

[0314] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0315] This invention is implemented as a cross-cultural communication support system that takes user emotions into consideration. This system has a function that recognizes the user's emotions using an emotion engine based on text data entered by the user on a terminal. When a user uses their terminal to input, for example, business emails or negotiation details, that data is sent to the server along with the emotion engine.

[0316] On the server, the received text data is first subjected to linguistic analysis. This includes language identification, grammatical structure analysis, and extraction of cultural nuances. These analyses clarify the context of the text and the user's intent. The sentiment engine also determines whether the user is experiencing any emotion—for example, joy, anger, or sadness—based on the word choice, expressions, and tone of the sentences within the text.

[0317] The analyzed data is then used by a generative AI model to estimate the cultural context, and culturally appropriate translation and interpretation are performed. The translation process here is performed based on adjustments made by the server, particularly taking sentiment recognition into account, and considers both the cultural context and the user's emotional state. For example, if the user is feeling stressed or tense, the translation will reflect a more relaxed tone and considerate expression.

[0318] The server then suggests a communication style that is appropriate for the user. Since the suggestions reflect the emotional state recognized by the emotion engine, the user can choose an appropriate communication method based on their own emotional state.

[0319] Ultimately, the device displays the translation results and suggestions to the user. Based on these results, the user can engage in effective communication that takes emotions into account. For example, in cross-cultural negotiations, the user can communicate confidently while utilizing the system's suggestions to prevent their own tension or anxiety from being conveyed to the other party.

[0320] The following describes the processing flow.

[0321] Step 1:

[0322] The user inputs text data containing emotions using a device. For example, the user might input something like, "I've been feeling anxious about my recent presentations."

[0323] Step 2:

[0324] The terminal sends the entered text data to the server. Metadata, including the user ID and language information, is also sent along with the data.

[0325] Step 3:

[0326] The server analyzes the received text data using natural language processing (NLP) techniques. This involves language identification, grammatical structure analysis, and extraction of cultural nuances.

[0327] Step 4:

[0328] The server uses an emotion engine to recognize the user's emotions from text data. This process determines what emotions the user is experiencing based on keywords and context.

[0329] Step 5:

[0330] The server estimates the cultural context of the text based on the analysis results. This estimation process takes into account standard communication patterns in different regions and cultures.

[0331] Step 6:

[0332] The server utilizes a generated AI model to consider the estimated cultural background and user emotions, and then performs appropriate translation and interpretation. In this case, the translation selects expressions that reflect the user's emotions.

[0333] Step 7:

[0334] The server takes the user's emotional state into account and suggests a communication style that suits them. For example, it might recommend calm language or a structured approach to alleviate anxiety.

[0335] Step 8:

[0336] The device receives translation results and style suggestions sent from the server and displays them to the user. Based on this, the user engages in optimal communication to accurately convey their intentions.

[0337] (Example 2)

[0338] 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".

[0339] In intercultural communication, misunderstandings and friction arise due to differences in language, cultural nuances, and a lack of emotional transmission. This problem is particularly evident in international business negotiations and multicultural exchanges, where facilitating smoother communication is essential. To address these challenges, an appropriate information transmission method that takes into account cultural backgrounds and user emotions is necessary.

[0340] 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.

[0341] In this invention, the server includes means for analyzing information entered by the user and identifying linguistic characteristics, grammatical structure, and cultural features; means for estimating the cultural context of others based on the analyzed information; and means for determining the user's emotional state using an emotion analysis function. This enables translation and interpretation that takes cultural background and emotions into account, as well as the proposal of appropriate information transmission methods.

[0342] A "user" is an individual or organization that inputs information into a system and utilizes its output.

[0343] "Information" refers to the text and data that users input into the system, which may include business messages and negotiation details.

[0344] "Analysis" is a procedure for processing input information and understanding its structure and content.

[0345] "Language characteristics" refer to grammatical rules and expressions specific to a particular language.

[0346] "Grammar structure" refers to the rules governing the arrangement and relationships of the elements (words and phrases) that make up a text.

[0347] "Cultural characteristics" refer to values, customs, or social norms that are specific to a particular region or group.

[0348] "Estimation" is the process of drawing conclusions with a certain degree of confidence based on incomplete information.

[0349] "Cultural context" refers to the cultural background and current state of affairs within a particular society or group.

[0350] "Sentiment analysis" is a technique that identifies and evaluates emotions based on the context and tone of text data.

[0351] Translation is the act of accurately converting information written in one language into another language.

[0352] "Interpretation" is the process of understanding and explaining the meaning and importance of given information.

[0353] "Information transmission methods" refer to the means and methods for effectively conveying information to others.

[0354] This invention is a system that supports intercultural communication. Users input business documents and messages using their own terminals. This information is first sent from the terminal to a server. The server has powerful data analysis capabilities and uses natural language processing libraries to identify the linguistic characteristics, grammatical structure, and cultural features of the received information.

[0355] The server then uses sentiment analysis technology to determine the emotional state the user is expressing in the text. This allows for the identification of emotions such as joy, anger, and sadness. The analyzed data is processed by a generative AI model, such as a large-scale language model, to estimate the cultural context and provide appropriate translations and interpretations. This entire process adjusts the tone and choice of expressions in the text, enabling communication that takes cultural context and emotions into account.

[0356] Furthermore, the server suggests a communication style suitable for the user. For example, by inputting a prompt sentence such as "Please suggest expressions that will give the user a relaxed impression to their negotiating partner," the AI ​​model can elicit an appropriate response.

[0357] Ultimately, the terminal displays the translation results and suggestions received from the server to the user. Based on this information, the user can engage in smooth and effective cross-cultural communication. This invention is envisioned for use in specific examples such as international business negotiations and multicultural exchanges, and is expected to reduce barriers to information transmission and promote better mutual understanding.

[0358] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0359] Step 1:

[0360] Users input text data, such as work-related documents and messages, using their own devices. This input includes the user's intended message and the emotions they wish to express. The device recognizes this as digital data and prepares it for transmission to the server.

[0361] Step 2:

[0362] The terminal sends the entered text data to the server. During this transmission, a communication protocol (e.g., HTTPS) is used to ensure data integrity and security. This allows the server to receive the data accurately and securely.

[0363] Step 3:

[0364] The server analyzes the received text data using a natural language processing library. Specifically, it processes the data to identify linguistic characteristics, grammatical structure, and cultural features. This analysis outputs the basic structure and contextual information of the text.

[0365] Step 4:

[0366] The server utilizes sentiment analysis capabilities to identify emotions within text. By evaluating the vocabulary and tone of the input text, it identifies the user's emotional state and assigns emotion tags such as joy, anger, and sadness. This provides important output for understanding the emotional nuances within the text.

[0367] Step 5:

[0368] The server inputs the analysis data into an AI model that generates the data, estimates the cultural background, and performs appropriate translation and interpretation. In this process, the AI ​​model considers the cultural context and provides a translation that is adjusted to match the user's emotions. As a result, content that is considerate of culture and emotions is output.

[0369] Step 6:

[0370] The server suggests a communication style that suits the user. Here, based on the results of sentiment analysis, a generative AI model selects appropriate expressions and tones in response to the prompt text and presents them to the user as suggestions.

[0371] Step 7:

[0372] The terminal displays the translation results and suggestions received from the server to the user. Based on this information, the user can confidently engage in cross-cultural communication while utilizing the system's advice.

[0373] (Application Example 2)

[0374] 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."

[0375] In intercultural communication, differing cultural backgrounds and emotional states can lead to misunderstandings, hindering smooth dialogue. Furthermore, interactions within families and multicultural environments tend to be complex, making it challenging to promote mutual understanding.

[0376] 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.

[0377] In this invention, the server includes means for analyzing text information entered by a user, means for estimating the cultural background of others based on the analyzed text information, and means for performing appropriate translation and interpretation while taking into account the estimated cultural background and emotional state. This makes it possible to promote interaction within families and multicultural environments and reduce misunderstandings in intercultural communication.

[0378] "User-input text information" refers to language data entered by users through their devices, intended for the purpose of cross-cultural communication.

[0379] "Means of analysis" refers to the process of understanding and organizing the structure, language, and cultural elements of received text information.

[0380] "Means for estimating the cultural background of others" refers to methods for determining the cultural background of a communication partner based on analyzed data, and for deepening one's understanding of that background.

[0381] "Means of appropriate translation and interpretation" refers to the process of performing translation and interpretation necessary to convey information to others, taking into account not only the meaning of the language but also the culture and emotions involved.

[0382] "Emotional state" refers to the psychological state that a user is experiencing when entering text information, including the type and intensity of the emotions they are feeling at that time.

[0383] "Home and multicultural environments" refer to places where people with diverse cultural backgrounds live together and interact with one another.

[0384] "Promoting communication" refers to initiatives aimed at deepening mutual understanding and exchanging information more smoothly and effectively.

[0385] In the system implementing this invention, the user first inputs their speech or message using a terminal. The server receives this input and first performs language analysis. This process uses software such as the Google Speech-to-Text API or DeepL API to organize the language structure and cultural interpretation based on the input information. After obtaining the analyzed text information, the server then runs a sentiment analysis model using TensorFlow to extract the user's emotional state. This makes it possible to identify whether the user is experiencing any particular emotion.

[0386] The server also has the ability to estimate the cultural background of others based on the analysis results. This utilizes generative AI technology, specifically OpenAI's GPT model, to perform appropriate translations and interpretations that take culture and emotions into account. For example, it can consider the tone of conversation and insert more amiable expressions as needed.

[0387] Finally, the translation results and communication style suggestions are displayed on the device. This enables users to engage in smooth and effective communication within their homes and in multicultural environments.

[0388] As a concrete example, when a guest from France visits a Japanese host family, the robot recognizes the guest's statement, "I'm having a great time today!", and suggests to the host, "It seems our French guest is enjoying themselves. How about we talk about French home cooking next?" This suggestion is generated using a generative AI model with the prompt, "Based on this user's emotions, suggest an appropriate communication style. As a Japanese household robot interacting with a guest from overseas, indicate how you should lead the conversation."

[0389] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0390] Step 1:

[0391] The user inputs text information into the terminal. The input data can be in voice or text format. The terminal sends this input as digital data to the server.

[0392] Step 2:

[0393] The server uses the Google Speech-to-Text API to convert audio data into text. During this process, the input audio data is automatically analyzed and output as text data.

[0394] Step 3:

[0395] The server uses the DeepL API to perform linguistic analysis on text information. From the text received as input data, it extracts the linguistic structure and cultural nuances, reveals the grammatical structure, and outputs it as text data.

[0396] Step 4:

[0397] The server uses a TensorFlow-based sentiment analysis model to extract the emotional state from analyzed text information. Text data is input, and the server outputs the user's emotions (joy, surprise, sadness, etc.) as numerical data.

[0398] Step 5:

[0399] The server uses OpenAI's GPT as its generative AI model to perform translation and interpretation that takes cultural background and emotional states into account. It takes prompt sentences that take emotions and culture into account as input and outputs text that suggests the optimal translation and communication style.

[0400] Step 6:

[0401] Translation results and suggestions are sent from the server to the terminal. The terminal displays the received data to the user, who then engages in smooth communication based on that information. For example, the terminal can select a dialogue based on the displayed suggestions.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] [Third Embodiment]

[0406] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0407] 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.

[0408] 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).

[0409] 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.

[0410] 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.

[0411] 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).

[0412] 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.

[0413] 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.

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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".

[0418] This invention is specifically implemented as a system to support intercultural communication. The initial operation performed by the user is to input text data through a terminal. This could be, for example, an email to a business partner with a different cultural background, or preparation for a presentation at a meeting. The user then uses a dedicated application on the terminal to send the text to the system.

[0419] The terminal sends the input text data to the server, which then analyzes the text using advanced natural language processing (NLP) techniques. During the analysis, the server identifies the language, interprets the grammatical structure, and recognizes subtle nuances between languages ​​and cultures. Based on the information obtained from this analysis, the server estimates the cultural background behind the input text. This estimation of cultural background utilizes cultural knowledge of the target language and its region.

[0420] Furthermore, the server utilizes a generative AI model to translate input text based on its estimated cultural context. This translation includes not only simple semantic conversions but also culturally conscious and appropriate expressions. For example, "a modest expression in accordance with the spirit of the Japanese tea ceremony" might be translated as "a direct and clear expression for an audience from American culture."

[0421] After the translation is complete, the server also suggests communication styles appropriate for different cultural backgrounds to the user. This suggestion is particularly useful in business and public communication to avoid misunderstandings. For example, it may offer suggestions on the use of honorifics and the order of self-introductions.

[0422] Ultimately, the terminal displays the translation results and suggestions sent from the server to the user. Based on these results, the user can then proceed with optimized communication. This system enables smooth communication in international business negotiations and multicultural exchange settings.

[0423] The following describes the processing flow.

[0424] Step 1:

[0425] Users input text data containing what they want to communicate using their device. This includes business emails and presentation scripts.

[0426] Step 2:

[0427] The terminal sends the entered text data to the server. At this stage, metadata such as the user ID and language selection are also sent.

[0428] Step 3:

[0429] The server analyzes the received text data. This includes language identification, grammatical structure analysis, and extraction of specific cultural nuances.

[0430] Step 4:

[0431] The server uses the analysis results to estimate the cultural background behind the input text. This estimation utilizes available database information.

[0432] Step 5:

[0433] The server uses a generated AI model to consider the estimated cultural background and perform appropriate translation and interpretation. In doing so, it selects culturally appropriate expressions.

[0434] Step 6:

[0435] The server suggests a communication style appropriate to the user's estimated cultural background. This includes suggestions for greetings and expressions.

[0436] Step 7:

[0437] The terminal receives the translation results and communication style suggestions sent from the server and displays them to the user.

[0438] Step 8:

[0439] Users review the displayed translation results and suggestions, make adjustments as needed, and communicate effectively with the other party.

[0440] (Example 1)

[0441] 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."

[0442] In intercultural communication, misunderstandings and the use of inappropriate expressions stemming from differences in language and cultural background are problematic. Under these circumstances, ensuring smooth and effective communication is essential in international business transactions, conferences, and multicultural exchanges. Traditional translation methods are limited to simple language conversion, making it difficult to appropriately consider cultural nuances and backgrounds in translation.

[0443] 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.

[0444] In this invention, the server includes means for analyzing user-input data using natural language processing technology to identify linguistic and cultural nuances, means for estimating the other party's cultural characteristics based on the analysis results, and means for performing appropriate translation and interpretation that takes cultural characteristics into account using generative AI technology. This enables smooth intercultural communication.

[0445] "User-input data" refers to information provided by the user via the device, such as text data necessary to support cross-cultural communication.

[0446] A "terminal" is a device used by a user to input data and send it to a server, and includes, for example, computers and smartphones.

[0447] A "server" refers to an information processing device that receives data transmitted from a terminal and performs processing such as analysis, translation, and suggestions.

[0448] "Natural language processing technology" refers to technologies that enable computers to understand and process language data, and includes functions such as language identification, grammatical structure analysis, and nuance recognition.

[0449] "Generative AI technology" refers to techniques that use artificial intelligence to generate data, and specifically to methods used for generating translations and expressions that take cultural characteristics into consideration.

[0450] "Cultural characteristics" refer to cultural elements and background information specific to a language or region, and play an important role in communication.

[0451] "Translation and interpretation" refers to the process of re-expressing text from one language in a way that is appropriate for another language or culture, taking into account not only word-level details but also context and cultural nuances.

[0452] "Communication style" refers to the manner in which information is transmitted between different cultures, including appropriate vocabulary, phrasing, and methods of expression.

[0453] This invention provides a system for effectively supporting intercultural communication. The user uses a terminal to input text data for communication with someone from a specific cultural or linguistic background. The terminal sends this data to a server, which analyzes the received data using natural language processing techniques. This analysis utilizes language models and cultural knowledge databases and includes processes for identifying language, grammatical structures, and cultural nuances.

[0454] The server estimates the cultural characteristics of the input text based on the analysis results. This estimation refers to a database containing pre-prepared cultural data. Furthermore, it utilizes generative AI technology to perform translation and interpretation that takes cultural characteristics into account. The generative AI technology generates appropriate vocabulary and expressions using prompt sentences, and guarantees that the generated translation is culturally sensitive.

[0455] As a concrete example, if a user inputs the polite greeting "Osewa ni natte orimasu" (Thank you for your continued support), which is used in Japanese business settings, the system will translate this into the expression "Hello, I hope you are doing well," which is appropriate for American business settings. In this case, the generation AI model will use the prompt "Translate the following text to an American business context: Osewa ni natte orimasu."

[0456] Ultimately, the translation results and suggested communication style are displayed on the device, allowing the user to communicate effectively. In this way, the present invention contributes to preventing misunderstandings between cultures and facilitating smooth dialogue.

[0457] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0458] Step 1:

[0459] Users input text data for the purpose of cross-cultural communication through a dedicated application on their terminal. This text is used, for example, in business emails or presentations at meetings. The terminal sends the input text data to the server. The output from the terminal is the transmission of text data to the server.

[0460] Step 2:

[0461] The server analyzes text data received from the terminal using natural language processing (NLP) techniques. Based on the text data as input, the server performs language identification, grammatical analysis, and recognition of cultural nuances. This results in outputting linguistic and cultural background information of the text.

[0462] Step 3:

[0463] The server references the analysis data and estimates the cultural characteristics of the subject. To perform this estimation, the server uses a cultural knowledge database. The input is the analysis data of language and cultural background, and the output is the estimated cultural characteristics. This process takes into account culture-specific expressions and customs.

[0464] Step 4:

[0465] The server uses a generative AI model to translate and interpret text based on estimated cultural characteristics. Here, the input is the cultural characteristics, which are used to instruct the generative AI model through prompt sentences. The output is the translated text in a culturally appropriate format.

[0466] Step 5:

[0467] The server provides the user with translation results and suggests appropriate communication styles and expressions for different cultures. These suggestions include hints on specific communication methods, such as the use of honorifics and the order of statements. The input is the translation result, and the output is the suggested communication style.

[0468] Step 6:

[0469] The terminal displays the translation results and suggestions sent from the server to the user. The user can review this and edit it as needed. The terminal's output is the screen display that should be shown to the user. Based on this result, the user can further optimize cross-cultural communication.

[0470] (Application Example 1)

[0471] 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."

[0472] In communication between individuals from different cultural backgrounds, differences in language and cultural nuances can lead to misunderstandings, sometimes resulting in misinterpretations of intended meanings. Furthermore, interactions with multinational customers, particularly at physical sales locations, require prompt and appropriate responses. In these situations, support is needed to enable staff to handle customer interactions efficiently and accurately.

[0473] 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.

[0474] In this invention, the server includes means for analyzing language data entered by a user and identifying linguistic characteristics, grammatical structure, and cultural nuances; means for estimating the recipient's cultural background based on the analyzed language data; and means for performing appropriate translation or interpretation while taking the estimated cultural background into consideration. This enables staff at physical sales locations to more smoothly respond to and communicate with multinational customers.

[0475] A "user" is an individual or group that operates the system and seeks support for culturally appropriate communication.

[0476] "Linguistic data" refers to the content of documents and conversations entered by users, and is the subject of cultural meaning analysis based on this data.

[0477] "Analysis" is the process of understanding the structure and meaning of input linguistic data and identifying the cultural elements behind it.

[0478] "Linguistic characteristics" refer to the unique grammar and expressions of a particular language.

[0479] "Grammar structure" refers to the arrangement and construction of words in a language, and plays an important role in understanding that language.

[0480] "Cultural nuances" refer to the subtle cultural nuances and backgrounds contained within linguistic expressions.

[0481] "Recipient" refers to the person with whom a user communicates.

[0482] "Cultural background" refers to the social, historical, and cultural context that lies behind language and expression.

[0483] Translation refers to the act of changing content expressed in one language into another language, and cultural considerations are essential for accurate transmission.

[0484] "Interpretation" is the act of understanding a language or cultural expression and grasping its meaning.

[0485] A "physical sales location" refers to a physical store or service location where direct customer service and product provision take place.

[0486] "Multinational customers" refer to customers from multiple countries and cultures, who often have different cultural expectations and linguistic backgrounds.

[0487] The implementation of this invention is primarily carried out through data exchange between the user, terminal, and server. The user, acting as a store staff member, uses a terminal such as a smartphone and utilizes the cross-cultural communication support system by inputting information obtained during conversations with customers.

[0488] The terminal sends the input language data to the server, which analyzes this data using advanced natural language processing techniques. In this process, the server identifies linguistic characteristics, grammatical structures, and cultural nuances. Furthermore, based on this, the server estimates the cultural background of the recipient (the customer) and utilizes a generative AI model to perform appropriate translation and interpretation. Translation considers cultural relevance beyond simple language conversion.

[0489] Users receive translations and communication style suggestions from the server on their devices, enabling them to communicate more smoothly with multinational customers. For example, this could be used when staff working at a physical store in Japan instantly translate a Japanese inquiry into a polite English response for a customer from an English-speaking country.

[0490] The server operates via a dedicated application running on portable devices such as smartphones and tablets. The overall system's performance is maximized through the collaboration of natural language processing software and generative AI models.

[0491] An example of a prompt would be: "To facilitate intercultural communication, please generate a response that includes a translation and communication suggestions that take cultural backgrounds into consideration."

[0492] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0493] Step 1:

[0494] The user inputs information obtained from conversations with customers into a dedicated application on their smartphone. The input data is text information, including the content of the conversation and hypotheses about the customer's cultural background. The device receives this data and prepares to send it to the server.

[0495] Step 2:

[0496] The terminal sends the entered text data to the server. The transmitted data is then analyzed on the server using natural language processing techniques. Specifically, it undergoes processing to identify linguistic characteristics, grammatical structures, and cultural nuances. This enables a structural understanding of the data.

[0497] Step 3:

[0498] The server estimates the cultural background of the recipient customer based on the analysis results. This estimation uses a pre-trained cultural information database and a generative AI model. This process involves data computations that compare the characteristics of the input data with known cultural information to identify the appropriate cultural context.

[0499] Step 4:

[0500] The server translates and interprets the input text based on the estimated cultural background. Using a generative AI model, it performs translations that reflect not only the semantic conversion of words but also cultural relevance within the context. The results are generated in a format that is easy for the user to understand.

[0501] Step 5:

[0502] The server sends the translation results and a suggested communication style based on the cultural context to the terminal. In this process, the server selects the most suitable option from the generated text and suggestions, and sends it to the user as practical information.

[0503] Step 6:

[0504] The user's device displays the translation results and suggestions received from the server. Based on the displayed information, the user can respond appropriately to multinational customers. In this way, cross-cultural communication proceeds smoothly.

[0505] 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.

[0506] This invention is implemented as a cross-cultural communication support system that takes user emotions into consideration. This system has a function that recognizes the user's emotions using an emotion engine based on text data entered by the user on a terminal. When a user uses their terminal to input, for example, business emails or negotiation details, that data is sent to the server along with the emotion engine.

[0507] On the server, the received text data is first subjected to linguistic analysis. This includes language identification, grammatical structure analysis, and extraction of cultural nuances. These analyses clarify the context of the text and the user's intent. The sentiment engine also determines whether the user is experiencing any emotion—for example, joy, anger, or sadness—based on the word choice, expressions, and tone of the sentences within the text.

[0508] The analyzed data is then used by a generative AI model to estimate the cultural context, and culturally appropriate translation and interpretation are performed. The translation process here is performed based on adjustments made by the server, particularly taking sentiment recognition into account, and considers both the cultural context and the user's emotional state. For example, if the user is feeling stressed or tense, the translation will reflect a more relaxed tone and considerate expression.

[0509] The server then suggests a communication style that is appropriate for the user. Since the suggestions reflect the emotional state recognized by the emotion engine, the user can choose an appropriate communication method based on their own emotional state.

[0510] Ultimately, the device displays the translation results and suggestions to the user. Based on these results, the user can engage in effective communication that takes emotions into account. For example, in cross-cultural negotiations, the user can communicate confidently while utilizing the system's suggestions to prevent their own tension or anxiety from being conveyed to the other party.

[0511] The following describes the processing flow.

[0512] Step 1:

[0513] The user inputs text data containing emotions using a device. For example, the user might input something like, "I've been feeling anxious about my recent presentations."

[0514] Step 2:

[0515] The terminal sends the entered text data to the server. Metadata, including the user ID and language information, is also sent along with the data.

[0516] Step 3:

[0517] The server analyzes the received text data using natural language processing (NLP) techniques. This involves language identification, grammatical structure analysis, and extraction of cultural nuances.

[0518] Step 4:

[0519] The server uses an emotion engine to recognize the user's emotions from text data. This process determines what emotions the user is experiencing based on keywords and context.

[0520] Step 5:

[0521] The server estimates the cultural context of the text based on the analysis results. This estimation process takes into account standard communication patterns in different regions and cultures.

[0522] Step 6:

[0523] The server utilizes a generated AI model to consider the estimated cultural background and user emotions, and then performs appropriate translation and interpretation. In this case, the translation selects expressions that reflect the user's emotions.

[0524] Step 7:

[0525] The server takes the user's emotional state into account and suggests a communication style that suits them. For example, it might recommend calm language or a structured approach to alleviate anxiety.

[0526] Step 8:

[0527] The device receives translation results and style suggestions sent from the server and displays them to the user. Based on this, the user engages in optimal communication to accurately convey their intentions.

[0528] (Example 2)

[0529] 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."

[0530] In intercultural communication, misunderstandings and friction arise due to differences in language, cultural nuances, and a lack of emotional transmission. This problem is particularly evident in international business negotiations and multicultural exchanges, where facilitating smoother communication is essential. To address these challenges, an appropriate information transmission method that takes into account cultural backgrounds and user emotions is necessary.

[0531] 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.

[0532] In this invention, the server includes means for analyzing information entered by the user and identifying linguistic characteristics, grammatical structure, and cultural features; means for estimating the cultural context of others based on the analyzed information; and means for determining the user's emotional state using an emotion analysis function. This enables translation and interpretation that takes cultural background and emotions into account, as well as the proposal of appropriate information transmission methods.

[0533] A "user" is an individual or organization that inputs information into a system and utilizes its output.

[0534] "Information" refers to the text and data that users input into the system, which may include business messages and negotiation details.

[0535] "Analysis" is a procedure for processing input information and understanding its structure and content.

[0536] "Language characteristics" refer to grammatical rules and expressions specific to a particular language.

[0537] "Grammar structure" refers to the rules governing the arrangement and relationships of the elements (words and phrases) that make up a text.

[0538] "Cultural characteristics" refer to values, customs, or social norms that are specific to a particular region or group.

[0539] "Estimation" is the process of drawing conclusions with a certain degree of confidence based on incomplete information.

[0540] "Cultural context" refers to the cultural background and current state of affairs within a particular society or group.

[0541] "Sentiment analysis" is a technique that identifies and evaluates emotions based on the context and tone of text data.

[0542] Translation is the act of accurately converting information written in one language into another language.

[0543] "Interpretation" is the process of understanding and explaining the meaning and importance of given information.

[0544] "Information transmission methods" refer to the means and methods for effectively conveying information to others.

[0545] This invention is a system that supports intercultural communication. Users input business documents and messages using their own terminals. This information is first sent from the terminal to a server. The server has powerful data analysis capabilities and uses natural language processing libraries to identify the linguistic characteristics, grammatical structure, and cultural features of the received information.

[0546] The server then uses sentiment analysis technology to determine the emotional state the user is expressing in the text. This allows for the identification of emotions such as joy, anger, and sadness. The analyzed data is processed by a generative AI model, such as a large-scale language model, to estimate the cultural context and provide appropriate translations and interpretations. This entire process adjusts the tone and choice of expressions in the text, enabling communication that takes cultural context and emotions into account.

[0547] Furthermore, the server suggests a communication style suitable for the user. For example, by inputting a prompt sentence such as "Please suggest expressions that will give the user a relaxed impression to their negotiating partner," the AI ​​model can elicit an appropriate response.

[0548] Ultimately, the terminal displays the translation results and suggestions received from the server to the user. Based on this information, the user can engage in smooth and effective cross-cultural communication. This invention is envisioned for use in specific examples such as international business negotiations and multicultural exchanges, and is expected to reduce barriers to information transmission and promote better mutual understanding.

[0549] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0550] Step 1:

[0551] Users input text data, such as work-related documents and messages, using their own devices. This input includes the user's intended message and the emotions they wish to express. The device recognizes this as digital data and prepares it for transmission to the server.

[0552] Step 2:

[0553] The terminal sends the entered text data to the server. During this transmission, a communication protocol (e.g., HTTPS) is used to ensure data integrity and security. This allows the server to receive the data accurately and securely.

[0554] Step 3:

[0555] The server analyzes the received text data using a natural language processing library. Specifically, it processes the data to identify linguistic characteristics, grammatical structure, and cultural features. This analysis outputs the basic structure and contextual information of the text.

[0556] Step 4:

[0557] The server utilizes sentiment analysis capabilities to identify emotions within text. By evaluating the vocabulary and tone of the input text, it identifies the user's emotional state and assigns emotion tags such as joy, anger, and sadness. This provides important output for understanding the emotional nuances within the text.

[0558] Step 5:

[0559] The server inputs the analysis data into an AI model that generates the data, estimates the cultural background, and performs appropriate translation and interpretation. In this process, the AI ​​model considers the cultural context and provides a translation that is adjusted to match the user's emotions. As a result, content that is considerate of culture and emotions is output.

[0560] Step 6:

[0561] The server suggests a communication style that suits the user. Here, based on the results of sentiment analysis, a generative AI model selects appropriate expressions and tones in response to the prompt text and presents them to the user as suggestions.

[0562] Step 7:

[0563] The terminal displays the translation results and suggestions received from the server to the user. Based on this information, the user can confidently engage in cross-cultural communication while utilizing the system's advice.

[0564] (Application Example 2)

[0565] 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."

[0566] In intercultural communication, differing cultural backgrounds and emotional states can lead to misunderstandings, hindering smooth dialogue. Furthermore, interactions within families and multicultural environments tend to be complex, making it challenging to promote mutual understanding.

[0567] 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.

[0568] In this invention, the server includes means for analyzing text information entered by a user, means for estimating the cultural background of others based on the analyzed text information, and means for performing appropriate translation and interpretation while taking into account the estimated cultural background and emotional state. This makes it possible to promote interaction within families and multicultural environments and reduce misunderstandings in intercultural communication.

[0569] "User-input text information" refers to language data entered by users through their devices, intended for the purpose of cross-cultural communication.

[0570] "Means of analysis" refers to the process of understanding and organizing the structure, language, and cultural elements of received text information.

[0571] "Means for estimating the cultural background of others" refers to methods for determining the cultural background of a communication partner based on analyzed data, and for deepening one's understanding of that background.

[0572] "Means of appropriate translation and interpretation" refers to the process of performing translation and interpretation necessary to convey information to others, taking into account not only the meaning of the language but also the culture and emotions involved.

[0573] "Emotional state" refers to the psychological state that a user is experiencing when entering text information, including the type and intensity of the emotions they are feeling at that time.

[0574] "Home and multicultural environments" refer to places where people with diverse cultural backgrounds live together and interact with one another.

[0575] "Promoting communication" refers to initiatives aimed at deepening mutual understanding and exchanging information more smoothly and effectively.

[0576] In the system implementing this invention, the user first inputs their speech or message using a terminal. The server receives this input and first performs language analysis. This process uses software such as the Google Speech-to-Text API or DeepL API to organize the language structure and cultural interpretation based on the input information. After obtaining the analyzed text information, the server then runs a sentiment analysis model using TensorFlow to extract the user's emotional state. This makes it possible to identify whether the user is experiencing any particular emotion.

[0577] The server also has the ability to estimate the cultural background of others based on the analysis results. This utilizes generative AI technology, specifically OpenAI's GPT model, to perform appropriate translations and interpretations that take culture and emotions into account. For example, it can consider the tone of conversation and insert more amiable expressions as needed.

[0578] Finally, the translation results and communication style suggestions are displayed on the device. This enables users to engage in smooth and effective communication within their homes and in multicultural environments.

[0579] As a concrete example, when a guest from France visits a Japanese host family, the robot recognizes the guest's statement, "I'm having a great time today!", and suggests to the host, "It seems our French guest is enjoying themselves. How about we talk about French home cooking next?" This suggestion is generated using a generative AI model with the prompt, "Based on this user's emotions, suggest an appropriate communication style. As a Japanese household robot interacting with a guest from overseas, indicate how you should lead the conversation."

[0580] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0581] Step 1:

[0582] The user inputs text information into the terminal. The input data can be in voice or text format. The terminal sends this input as digital data to the server.

[0583] Step 2:

[0584] The server uses the Google Speech-to-Text API to convert audio data into text. During this process, the input audio data is automatically analyzed and output as text data.

[0585] Step 3:

[0586] The server uses the DeepL API to perform linguistic analysis on text information. From the text received as input data, it extracts the linguistic structure and cultural nuances, reveals the grammatical structure, and outputs it as text data.

[0587] Step 4:

[0588] The server uses a TensorFlow-based sentiment analysis model to extract the emotional state from analyzed text information. Text data is input, and the server outputs the user's emotions (joy, surprise, sadness, etc.) as numerical data.

[0589] Step 5:

[0590] The server uses OpenAI's GPT as its generative AI model to perform translation and interpretation that takes cultural background and emotional states into account. It takes prompt sentences that take emotions and culture into account as input and outputs text that suggests the optimal translation and communication style.

[0591] Step 6:

[0592] Translation results and suggestions are sent from the server to the terminal. The terminal displays the received data to the user, who then engages in smooth communication based on that information. For example, the terminal can select a dialogue based on the displayed suggestions.

[0593] 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.

[0594] 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.

[0595] 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.

[0596] [Fourth Embodiment]

[0597] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0598] 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.

[0599] 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).

[0600] 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.

[0601] 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.

[0602] 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).

[0603] 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.

[0604] 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.

[0605] 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.

[0606] 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.

[0607] 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.

[0608] 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.

[0609] 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".

[0610] This invention is specifically implemented as a system to support intercultural communication. The initial operation performed by the user is to input text data through a terminal. This could be, for example, an email to a business partner with a different cultural background, or preparation for a presentation at a meeting. The user then uses a dedicated application on the terminal to send the text to the system.

[0611] The terminal sends the input text data to the server, which then analyzes the text using advanced natural language processing (NLP) techniques. During the analysis, the server identifies the language, interprets the grammatical structure, and recognizes subtle nuances between languages ​​and cultures. Based on the information obtained from this analysis, the server estimates the cultural background behind the input text. This estimation of cultural background utilizes cultural knowledge of the target language and its region.

[0612] Furthermore, the server utilizes a generative AI model to translate input text based on its estimated cultural context. This translation includes not only simple semantic conversions but also culturally conscious and appropriate expressions. For example, "a modest expression in accordance with the spirit of the Japanese tea ceremony" might be translated as "a direct and clear expression for an audience from American culture."

[0613] After the translation is complete, the server also suggests communication styles appropriate for different cultural backgrounds to the user. This suggestion is particularly useful in business and public communication to avoid misunderstandings. For example, it may offer suggestions on the use of honorifics and the order of self-introductions.

[0614] Ultimately, the terminal displays the translation results and suggestions sent from the server to the user. Based on these results, the user can then proceed with optimized communication. This system enables smooth communication in international business negotiations and multicultural exchange settings.

[0615] The following describes the processing flow.

[0616] Step 1:

[0617] Users input text data containing what they want to communicate using their device. This includes business emails and presentation scripts.

[0618] Step 2:

[0619] The terminal sends the entered text data to the server. At this stage, metadata such as the user ID and language selection are also sent.

[0620] Step 3:

[0621] The server analyzes the received text data. This includes language identification, grammatical structure analysis, and extraction of specific cultural nuances.

[0622] Step 4:

[0623] The server uses the analysis results to estimate the cultural background behind the input text. This estimation utilizes available database information.

[0624] Step 5:

[0625] The server uses a generated AI model to consider the estimated cultural background and perform appropriate translation and interpretation. In doing so, it selects culturally appropriate expressions.

[0626] Step 6:

[0627] The server suggests a communication style appropriate to the user's estimated cultural background. This includes suggestions for greetings and expressions.

[0628] Step 7:

[0629] The terminal receives the translation results and communication style suggestions sent from the server and displays them to the user.

[0630] Step 8:

[0631] Users review the displayed translation results and suggestions, make adjustments as needed, and communicate effectively with the other party.

[0632] (Example 1)

[0633] 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".

[0634] In intercultural communication, misunderstandings and the use of inappropriate expressions stemming from differences in language and cultural background are problematic. Under these circumstances, ensuring smooth and effective communication is essential in international business transactions, conferences, and multicultural exchanges. Traditional translation methods are limited to simple language conversion, making it difficult to appropriately consider cultural nuances and backgrounds in translation.

[0635] 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.

[0636] In this invention, the server includes means for analyzing user-input data using natural language processing technology to identify linguistic and cultural nuances, means for estimating the other party's cultural characteristics based on the analysis results, and means for performing appropriate translation and interpretation that takes cultural characteristics into account using generative AI technology. This enables smooth intercultural communication.

[0637] "User-input data" refers to information provided by the user via the device, such as text data necessary to support cross-cultural communication.

[0638] A "terminal" is a device used by a user to input data and send it to a server, and includes, for example, computers and smartphones.

[0639] A "server" refers to an information processing device that receives data transmitted from a terminal and performs processing such as analysis, translation, and suggestions.

[0640] "Natural language processing technology" refers to technologies that enable computers to understand and process language data, and includes functions such as language identification, grammatical structure analysis, and nuance recognition.

[0641] "Generative AI technology" refers to techniques that use artificial intelligence to generate data, and specifically to methods used for generating translations and expressions that take cultural characteristics into consideration.

[0642] "Cultural characteristics" refer to cultural elements and background information specific to a language or region, and play an important role in communication.

[0643] "Translation and interpretation" refers to the process of re-expressing text from one language in a way that is appropriate for another language or culture, taking into account not only word-level details but also context and cultural nuances.

[0644] "Communication style" refers to the manner in which information is transmitted between different cultures, including appropriate vocabulary, phrasing, and methods of expression.

[0645] This invention provides a system for effectively supporting intercultural communication. The user uses a terminal to input text data for communication with someone from a specific cultural or linguistic background. The terminal sends this data to a server, which analyzes the received data using natural language processing techniques. This analysis utilizes language models and cultural knowledge databases and includes processes for identifying language, grammatical structures, and cultural nuances.

[0646] The server estimates the cultural characteristics of the input text based on the analysis results. This estimation refers to a database containing pre-prepared cultural data. Furthermore, it utilizes generative AI technology to perform translation and interpretation that takes cultural characteristics into account. The generative AI technology generates appropriate vocabulary and expressions using prompt sentences, and guarantees that the generated translation is culturally sensitive.

[0647] As a concrete example, if a user inputs the polite greeting "Osewa ni natte orimasu" (Thank you for your continued support), which is used in Japanese business settings, the system will translate this into the expression "Hello, I hope you are doing well," which is appropriate for American business settings. In this case, the generation AI model will use the prompt "Translate the following text to an American business context: Osewa ni natte orimasu."

[0648] Ultimately, the translation results and suggested communication style are displayed on the device, allowing the user to communicate effectively. In this way, the present invention contributes to preventing misunderstandings between cultures and facilitating smooth dialogue.

[0649] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0650] Step 1:

[0651] Users input text data for the purpose of cross-cultural communication through a dedicated application on their terminal. This text is used, for example, in business emails or presentations at meetings. The terminal sends the input text data to the server. The output from the terminal is the transmission of text data to the server.

[0652] Step 2:

[0653] The server analyzes text data received from the terminal using natural language processing (NLP) techniques. Based on the text data as input, the server performs language identification, grammatical analysis, and recognition of cultural nuances. This results in outputting linguistic and cultural background information of the text.

[0654] Step 3:

[0655] The server references the analysis data and estimates the cultural characteristics of the subject. To perform this estimation, the server uses a cultural knowledge database. The input is the analysis data of language and cultural background, and the output is the estimated cultural characteristics. This process takes into account culture-specific expressions and customs.

[0656] Step 4:

[0657] The server uses a generative AI model to translate and interpret text based on estimated cultural characteristics. Here, the input is the cultural characteristics, which are used to instruct the generative AI model through prompt sentences. The output is the translated text in a culturally appropriate format.

[0658] Step 5:

[0659] The server provides the user with translation results and suggests appropriate communication styles and expressions for different cultures. These suggestions include hints on specific communication methods, such as the use of honorifics and the order of statements. The input is the translation result, and the output is the suggested communication style.

[0660] Step 6:

[0661] The terminal displays the translation results and suggestions sent from the server to the user. The user can review this and edit it as needed. The terminal's output is the screen display that should be shown to the user. Based on this result, the user can further optimize cross-cultural communication.

[0662] (Application Example 1)

[0663] 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".

[0664] In communication between individuals from different cultural backgrounds, differences in language and cultural nuances can lead to misunderstandings, sometimes resulting in misinterpretations of intended meanings. Furthermore, interactions with multinational customers, particularly at physical sales locations, require prompt and appropriate responses. In these situations, support is needed to enable staff to handle customer interactions efficiently and accurately.

[0665] 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.

[0666] In this invention, the server includes means for analyzing language data entered by a user and identifying linguistic characteristics, grammatical structure, and cultural nuances; means for estimating the recipient's cultural background based on the analyzed language data; and means for performing appropriate translation or interpretation while taking the estimated cultural background into consideration. This enables staff at physical sales locations to more smoothly respond to and communicate with multinational customers.

[0667] A "user" is an individual or group that operates the system and seeks support for culturally appropriate communication.

[0668] "Linguistic data" refers to the content of documents and conversations entered by users, and is the subject of cultural meaning analysis based on this data.

[0669] "Analysis" is the process of understanding the structure and meaning of input linguistic data and identifying the cultural elements behind it.

[0670] "Linguistic characteristics" refer to the unique grammar and expressions of a particular language.

[0671] "Grammar structure" refers to the arrangement and construction of words in a language, and plays an important role in understanding that language.

[0672] "Cultural nuances" refer to the subtle cultural nuances and backgrounds contained within linguistic expressions.

[0673] "Recipient" refers to the person with whom a user communicates.

[0674] "Cultural background" refers to the social, historical, and cultural context that lies behind language and expression.

[0675] Translation refers to the act of changing content expressed in one language into another language, and cultural considerations are essential for accurate transmission.

[0676] "Interpretation" is the act of understanding a language or cultural expression and grasping its meaning.

[0677] A "physical sales location" refers to a physical store or service location where direct customer service and product provision take place.

[0678] "Multinational customers" refer to customers from multiple countries and cultures, who often have different cultural expectations and linguistic backgrounds.

[0679] The implementation of this invention is primarily carried out through data exchange between the user, terminal, and server. The user, acting as a store staff member, uses a terminal such as a smartphone and utilizes the cross-cultural communication support system by inputting information obtained during conversations with customers.

[0680] The terminal sends the input language data to the server, which analyzes this data using advanced natural language processing techniques. In this process, the server identifies linguistic characteristics, grammatical structures, and cultural nuances. Furthermore, based on this, the server estimates the cultural background of the recipient (the customer) and utilizes a generative AI model to perform appropriate translation and interpretation. Translation considers cultural relevance beyond simple language conversion.

[0681] Users receive translations and communication style suggestions from the server on their devices, enabling them to communicate more smoothly with multinational customers. For example, this could be used when staff working at a physical store in Japan instantly translate a Japanese inquiry into a polite English response for a customer from an English-speaking country.

[0682] The server operates via a dedicated application running on portable devices such as smartphones and tablets. The overall system's performance is maximized through the collaboration of natural language processing software and generative AI models.

[0683] An example of a prompt would be: "To facilitate intercultural communication, please generate a response that includes a translation and communication suggestions that take cultural backgrounds into consideration."

[0684] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0685] Step 1:

[0686] The user inputs information obtained from conversations with customers into a dedicated application on their smartphone. The input data is text information, including the content of the conversation and hypotheses about the customer's cultural background. The device receives this data and prepares to send it to the server.

[0687] Step 2:

[0688] The terminal sends the entered text data to the server. The transmitted data is then analyzed on the server using natural language processing techniques. Specifically, it undergoes processing to identify linguistic characteristics, grammatical structures, and cultural nuances. This enables a structural understanding of the data.

[0689] Step 3:

[0690] The server estimates the cultural background of the recipient customer based on the analysis results. This estimation uses a pre-trained cultural information database and a generative AI model. This process involves data computations that compare the characteristics of the input data with known cultural information to identify the appropriate cultural context.

[0691] Step 4:

[0692] The server translates and interprets the input text based on the estimated cultural background. Using a generative AI model, it performs translations that reflect not only the semantic conversion of words but also cultural relevance within the context. The results are generated in a format that is easy for the user to understand.

[0693] Step 5:

[0694] The server sends the translation results and a suggested communication style based on the cultural context to the terminal. In this process, the server selects the most suitable option from the generated text and suggestions, and sends it to the user as practical information.

[0695] Step 6:

[0696] The user's device displays the translation results and suggestions received from the server. Based on the displayed information, the user can respond appropriately to multinational customers. In this way, cross-cultural communication proceeds smoothly.

[0697] 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.

[0698] This invention is implemented as a cross-cultural communication support system that takes user emotions into consideration. This system has a function that recognizes the user's emotions using an emotion engine based on text data entered by the user on a terminal. When a user uses their terminal to input, for example, business emails or negotiation details, that data is sent to the server along with the emotion engine.

[0699] On the server, the received text data is first subjected to linguistic analysis. This includes language identification, grammatical structure analysis, and extraction of cultural nuances. These analyses clarify the context of the text and the user's intent. The sentiment engine also determines whether the user is experiencing any emotion—for example, joy, anger, or sadness—based on the word choice, expressions, and tone of the sentences within the text.

[0700] The analyzed data is then used by a generative AI model to estimate the cultural context, and culturally appropriate translation and interpretation are performed. The translation process here is performed based on adjustments made by the server, particularly taking sentiment recognition into account, and considers both the cultural context and the user's emotional state. For example, if the user is feeling stressed or tense, the translation will reflect a more relaxed tone and considerate expression.

[0701] The server then suggests a communication style that is appropriate for the user. Since the suggestions reflect the emotional state recognized by the emotion engine, the user can choose an appropriate communication method based on their own emotional state.

[0702] Ultimately, the device displays the translation results and suggestions to the user. Based on these results, the user can engage in effective communication that takes emotions into account. For example, in cross-cultural negotiations, the user can communicate confidently while utilizing the system's suggestions to prevent their own tension or anxiety from being conveyed to the other party.

[0703] The following describes the processing flow.

[0704] Step 1:

[0705] The user inputs text data containing emotions using a device. For example, the user might input something like, "I've been feeling anxious about my recent presentations."

[0706] Step 2:

[0707] The terminal sends the entered text data to the server. Metadata, including the user ID and language information, is also sent along with the data.

[0708] Step 3:

[0709] The server analyzes the received text data using natural language processing (NLP) techniques. This involves language identification, grammatical structure analysis, and extraction of cultural nuances.

[0710] Step 4:

[0711] The server uses an emotion engine to recognize the user's emotions from text data. This process determines what emotions the user is experiencing based on keywords and context.

[0712] Step 5:

[0713] The server estimates the cultural context of the text based on the analysis results. This estimation process takes into account standard communication patterns in different regions and cultures.

[0714] Step 6:

[0715] The server utilizes a generated AI model to consider the estimated cultural background and user emotions, and then performs appropriate translation and interpretation. In this case, the translation selects expressions that reflect the user's emotions.

[0716] Step 7:

[0717] The server takes the user's emotional state into account and suggests a communication style that suits them. For example, it might recommend calm language or a structured approach to alleviate anxiety.

[0718] Step 8:

[0719] The device receives translation results and style suggestions sent from the server and displays them to the user. Based on this, the user engages in optimal communication to accurately convey their intentions.

[0720] (Example 2)

[0721] 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".

[0722] In intercultural communication, misunderstandings and friction arise due to differences in language, cultural nuances, and a lack of emotional transmission. This problem is particularly evident in international business negotiations and multicultural exchanges, where facilitating smoother communication is essential. To address these challenges, an appropriate information transmission method that takes into account cultural backgrounds and user emotions is necessary.

[0723] 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.

[0724] In this invention, the server includes means for analyzing information entered by the user and identifying linguistic characteristics, grammatical structure, and cultural features; means for estimating the cultural context of others based on the analyzed information; and means for determining the user's emotional state using an emotion analysis function. This enables translation and interpretation that takes cultural background and emotions into account, as well as the proposal of appropriate information transmission methods.

[0725] A "user" is an individual or organization that inputs information into a system and utilizes its output.

[0726] "Information" refers to the text and data that users input into the system, which may include business messages and negotiation details.

[0727] "Analysis" is a procedure for processing input information and understanding its structure and content.

[0728] "Language characteristics" refer to grammatical rules and expressions specific to a particular language.

[0729] "Grammar structure" refers to the rules governing the arrangement and relationships of the elements (words and phrases) that make up a text.

[0730] "Cultural characteristics" refer to values, customs, or social norms that are specific to a particular region or group.

[0731] "Estimation" is the process of drawing conclusions with a certain degree of confidence based on incomplete information.

[0732] "Cultural context" refers to the cultural background and current state of affairs within a particular society or group.

[0733] "Sentiment analysis" is a technique that identifies and evaluates emotions based on the context and tone of text data.

[0734] Translation is the act of accurately converting information written in one language into another language.

[0735] "Interpretation" is the process of understanding and explaining the meaning and importance of given information.

[0736] "Information transmission methods" refer to the means and methods for effectively conveying information to others.

[0737] This invention is a system that supports intercultural communication. Users input business documents and messages using their own terminals. This information is first sent from the terminal to a server. The server has powerful data analysis capabilities and uses natural language processing libraries to identify the linguistic characteristics, grammatical structure, and cultural features of the received information.

[0738] The server then uses sentiment analysis technology to determine the emotional state the user is expressing in the text. This allows for the identification of emotions such as joy, anger, and sadness. The analyzed data is processed by a generative AI model, such as a large-scale language model, to estimate the cultural context and provide appropriate translations and interpretations. This entire process adjusts the tone and choice of expressions in the text, enabling communication that takes cultural context and emotions into account.

[0739] Furthermore, the server suggests a communication style suitable for the user. For example, by inputting a prompt sentence such as "Please suggest expressions that will give the user a relaxed impression to their negotiating partner," the AI ​​model can elicit an appropriate response.

[0740] Ultimately, the terminal displays the translation results and suggestions received from the server to the user. Based on this information, the user can engage in smooth and effective cross-cultural communication. This invention is envisioned for use in specific examples such as international business negotiations and multicultural exchanges, and is expected to reduce barriers to information transmission and promote better mutual understanding.

[0741] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0742] Step 1:

[0743] Users input text data, such as work-related documents and messages, using their own devices. This input includes the user's intended message and the emotions they wish to express. The device recognizes this as digital data and prepares it for transmission to the server.

[0744] Step 2:

[0745] The terminal sends the entered text data to the server. During this transmission, a communication protocol (e.g., HTTPS) is used to ensure data integrity and security. This allows the server to receive the data accurately and securely.

[0746] Step 3:

[0747] The server analyzes the received text data using a natural language processing library. Specifically, it processes the data to identify linguistic characteristics, grammatical structure, and cultural features. This analysis outputs the basic structure and contextual information of the text.

[0748] Step 4:

[0749] The server utilizes sentiment analysis capabilities to identify emotions within text. By evaluating the vocabulary and tone of the input text, it identifies the user's emotional state and assigns emotion tags such as joy, anger, and sadness. This provides important output for understanding the emotional nuances within the text.

[0750] Step 5:

[0751] The server inputs the analysis data into an AI model that generates the data, estimates the cultural background, and performs appropriate translation and interpretation. In this process, the AI ​​model considers the cultural context and provides a translation that is adjusted to match the user's emotions. As a result, content that is considerate of culture and emotions is output.

[0752] Step 6:

[0753] The server suggests a communication style that suits the user. Here, based on the results of sentiment analysis, a generative AI model selects appropriate expressions and tones in response to the prompt text and presents them to the user as suggestions.

[0754] Step 7:

[0755] The terminal displays the translation results and suggestions received from the server to the user. Based on this information, the user can confidently engage in cross-cultural communication while utilizing the system's advice.

[0756] (Application Example 2)

[0757] 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".

[0758] In intercultural communication, differing cultural backgrounds and emotional states can lead to misunderstandings, hindering smooth dialogue. Furthermore, interactions within families and multicultural environments tend to be complex, making it challenging to promote mutual understanding.

[0759] 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.

[0760] In this invention, the server includes means for analyzing text information entered by a user, means for estimating the cultural background of others based on the analyzed text information, and means for performing appropriate translation and interpretation while taking into account the estimated cultural background and emotional state. This makes it possible to promote interaction within families and multicultural environments and reduce misunderstandings in intercultural communication.

[0761] "User-input text information" refers to language data entered by users through their devices, intended for the purpose of cross-cultural communication.

[0762] "Means of analysis" refers to the process of understanding and organizing the structure, language, and cultural elements of received text information.

[0763] "Means for estimating the cultural background of others" refers to methods for determining the cultural background of a communication partner based on analyzed data, and for deepening one's understanding of that background.

[0764] "Means of appropriate translation and interpretation" refers to the process of performing translation and interpretation necessary to convey information to others, taking into account not only the meaning of the language but also the culture and emotions involved.

[0765] "Emotional state" refers to the psychological state that a user is experiencing when entering text information, including the type and intensity of the emotions they are feeling at that time.

[0766] "Home and multicultural environments" refer to places where people with diverse cultural backgrounds live together and interact with one another.

[0767] "Promoting communication" refers to initiatives aimed at deepening mutual understanding and exchanging information more smoothly and effectively.

[0768] In the system implementing this invention, the user first inputs their speech or message using a terminal. The server receives this input and first performs language analysis. This process uses software such as the Google Speech-to-Text API or DeepL API to organize the language structure and cultural interpretation based on the input information. After obtaining the analyzed text information, the server then runs a sentiment analysis model using TensorFlow to extract the user's emotional state. This makes it possible to identify whether the user is experiencing any particular emotion.

[0769] The server also has the ability to estimate the cultural background of others based on the analysis results. This utilizes generative AI technology, specifically OpenAI's GPT model, to perform appropriate translations and interpretations that take culture and emotions into account. For example, it can consider the tone of conversation and insert more amiable expressions as needed.

[0770] Finally, the translation results and communication style suggestions are displayed on the device. This enables users to engage in smooth and effective communication within their homes and in multicultural environments.

[0771] As a concrete example, when a guest from France visits a Japanese host family, the robot recognizes the guest's statement, "I'm having a great time today!", and suggests to the host, "It seems our French guest is enjoying themselves. How about we talk about French home cooking next?" This suggestion is generated using a generative AI model with the prompt, "Based on this user's emotions, suggest an appropriate communication style. As a Japanese household robot interacting with a guest from overseas, indicate how you should lead the conversation."

[0772] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0773] Step 1:

[0774] The user inputs text information into the terminal. The input data can be in voice or text format. The terminal sends this input as digital data to the server.

[0775] Step 2:

[0776] The server uses the Google Speech-to-Text API to convert audio data into text. During this process, the input audio data is automatically analyzed and output as text data.

[0777] Step 3:

[0778] The server uses the DeepL API to perform linguistic analysis on text information. From the text received as input data, it extracts the linguistic structure and cultural nuances, reveals the grammatical structure, and outputs it as text data.

[0779] Step 4:

[0780] The server uses a TensorFlow-based sentiment analysis model to extract the emotional state from analyzed text information. Text data is input, and the server outputs the user's emotions (joy, surprise, sadness, etc.) as numerical data.

[0781] Step 5:

[0782] The server uses OpenAI's GPT as its generative AI model to perform translation and interpretation that takes cultural background and emotional states into account. It takes prompt sentences that take emotions and culture into account as input and outputs text that suggests the optimal translation and communication style.

[0783] Step 6:

[0784] Translation results and suggestions are sent from the server to the terminal. The terminal displays the received data to the user, who then engages in smooth communication based on that information. For example, the terminal can select a dialogue based on the displayed suggestions.

[0785] 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.

[0786] 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.

[0787] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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."

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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 this memory.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] The following is further disclosed regarding the embodiments described above.

[0807] (Claim 1)

[0808] A means of analyzing user-inputted text data to identify language, grammatical structure, and cultural nuances,

[0809] A means of estimating the cultural background of the other party based on analyzed text data,

[0810] Taking into account the estimated cultural background, means of performing appropriate translation and interpretation,

[0811] A means of proposing appropriate communication styles and methods of expression to users,

[0812] A means of displaying the results to the user,

[0813] A system that includes this.

[0814] (Claim 2)

[0815] The system according to claim 1, which uses generative AI technology to perform translation and interpretation that takes cultural background into consideration.

[0816] (Claim 3)

[0817] The system according to claim 1, which aims to facilitate communication in international business negotiations and multicultural exchange settings.

[0818] "Example 1"

[0819] (Claim 1)

[0820] A means of receiving data entered by the user via a terminal and sending it to a server,

[0821] A means of analyzing data received by a server using natural language processing technology to identify language, grammatical structure, and cultural nuances,

[0822] Based on the analysis results, a means to estimate the cultural characteristics of the other party,

[0823] A means of performing appropriate translation and interpretation, taking into account estimated cultural characteristics using generative AI technology,

[0824] Along with the translation results, we offer methods for suggesting communication styles and methods of expression.

[0825] Means for displaying this information to the user,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, which uses generative AI technology to utilize prompt sentences and provides appropriate translation and expression methods that take cultural characteristics into consideration.

[0829] (Claim 3)

[0830] The system according to claim 1, which aims to improve intercultural communication and facilitate international trade and cultural exchange.

[0831] "Application Example 1"

[0832] (Claim 1)

[0833] A means of analyzing user-inputted language data to identify linguistic characteristics, grammatical structures, and cultural nuances,

[0834] A means of estimating the recipient's cultural background based on analyzed linguistic data,

[0835] Taking into account the estimated cultural background, means of performing appropriate translation and interpretation,

[0836] As a means of addressing individual work environments, we propose appropriate communication styles and methods of expression to users,

[0837] A means of displaying the results to the user,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, which uses generative AI technology to perform translation and interpretation that takes into account the cultural background of individual work environments.

[0841] (Claim 3)

[0842] The system according to claim 1, which aims to overcome linguistic differences between employees and multinational customers at physical sales locations.

[0843] "Example 2 of combining an emotion engine"

[0844] (Claim 1)

[0845] A device that analyzes information entered by the user and identifies linguistic characteristics, grammatical structure, and cultural features,

[0846] A device that estimates the cultural situation of others based on the analyzed information,

[0847] A device that performs appropriate translation and interpretation, taking into account the estimated cultural context,

[0848] A device that proposes suitable information transmission methods and expression methods to users,

[0849] A device that uses emotion analysis functionality to determine the user's emotional state,

[0850] A device that displays the results to the user,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, which uses generation technology to perform translation and interpretation that takes cultural context into account.

[0854] (Claim 3)

[0855] The system according to claim 1, which aims to facilitate information exchange in international business negotiations and multicultural exchange settings.

[0856] "Application example 2 when combining with an emotional engine"

[0857] (Claim 1)

[0858] A means of analyzing text information entered by a user to identify language, grammatical structure, and cultural interpretation,

[0859] A means of estimating the cultural background of others based on analyzed text information,

[0860] Taking into account the estimated cultural background and emotional state, means of performing appropriate translation and interpretation,

[0861] A means of proposing communication styles and methods of expression that are suitable for the user,

[0862] Means to support dialogue in order to promote interaction within the family and in multicultural environments,

[0863] A means of displaying the results to the user,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, which uses generative AI technology to perform translation and interpretation that takes into account cultural background and emotional state.

[0867] (Claim 3)

[0868] The system according to claim 1, which aims to facilitate mutual exchange and understanding in a multicultural environment. [Explanation of Symbols]

[0869] 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 analyzing user-inputted text data to identify language, grammatical structure, and cultural nuances, A means of estimating the cultural background of the other party based on analyzed text data, Taking into account the estimated cultural background, means of performing appropriate translation and interpretation, A means of proposing appropriate communication styles and methods of expression to users, A means of displaying the results to the user, A system that includes this.

2. The system according to claim 1, which uses generative AI technology to perform translation and interpretation that takes cultural background into consideration.

3. The system according to claim 1, which aims to facilitate communication in international business negotiations and multicultural exchange settings.

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