system

Abstract

We provide the system. [Solution] To support intercultural communication, Means of collecting information about different cultures, A means of understanding cultural background by analyzing user input using natural language processing technology, A means of generating an appropriate communication strategy based on the analysis results, A means of presenting the generated strategy to the user, Means for optimizing audio guidance based on the cultural background of passengers, 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] Communication between people with different cultural backgrounds can easily be hindered by cultural misunderstandings and misrecognitions. Such situations can particularly impede the progress of projects in business and international communication scenarios and may have an adverse impact on the relationship between both parties. The present invention aims to prevent such troubles caused by cultural misunderstandings.

Means for Solving the Problems

[0005] The intercultural communication support system according to the present invention has means for collecting information on different cultures and analyzing user input using natural language processing technology. Furthermore, it includes means for generating and presenting appropriate communication strategies based on the analysis results, thereby supporting users in engaging in appropriate communication. In addition, it provides feedback on the communication actions taken by the user and enables the construction and updating of a knowledge base to promote intercultural understanding, thereby preventing cultural misunderstandings.

[0006] "Intercultural communication" is the process by which people from different cultural backgrounds exchange information and feelings.

[0007] "Cultural background" is a concept that refers to the values, beliefs, and patterns of behavior rooted in the culture to which an individual or group belongs.

[0008] "Natural language processing technology" is the technology that allows computers to understand, interpret, and generate human language.

[0009] "Analysis" is the process of breaking down complex information or data into its elements and understanding their meaning.

[0010] A "communication strategy" is a plan and method for effectively disseminating information according to a specific purpose.

[0011] "Feedback" is the process of providing evaluations or reactions to actions or results.

[0012] A "knowledge base" is a database in which specific information and knowledge are systematically organized and accessible. [Brief explanation of the drawing]

[0013] [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]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] 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 one 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.

[0017] 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.

[0018] 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, etc.

[0019] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] The intercultural communication support system according to the present invention is a system based on the collection of intercultural information and the analysis of user input, and is implemented as follows.

[0035] The server collects vast amounts of information about different cultures from the internet and specialized databases to build a cultural knowledge base. This knowledge base includes common customs, business etiquette, and communication styles to be aware of in different cultural spheres.

[0036] The user accesses the system using a terminal and inputs information about their own cultural background and the cultural background of the person they wish to communicate with into the server. The terminal receives the input from the user and sends it to the server.

[0037] The server analyzes the received user input using natural language processing technology to understand the user's intentions and emotions. Based on this, the server identifies potential challenges related to cross-cultural communication, references relevant information from its knowledge base, and generates the optimal communication strategy for the user.

[0038] The terminal receives suggestions from the server and presents them to the user visually or audibly. Based on this information, the user can choose appropriate actions and engage in cross-cultural communication.

[0039] As a concrete example, consider a business meeting between a Japanese company and a British company. The user inputs a request via their device to review basic business etiquette related to Japanese culture. The server uses natural language processing technology to analyze the user's input and provides information about how to show respect and the importance of exchanging business cards in Japanese business culture. This information is presented to the user via their device, enabling them to adopt appropriate attitudes and behaviors during the meeting.

[0040] Furthermore, after the meeting, the device can display feedback on the user's communication behavior and suggest areas for improvement and success stories for the next meeting, thereby continuously improving the user's cross-cultural understanding.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The server collects information about different cultures from the internet and specialized databases, and stores it as a cultural knowledge base. This knowledge base includes information on cultural customs, business etiquette, and communication styles from around the world.

[0044] Step 2:

[0045] Users access the system through a terminal. The terminal provides an interface that receives questions from the user regarding communication methods based on the other party's culture and specific situations.

[0046] Step 3:

[0047] The device sends the user's question to the server. The question includes information about the user's cultural background and the cultural background of the person they wish to communicate with.

[0048] Step 4:

[0049] The server receives user input data sent from the terminal and analyzes its content using natural language processing technology. This allows it to identify the user's intentions and emotions, and pinpoint communication challenges in light of their cultural background.

[0050] Step 5:

[0051] The server extracts relevant information from its knowledge base based on the analysis results and generates an optimal communication strategy for the user. This strategy includes specific language choices and guidelines for action.

[0052] Step 6:

[0053] The server sends the generated communication strategy to the terminal. The terminal presents this proposal to the user visually or audibly.

[0054] Step 7:

[0055] Users refer to the information presented on their devices and take appropriate actions in real-world communication scenarios.

[0056] Step 8:

[0057] After the conversation ends, the device provides feedback based on the user's choices and actions. This feedback includes successes and areas for improvement, serving as guidance for future communication.

[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, it is essential to mitigate misunderstandings and friction arising from differences in cultural backgrounds. However, traditional methods have struggled to efficiently collect and analyze detailed information about each culture, resulting in a lack of timely provision of concrete strategies for users to facilitate smooth intercultural communication.

[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 collecting information on different cultures from a global information network and specialized information sources, means for forming a cultural knowledge base based on the collected information, means for using natural language processing technology to receive and analyze user information, and means for presenting the generated dialogue strategy to the user visually or audibly. This enables the user to obtain an effective cross-cultural communication strategy.

[0063] "Information about different cultures" is a general term encompassing customs, social norms, business etiquette, and communication styles related to diverse cultures around the world.

[0064] A "global information network" refers to a globally accessible information network that utilizes the internet.

[0065] A "specialized information source" refers to a reliable source that provides highly specialized knowledge and data on a particular field or topic.

[0066] A "cultural knowledge base" is a structured collection of knowledge generated from collected culture-related information, which is used to support intercultural understanding.

[0067] A "user" is an individual or organization that inputs information and receives results through an intercultural communication support system.

[0068] "Natural language processing technology" is a technology that uses computers to process and analyze human language in order to understand its meaning.

[0069] A "generative model" refers to an algorithm that automatically generates dialogue strategies and information based on input data.

[0070] A "dialogue strategy" refers to a set of planned guidelines and methods for effectively conducting communication with a specific purpose.

[0071] "Means of visual or auditory presentation" refers to methods of providing information to users in a form that they can see or hear through displays, speakers, etc.

[0072] The intercultural communication support system according to the present invention is specifically implemented based on the collection of intercultural information and the analysis of user input. The embodiments of this system are described in detail below.

[0073] The server collects information on different cultures from a global information network and specialized information sources. Specifically, it can obtain culture-related data using, for example, a web scraping program developed in Python. Based on the collected data, this server forms a cultural knowledge base and stores it in a MySQL® database, thereby building a vast information resource for intercultural understanding.

[0074] Users access the system through their terminal and input information about their own cultural background and the cultural background of the other party. This input information is provided in text format, for example, in a form on a web browser, such as "I come from an Asian cultural background and I am collaborating with European partners." The terminal sends the acquired user input information to the server, where it is processed.

[0075] The server uses natural language processing techniques to process the received input information. This process utilizes natural language processing libraries such as spaCy and Transformers to analyze the user's intent and emotions. Furthermore, a generative AI model generates the optimal communication strategy for the user. This ensures that the user receives specific and appropriate cultural characteristics and advice to be mindful of during interactions.

[0076] The generated communication strategy is presented to the user visually or audibly via the device. For example, the display might show information such as, "In European business meetings, direct and clear communication is preferred." Users can use this information to facilitate smooth communication across cultures.

[0077] As a concrete example, in a business meeting between a Japanese company and a British company, the user enters a prompt message via their terminal saying, "I would like to learn about British business etiquette." In response, the server generates a strategy such as, "In British culture, prior confirmation via email is important, and limited body language is recommended during conversations," and presents it to the user. In this way, the present invention effectively supports the user's cross-cultural adaptation and successful communication.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The server collects information about different cultures from global information networks such as the internet and specialized information sources. This information includes the unique customs and communication styles of each cultural sphere. This collection utilizes web scraping techniques, and sometimes data is obtained from APIs. The input is keywords related to a specific culture, and the output is raw data to form a cultural knowledge base.

[0081] Step 2:

[0082] The server analyzes the collected raw data and builds a cultural knowledge base. Specifically, it uses database software to classify the collected data by cultural area and extracts cultural features and patterns by performing text mining as needed. The input is raw data, and the output is a structured knowledge base.

[0083] Step 3:

[0084] Users input information about their own cultural background and the cultural background of the other party through their device. This is usually entered in text format into a web form. This information indicates the user's intentions and the background of the communication they seek, and the device sends this input to the server. The input is the user's cultural background information, and the output is data prepared for natural language processing.

[0085] Step 4:

[0086] The server analyzes the received user information using natural language processing techniques. Here, existing libraries (e.g., spaCy and Transformers) are used to understand the user's intent and sentiment in relation to the input text. The input is the text sent by the user, and the output is the analyzed intent and sentiment data.

[0087] Step 5:

[0088] The server utilizes a generative AI model based on user intent and sentiment data to generate appropriate communication strategies. This generation process combines predictive algorithms with information from a knowledge base to derive specific action guidelines and advice. The input is analyzed intent and sentiment data, and the output is a specific communication strategy.

[0089] Step 6:

[0090] The terminal presents the communication strategy received from the server to the user visually or audibly. This is achieved by displaying information on a screen or by using speech synthesis to read the content aloud. The input is the generated communication strategy, and the output is the information presented to the user visually or audibly.

[0091] Step 7:

[0092] Users engage in cross-cultural communication based on communication strategies presented by the system. They then provide feedback on their communication through the device. The input is feedback based on the user's real-world experience, and the output is used to identify areas for improvement and identify success stories for future interactions.

[0093] (Application Example 1)

[0094] 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."

[0095] In situations requiring intercultural communication, interactions between individuals with different cultural backgrounds can sometimes lead to insufficient understanding or misunderstandings. Therefore, there is a need for systems that support smoother and more accurate communication. In particular, in autonomous vehicles, providing guidance and information tailored to the cultural backgrounds of passengers is a challenge.

[0096] 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.

[0097] In this invention, the server includes means for collecting information about different cultures, means for analyzing user input using natural language processing technology to understand the cultural background, and means for generating an appropriate communication strategy based on the analysis results. This makes it possible to optimize voice guidance in autonomous vehicles while taking into account different cultural backgrounds.

[0098] "Information about different cultures" is a general term encompassing customs, values, and communication styles in different cultural spheres.

[0099] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0100] "Cultural background" refers to the characteristics and historical influences of the culture to which individuals belong.

[0101] A "communication strategy" refers to the methods of contact and information transmission established to facilitate smooth intercultural exchange.

[0102] "Optimizing voice guidance" means providing optimal voice guidance tailored to the characteristics of the user and the environment.

[0103] A "knowledge base" is a database that structurally organizes information and data, and aggregates knowledge related to a specific field.

[0104] The system for realizing this invention optimizes voice guidance within an autonomous vehicle according to the cultural background of the passengers, in order to support intercultural communication.

[0105] The server collects information on different cultures from the internet and specialized databases to build a cultural knowledge base. Using a natural language processing engine (e.g., Google® Cloud Natural Language API), it analyzes the user's voice input to understand their intent and emotions. Based on the analyzed information, the server generates an appropriate communication strategy and optimizes voice guidance. The generated guidance is presented to passengers via the in-vehicle computer through displays and voice systems.

[0106] The terminal uses a voice recognition microphone to receive cultural background information and navigation needs entered by the user via voice. This input is sent to a server for analysis.

[0107] As a concrete example, if a Japanese tourist boards an autonomous vehicle in an international tourist destination, this system can provide audio guidance about local cultural customs and tourist attractions. This allows passengers to enjoy a comfortable and easy-to-understand navigation experience.

[0108] An example of a prompt sentence for a generative AI model is, "The passenger on the train is from Japan. Please provide helpful cultural advice for this country."

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The device receives voice input from the user using a voice recognition microphone. This input includes the user's cultural background information and navigation preferences. The device converts this voice into a digital signal and sends it to the server.

[0112] Step 2:

[0113] The server analyzes the received digital audio signal using a natural language processing engine and converts it into text data. This provides information to understand the user's intent, emotions, and cultural background. The analyzed text data is then compared with a knowledge base.

[0114] Step 3:

[0115] The server references a knowledge base and generates an appropriate communication strategy based on the user's cultural background. This strategy includes information on cultural etiquette and tourist information. A generative AI model is used to formulate specific guidance content.

[0116] Step 4:

[0117] The server determines the content of the voice guidance based on the generated communication strategy and generates digital voice data. This data is output as guidance information via the in-vehicle computer.

[0118] Step 5:

[0119] The terminal provides passengers with voice guidance through the vehicle's speaker system. Through this voice guidance, users can receive appropriate cultural and tourist information, allowing them to travel to their destination with peace of mind.

[0120] 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.

[0121] The intercultural communication support system according to the present invention achieves advanced communication support that takes emotional elements into consideration by combining it with an emotion engine. An embodiment thereof is shown below.

[0122] The server first comprehensively collects information about different cultures to form a cultural knowledge base. This knowledge base structures detailed information about common misunderstandings that occur between cultures and culture-specific communication styles. Meanwhile, an emotion engine is built into the system to appropriately analyze the user's emotional state.

[0123] The user connects to the system via a terminal. The terminal transmits not only user input information but also non-verbal cues such as voice and facial expressions using the camera and microphone to the emotion engine. This process allows the user to receive appropriate support even in situations involving emotions such as anxiety, tension, or joy.

[0124] The server uses natural language processing technology to analyze information received from users, performing sentiment analysis in parallel with understanding the cultural background. Specifically, it derives communication strategies that match the user's emotional state from a knowledge base and generates optimal suggestions that take into account the cultural background and emotional state.

[0125] The terminal receives instructions from the server and presents the user with an appropriate communication strategy. Here, it can provide feedback that aligns with the user's emotions, creating a sense of security while assisting in problem-solving.

[0126] As a concrete example, consider a scenario where a Japanese company and a French company are conducting business negotiations. When a user finds it difficult to reconcile the Japanese politeness with the French intuitive negotiation style, they use the terminal to request support from the server. The server analyzes the user's emotions and suggests relaxed expressions of respect and presentation methods to alleviate tension. These suggestions are communicated to the user via the terminal, making it easier for the user to proceed with negotiations based on them.

[0127] In this way, this system, which combines emotional engines, provides support adapted to cultural and emotional backgrounds, embodying a practical means of facilitating smooth intercultural communication.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The server collects information about different cultures from the internet and specialized databases to form a cultural knowledge base. This knowledge base includes customs, communication styles, and important manners specific to each culture.

[0131] Step 2:

[0132] Users access the system through a terminal and input the necessary information and support requests. The terminal provides an interface that accepts the user's cultural background and the topics they wish to learn about.

[0133] Step 3:

[0134] The device records the user's emotional state by capturing the user's voice input and facial expressions through the camera and microphone, and sending them to the emotion engine.

[0135] Step 4:

[0136] The server uses natural language processing technology to analyze user information and sentiment data obtained from the terminal. It understands the user's intentions and emotions, and based on this, identifies potential communication challenges.

[0137] Step 5:

[0138] The emotion engine analyzes emotions from collected facial expression data and audio to determine whether the user is feeling anxiety, tension, or other similar emotions. This result influences the server's decision-making process.

[0139] Step 6:

[0140] Based on analysis results and sentiment data, the server derives the optimal communication strategy for the user from its knowledge base. This strategy is tailored to the user's emotional state and cultural background.

[0141] Step 7:

[0142] The server sends the generated communication strategy to the terminal. The terminal presents this strategy to the user visually or audibly, supporting the user's communication actions.

[0143] Step 8:

[0144] Users utilize the information presented on their devices and engage in dialogue with others according to the suggested communication strategy.

[0145] Step 9:

[0146] After a conversation or interaction ends, the device provides the user with feedback, including sentiment analysis results. This feedback allows the user to identify areas for improvement and successful examples in their communication style.

[0147] (Example 2)

[0148] 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".

[0149] In intercultural communication, overcoming cultural misunderstandings and emotional gaps presents a significant challenge. In particular, smooth communication with individuals from different cultural backgrounds requires not only verbal exchange but also an understanding of emotions and nonverbal cues. A system is needed to address this challenge and enable users to design appropriate communication strategies.

[0150] 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.

[0151] In this invention, the server includes means for collecting a wide range of information on different cultures and building a cultural knowledge base, means for collecting non-verbal emotional data in addition to user input information, and means for analyzing the information using natural language processing technology and identifying the user's emotional state using an emotion engine. This makes it possible to support users in implementing appropriate communication strategies across cultures.

[0152] "Different cultures" refer to cultures from different countries, regions, or social backgrounds, and mean that their cultural characteristics, values, and communication styles are diverse.

[0153] A "knowledge base" is a type of database that systematically organizes information and knowledge accumulated in a specific field, making it accessible as needed.

[0154] An "emotion engine" is a technical means by which a computer system recognizes emotions from a user's facial expressions and voice, and identifies their state.

[0155] "Natural language processing technology" is a technology that enables computers to understand and process human language, making it possible to analyze text and grasp its meaning.

[0156] A "generative AI model" refers to an algorithm that uses artificial intelligence to generate new data and information, especially text and images.

[0157] A "prompt sentence" is an example input or question used to extract specific information; it is a guiding sentence designed to help a generative AI model produce appropriate output.

[0158] "Feedback" is a response that provides information tailored to the user's actions and circumstances, encouraging further action or assisting in decision-making.

[0159] This invention provides a system for supporting intercultural communication. Its central components are a server, a terminal, and a user.

[0160] The server provides hardware and software for collecting, organizing, and analyzing large amounts of data related to different cultures. The cultural knowledge base functions as a constantly updated, complex database that draws information from a wide range of datasets. The server incorporates natural language processing technology and an emotion engine to analyze user-submitted text and non-verbal information (facial expressions, voice). The emotion engine is specifically designed to identify the user's emotional state and performs real-time sentiment analysis using advanced algorithms.

[0161] Users access the system through devices such as mobile phones and personal computers, and input and retrieve necessary information. These devices provide an interface for sending and receiving data with the server, and are equipped with devices for acquiring non-verbal information, such as cameras and microphones, which play a role in improving the accuracy of user sentiment data.

[0162] The generative AI model facilitates communication by generating prompts from analyzed data and providing them to the user. These prompts are optimized according to the user's situation, helping to bridge communication gaps across cultures. A specific example might be a prompt such as, "In business negotiations, please propose strategies to ease tensions, taking into account the cultural differences between Japanese and French companies." This prompt reflects the user's actual situation and provides guidance for offering more appropriate communication strategies.

[0163] Based on the hardware and software configuration described above, this system functions as a powerful tool to support effective intercultural communication.

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] The server collects comprehensive information related to different cultures. Input data includes cultural datasets and literature, which are used to build and update the database. Features are extracted from the datasets and aggregated as a cultural knowledge base, generating structured data that can be quickly referenced as needed.

[0167] Step 2:

[0168] The user connects to the system via a terminal and provides text-based input information. The terminal uses its camera and microphone to collect non-verbal information such as the user's voice and facial expressions, and sends it to the server. The input consists of text information and non-verbal hints, and this data is used in the next analysis step.

[0169] Step 3:

[0170] The server uses natural language processing technology to analyze the user's text information. Simultaneously, an emotion engine identifies the user's emotional state based on voice and facial expression data. It processes the input text data and nonverbal information and performs data analysis to understand the user's cultural background and emotional situation.

[0171] Step 4:

[0172] The server generates an optimal communication strategy based on the user's emotions and cultural knowledge base. This strategy is constructed from analyzed data and forms a dialogue plan that takes into account the user's current emotional state. The generated strategy is stored within the system and output in an executable format.

[0173] Step 5:

[0174] The terminal presents the user with a communication strategy received from the server. This includes prompts constructed using a generative AI model. The output consists of practical advice and suggestions tailored to the user's situation, presented in a format that is easy for the user to understand and act upon.

[0175] Step 6:

[0176] Users effectively communicate across cultures by following the suggested proposals and prompts. A feedback function provides real-time advice and suggestions for improvement based on the user's communication actions. This enables flexible responses tailored to different genres and situations.

[0177] (Application Example 2)

[0178] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0179] Cultural misunderstandings and emotional stress can arise in intercultural communication. In such situations, smooth dialogue and cooperation become difficult, creating a need for technologies that efficiently and consistently support intercultural communication.

[0180] 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.

[0181] In this invention, the server includes means for collecting information related to different cultures, means for analyzing user input using natural language processing technology to understand the cultural background, and means for analyzing the user's emotional state using emotion analysis technology and providing suggestions appropriate to the emotion based on the analysis results. This reduces misunderstandings and stress between cultures, enabling users to communicate with peace of mind.

[0182] A "system that supports intercultural communication" is a technology that helps people from different cultural backgrounds communicate smoothly with each other.

[0183] "Means of collecting information related to different cultures" refers to technologies that comprehensively collect data on different cultures and form a cultural knowledge base.

[0184] "Natural language processing technology" is a computer technology that analyzes user input to understand its meaning and cultural background.

[0185] "Emotional analysis technology" is a technology that evaluates and analyzes the emotional state of a user.

[0186] "Means of generating communication strategies" are techniques for proposing appropriate communication methods based on cultural background and emotional states.

[0187] "Means of providing proposals" refers to technologies that present generated communication strategies to users and help them in actual conversations.

[0188] In one embodiment of this invention, the intercultural communication support system consists of a server, a terminal, and a user.

[0189] The server comprehensively collects information related to different cultures and builds it into a cultural knowledge base. This base structures information on common misunderstandings between cultures and culture-specific communication styles. Furthermore, it analyzes the user's emotional state using sentiment analysis techniques. Specifically, the server integrates natural language processing and sentiment analysis techniques to analyze user input. Specific software used includes, for example, the Hugging Face Transformers library.

[0190] The device receives input from the user and also acquires nonverbal cues such as voice and facial expressions through the camera and microphone. This nonverbal information is used for emotion analysis, contributing to a detailed analysis of the user's emotional state.

[0191] Users interact with the system via their devices. Based on the analysis results, the system generates appropriate communication strategies tailored to the user's cultural background and emotional state, and provides this feedback to the user. This feedback helps users engage in cross-cultural interactions more smoothly and with greater confidence.

[0192] For example, if a user is speaking with a foreign client in a business meeting, the suggestions they receive might represent various strategies to mitigate cultural differences and facilitate effective communication.

[0193] The following prompt statements are possible inputs for a generative AI model:

[0194] Context: I am talking to someone from another country in a business meeting.

[0195] Input: "How should I respond when I encounter expressions specific to a different culture in a conversation?"

[0196] This allows users to leverage system suggestions and facilitate smooth, real-time cross-cultural communication.

[0197] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0198] Step 1:

[0199] The device receives voice input from the user and captures the voice data through the microphone. The voice data is converted to text using the Speech Recognition library. This converted text becomes the input for subsequent analysis processes.

[0200] Step 2:

[0201] The device captures the user's facial expressions through its camera and acquires them as image data using the OpenCV library. The acquired image data is then used as input for emotion analysis.

[0202] Step 3:

[0203] The server performs natural language processing on the acquired text data using the Hugging Face Transformers library. It understands the cultural background and context from the text content and obtains the analysis results. These analysis results become input for the next sentiment analysis step.

[0204] Step 4:

[0205] The server utilizes emotion analysis technology to evaluate the user's emotional state from input text and image data. In this process, the emotion engine specifically identifies the user's emotions and obtains analysis results. These results serve as output to deepen our understanding of the user's internal state.

[0206] Step 5:

[0207] The server generates an optimal communication strategy based on the analyzed cultural and emotional data. This strategy serves as a guideline for providing users with relevant suggestions using a generative AI model.

[0208] Step 6:

[0209] The terminal displays the communication strategy received from the server to the user. The user can use this feedback to facilitate smooth cross-cultural communication. Specific suggestions include appropriate expressions and dialogue techniques that take the other party's culture into consideration.

[0210] This series of processes enables users to avoid cross-cultural misunderstandings in real time and facilitate smooth communication.

[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] The intercultural communication support system according to the present invention is a system based on the collection of intercultural information and the analysis of user input, and is implemented as follows.

[0228] The server collects vast amounts of information about different cultures from the internet and specialized databases to build a cultural knowledge base. This knowledge base includes common customs, business etiquette, and communication styles to be aware of in different cultural spheres.

[0229] The user accesses the system using a terminal and inputs information about their own cultural background and the cultural background of the person they wish to communicate with into the server. The terminal receives the input from the user and sends it to the server.

[0230] The server analyzes the received user input using natural language processing technology to understand the user's intentions and emotions. Based on this, the server identifies potential challenges related to cross-cultural communication, references relevant information from its knowledge base, and generates the optimal communication strategy for the user.

[0231] The terminal receives suggestions from the server and presents them to the user visually or audibly. Based on this information, the user can choose appropriate actions and engage in cross-cultural communication.

[0232] As a concrete example, consider a business meeting between a Japanese company and a British company. The user inputs a request via their device to review basic business etiquette related to Japanese culture. The server uses natural language processing technology to analyze the user's input and provides information about how to show respect and the importance of exchanging business cards in Japanese business culture. This information is presented to the user via their device, enabling them to adopt appropriate attitudes and behaviors during the meeting.

[0233] Furthermore, after the meeting, the device can display feedback on the user's communication behavior and suggest areas for improvement and success stories for the next meeting, thereby continuously improving the user's cross-cultural understanding.

[0234] The following describes the processing flow.

[0235] Step 1:

[0236] The server collects information about different cultures from the internet and specialized databases, and stores it as a cultural knowledge base. This knowledge base includes information on cultural customs, business etiquette, and communication styles from around the world.

[0237] Step 2:

[0238] Users access the system through a terminal. The terminal provides an interface that receives questions from the user regarding communication methods based on the other party's culture and specific situations.

[0239] Step 3:

[0240] The device sends the user's question to the server. The question includes information about the user's cultural background and the cultural background of the person they wish to communicate with.

[0241] Step 4:

[0242] The server receives user input data sent from the terminal and analyzes its content using natural language processing technology. This allows it to identify the user's intentions and emotions, and pinpoint communication challenges in light of their cultural background.

[0243] Step 5:

[0244] The server extracts relevant information from its knowledge base based on the analysis results and generates an optimal communication strategy for the user. This strategy includes specific language choices and guidelines for action.

[0245] Step 6:

[0246] The server sends the generated communication strategy to the terminal. The terminal presents this proposal to the user visually or audibly.

[0247] Step 7:

[0248] Users refer to the information presented on their devices and take appropriate actions in real-world communication scenarios.

[0249] Step 8:

[0250] After the conversation ends, the device provides feedback based on the user's choices and actions. This feedback includes successes and areas for improvement, serving as guidance for future communication.

[0251] (Example 1)

[0252] 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."

[0253] In intercultural communication, it is essential to mitigate misunderstandings and friction arising from differences in cultural backgrounds. However, traditional methods have struggled to efficiently collect and analyze detailed information about each culture, resulting in a lack of timely provision of concrete strategies for users to facilitate smooth intercultural communication.

[0254] 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.

[0255] In this invention, the server includes means for collecting information on different cultures from a global information network and specialized information sources, means for forming a cultural knowledge base based on the collected information, means for using natural language processing technology to receive and analyze user information, and means for presenting the generated dialogue strategy to the user visually or audibly. This enables the user to obtain an effective cross-cultural communication strategy.

[0256] "Information about different cultures" is a general term encompassing customs, social norms, business etiquette, and communication styles related to diverse cultures around the world.

[0257] A "global information network" refers to a globally accessible information network that utilizes the internet.

[0258] A "specialized information source" refers to a reliable source that provides highly specialized knowledge and data on a particular field or topic.

[0259] A "cultural knowledge base" is a structured collection of knowledge generated from collected culture-related information, which is used to support intercultural understanding.

[0260] A "user" is an individual or organization that inputs information and receives results through an intercultural communication support system.

[0261] "Natural language processing technology" is a technology that uses computers to process and analyze human language in order to understand its meaning.

[0262] A "generative model" refers to an algorithm that automatically generates dialogue strategies and information based on input data.

[0263] A "dialogue strategy" refers to a set of planned guidelines and methods for effectively conducting communication with a specific purpose.

[0264] "Means of visual or auditory presentation" refers to methods of providing information to users in a form that they can see or hear through displays, speakers, etc.

[0265] The intercultural communication support system according to the present invention is specifically implemented based on the collection of intercultural information and the analysis of user input. The embodiments of this system are described in detail below.

[0266] The server collects information on different cultures from a global information network and specialized information sources. Specifically, it can obtain culture-related data using, for example, a web scraping program developed in Python. Based on the collected data, this server forms a cultural knowledge base and stores it in a MySQL database, thereby building a vast information resource for intercultural understanding.

[0267] Users access the system through their terminal and input information about their own cultural background and the cultural background of the other party. This input information is provided in text format, for example, in a form on a web browser, such as "I come from an Asian cultural background and I am collaborating with European partners." The terminal sends the acquired user input information to the server, where it is processed.

[0268] The server uses natural language processing techniques to process the received input information. This process utilizes natural language processing libraries such as spaCy and Transformers to analyze the user's intent and emotions. Furthermore, a generative AI model generates the optimal communication strategy for the user. This ensures that the user receives specific and appropriate cultural characteristics and advice to be mindful of during interactions.

[0269] The generated communication strategy is presented to the user visually or audibly via the device. For example, the display might show information such as, "In European business meetings, direct and clear communication is preferred." Users can use this information to facilitate smooth communication across cultures.

[0270] As a concrete example, in a business meeting between a Japanese company and a British company, the user enters a prompt message via their terminal saying, "I would like to learn about British business etiquette." In response, the server generates a strategy such as, "In British culture, prior confirmation via email is important, and limited body language is recommended during conversations," and presents it to the user. In this way, the present invention effectively supports the user's cross-cultural adaptation and successful communication.

[0271] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0272] Step 1:

[0273] The server collects information about different cultures from global information networks such as the internet and specialized information sources. This information includes the unique customs and communication styles of each cultural sphere. This collection utilizes web scraping techniques, and sometimes data is obtained from APIs. The input is keywords related to a specific culture, and the output is raw data to form a cultural knowledge base.

[0274] Step 2:

[0275] The server analyzes the collected raw data and builds a cultural knowledge base. Specifically, it uses database software to classify the collected data by cultural area and extracts cultural features and patterns by performing text mining as needed. The input is raw data, and the output is a structured knowledge base.

[0276] Step 3:

[0277] The user inputs information regarding their own cultural background and the cultural background of the other party through the terminal. This is usually input in text form into a web form. This information indicates the user's intentions and the background of the communication they seek, and the terminal sends this input to the server. The input is the user's cultural background information, and the output is the state where data is prepared for natural language processing.

[0278] Step 4:

[0279] The server analyzes the received user information using natural language processing techniques. Here, existing libraries (such as spaCy or Transformers) are used to understand what the input text represents in terms of the user's intentions and emotions. The input is the text sent from the user, and the output is the analyzed intention and emotion data.

[0280] Step 5:

[0281] The server utilizes a generated AI model based on the user's intention and emotion data to generate an appropriate communication strategy. In this generation, information from prediction algorithms and knowledge bases is combined to derive specific action guidelines and advice. The input is the analyzed intention and emotion data, and the output is the specific communication strategy.

[0282] Step 6:

[0283] The terminal visually or audibly presents the communication strategy received from the server to the user. This is achieved by displaying information on the display or reading the content using speech synthesis. The input is the generated communication strategy, and the output is the information presented to the user visually or as audio.

[0284] Step 7:

[0285] The user executes cross-cultural communication based on the communication strategy presented by the system. Then, through the terminal, the user provides feedback on their communication. The input is feedback based on the user's actual experience, and the output is reflected as improvements and success stories for the next time.

[0286] (Application Example 1)

[0287] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0288] In situations where cross-cultural communication is required, communication between people with different cultural backgrounds may lead to insufficient understanding or misunderstandings. Therefore, a system that supports smoother and more accurate communication is needed. In particular, in autonomous vehicles, providing guidance and guides according to the cultural background of passengers is an issue.

[0289] 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.

[0290] In this invention, the server includes means for collecting information on different cultures, means for analyzing the user's input by natural language processing technology to understand the cultural background, and means for generating an appropriate communication strategy based on the analysis result. As a result, it becomes possible to optimize voice guidance considering different cultural backgrounds in an autonomous vehicle.

[0291] "Information on different cultures" is a general term for customs, values, communication styles, etc. in different cultural circles.

[0292] "Natural language processing technology" is a technology for enabling a computer to understand, analyze, and generate human language.

[0293] "Cultural background" refers to the characteristics of the culture to which individuals belong and the historical influence.

[0294] A "communication strategy" refers to the methods of contact and information transmission established to facilitate smooth intercultural exchange.

[0295] "Optimizing voice guidance" means providing optimal voice guidance tailored to the characteristics of the user and the environment.

[0296] A "knowledge base" is a database that structurally organizes information and data, and aggregates knowledge related to a specific field.

[0297] The system for realizing this invention optimizes voice guidance within an autonomous vehicle according to the cultural background of the passengers, in order to support intercultural communication.

[0298] The server collects information on different cultures from the internet and specialized databases to build a cultural knowledge base. Using a natural language processing engine (e.g., Google Cloud Natural Language API), it analyzes the user's voice input to understand their intent and emotions. Based on the analyzed information, the server generates an appropriate communication strategy and optimizes voice guidance. The generated guidance is presented to passengers via the in-vehicle computer through displays and voice systems.

[0299] The terminal uses a voice recognition microphone to receive cultural background information and navigation needs entered by the user via voice. This input is sent to a server for analysis.

[0300] As a concrete example, if a Japanese tourist boards an autonomous vehicle in an international tourist destination, this system can provide audio guidance about local cultural customs and tourist attractions. This allows passengers to enjoy a comfortable and easy-to-understand navigation experience.

[0301] Examples of prompt texts for the generation AI model include "The passengers in the car are from Japan. Please provide useful cultural advice in this country."

[0302] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0303] Step 1:

[0304] The terminal receives voice input from the user using the voice recognition microphone. This input includes the user's cultural background information and navigation preferences. The terminal converts this voice into a digital signal and transmits it to the server.

[0305] Step 2:

[0306] The server analyzes the received digital voice signal using a natural language processing engine and converts it into text data. Thereby, information for understanding the user's intention, emotion, and cultural background is obtained. The analyzed text data is compared with the knowledge base.

[0307] Step 3:

[0308] The server refers to the knowledge base and generates an appropriate communication strategy based on the user's cultural background. This strategy includes information on cultural manners and tourist guides. Using the generation AI model, specific guidance content is formulated.

[0309] Step 4:

[0310] The server determines the content of the voice guidance based on the generated communication strategy and generates digital voice data. This data is output as guidance information through the in-vehicle computer.

[0311] Step 5:

[0312] The terminal provides passengers with voice guidance through the vehicle's speaker system. Through this voice guidance, users can receive appropriate cultural and tourist information, allowing them to travel to their destination with peace of mind.

[0313] 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.

[0314] The intercultural communication support system according to the present invention achieves advanced communication support that takes emotional elements into consideration by combining it with an emotion engine. An embodiment thereof is shown below.

[0315] The server first comprehensively collects information about different cultures to form a cultural knowledge base. This knowledge base structures detailed information about common misunderstandings that occur between cultures and culture-specific communication styles. Meanwhile, an emotion engine is built into the system to appropriately analyze the user's emotional state.

[0316] The user connects to the system via a terminal. The terminal transmits not only user input information but also non-verbal cues such as voice and facial expressions using the camera and microphone to the emotion engine. This process allows the user to receive appropriate support even in situations involving emotions such as anxiety, tension, or joy.

[0317] The server uses natural language processing technology to analyze information received from users, performing sentiment analysis in parallel with understanding the cultural background. Specifically, it derives communication strategies that match the user's emotional state from a knowledge base and generates optimal suggestions that take into account the cultural background and emotional state.

[0318] The terminal receives instructions from the server and presents the user with an appropriate communication strategy. Here, it can provide feedback that aligns with the user's emotions, creating a sense of security while assisting in problem-solving.

[0319] As a concrete example, consider a scenario where a Japanese company and a French company are conducting business negotiations. When a user finds it difficult to reconcile the Japanese politeness with the French intuitive negotiation style, they use the terminal to request support from the server. The server analyzes the user's emotions and suggests relaxed expressions of respect and presentation methods to alleviate tension. These suggestions are communicated to the user via the terminal, making it easier for the user to proceed with negotiations based on them.

[0320] In this way, this system, which combines emotional engines, provides support adapted to cultural and emotional backgrounds, embodying a practical means of facilitating smooth intercultural communication.

[0321] The following describes the processing flow.

[0322] Step 1:

[0323] The server collects information about different cultures from the internet and specialized databases to form a cultural knowledge base. This knowledge base includes customs, communication styles, and important manners specific to each culture.

[0324] Step 2:

[0325] Users access the system through a terminal and input the necessary information and support requests. The terminal provides an interface that accepts the user's cultural background and the topics they wish to learn about.

[0326] Step 3:

[0327] The device records the user's emotional state by capturing the user's voice input and facial expressions through the camera and microphone, and sending them to the emotion engine.

[0328] Step 4:

[0329] The server uses natural language processing technology to analyze user information and sentiment data obtained from the terminal. It understands the user's intentions and emotions and identifies potential communication challenges based on this understanding.

[0330] Step 5:

[0331] The emotion engine analyzes emotions from collected facial expression data and audio to determine whether the user is feeling anxiety, tension, or other similar emotions. This result influences the server's decision-making process.

[0332] Step 6:

[0333] Based on analysis results and sentiment data, the server derives the optimal communication strategy for the user from its knowledge base. This strategy is tailored to the user's emotional state and cultural background.

[0334] Step 7:

[0335] The server sends the generated communication strategy to the terminal. The terminal presents this strategy to the user visually or audibly, supporting the user's communication actions.

[0336] Step 8:

[0337] Users utilize the information presented on their devices and engage in dialogue with others according to the suggested communication strategy.

[0338] Step 9:

[0339] After a conversation or interaction ends, the device provides the user with feedback, including sentiment analysis results. This feedback allows the user to identify areas for improvement and successful examples in their communication style.

[0340] (Example 2)

[0341] 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".

[0342] In intercultural communication, overcoming cultural misunderstandings and emotional gaps presents a significant challenge. In particular, smooth communication with individuals from different cultural backgrounds requires not only verbal exchange but also an understanding of emotions and nonverbal cues. A system is needed to address this challenge and enable users to design appropriate communication strategies.

[0343] 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.

[0344] In this invention, the server includes means for collecting a wide range of information on different cultures and building a cultural knowledge base, means for collecting non-verbal emotional data in addition to user input information, and means for analyzing the information using natural language processing technology and identifying the user's emotional state using an emotion engine. This makes it possible to support users in implementing appropriate communication strategies across cultures.

[0345] "Different cultures" refer to cultures from different countries, regions, or social backgrounds, and mean that their cultural characteristics, values, and communication styles are diverse.

[0346] A "knowledge base" is a type of database that systematically organizes information and knowledge accumulated in a specific field, making it accessible as needed.

[0347] An "emotion engine" is a technical means by which a computer system recognizes emotions from a user's facial expressions and voice, and identifies their state.

[0348] "Natural language processing technology" is a technology that enables computers to understand and process human language, making it possible to analyze text and grasp its meaning.

[0349] A "generative AI model" refers to an algorithm that uses artificial intelligence to generate new data and information, especially text and images.

[0350] A "prompt sentence" is an example input or question used to extract specific information; it is a guiding sentence designed to help a generative AI model produce appropriate output.

[0351] "Feedback" is a response that provides information tailored to the user's actions and circumstances, encouraging further action or assisting in decision-making.

[0352] This invention provides a system for supporting intercultural communication. Its central components are a server, a terminal, and a user.

[0353] The server provides hardware and software for collecting, organizing, and analyzing large amounts of data related to different cultures. The cultural knowledge base functions as a constantly updated, complex database that draws information from a wide range of datasets. The server incorporates natural language processing technology and an emotion engine to analyze user-submitted text and non-verbal information (facial expressions, voice). The emotion engine is specifically designed to identify the user's emotional state and performs real-time sentiment analysis using advanced algorithms.

[0354] Users access the system through devices such as mobile phones and personal computers, and input and retrieve necessary information. These devices provide an interface for sending and receiving data with the server, and are equipped with devices for acquiring non-verbal information, such as cameras and microphones, which play a role in improving the accuracy of user sentiment data.

[0355] The generative AI model facilitates communication by generating prompts from analyzed data and providing them to the user. These prompts are optimized according to the user's situation, helping to bridge communication gaps across cultures. A specific example might be a prompt such as, "In business negotiations, please propose strategies to ease tensions, taking into account the cultural differences between Japanese and French companies." This prompt reflects the user's actual situation and provides guidance for offering more appropriate communication strategies.

[0356] Based on the hardware and software configuration described above, this system functions as a powerful tool to support effective intercultural communication.

[0357] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0358] Step 1:

[0359] The server collects comprehensive information related to different cultures. Input data includes cultural datasets and literature, which are used to build and update the database. Features are extracted from the datasets and aggregated as a cultural knowledge base, generating structured data that can be quickly referenced as needed.

[0360] Step 2:

[0361] The user connects to the system via a terminal and provides text-based input information. The terminal uses its camera and microphone to collect non-verbal information such as the user's voice and facial expressions, and sends it to the server. The input consists of text information and non-verbal hints, and this data is used in the next analysis step.

[0362] Step 3:

[0363] The server uses natural language processing technology to analyze the user's text information. Simultaneously, an emotion engine identifies the user's emotional state based on voice and facial expression data. It processes the input text data and nonverbal information and performs data analysis to understand the user's cultural background and emotional situation.

[0364] Step 4:

[0365] The server generates an optimal communication strategy based on the user's emotions and cultural knowledge base. This strategy is constructed from analyzed data and forms a dialogue plan that takes into account the user's current emotional state. The generated strategy is stored within the system and output in an executable format.

[0366] Step 5:

[0367] The terminal presents the user with a communication strategy received from the server. This includes prompts constructed using a generative AI model. The output consists of practical advice and suggestions tailored to the user's situation, presented in a format that is easy for the user to understand and act upon.

[0368] Step 6:

[0369] Users effectively communicate across cultures by following the suggested proposals and prompts. A feedback function provides real-time advice and suggestions for improvement based on the user's communication actions. This enables flexible responses tailored to different genres and situations.

[0370] (Application Example 2)

[0371] 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."

[0372] Cultural misunderstandings and emotional stress can arise in intercultural communication. In such situations, smooth dialogue and cooperation become difficult, creating a need for technologies that efficiently and consistently support intercultural communication.

[0373] 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.

[0374] In this invention, the server includes means for collecting information related to different cultures, means for analyzing user input using natural language processing technology to understand the cultural background, and means for analyzing the user's emotional state using emotion analysis technology and providing suggestions appropriate to the emotion based on the analysis results. This reduces misunderstandings and stress between cultures, enabling users to communicate with peace of mind.

[0375] A "system that supports intercultural communication" is a technology that helps people from different cultural backgrounds communicate smoothly with each other.

[0376] "Means of collecting information related to different cultures" refers to technologies that comprehensively collect data on different cultures and form a cultural knowledge base.

[0377] "Natural language processing technology" is a computer technology that analyzes user input to understand its meaning and cultural background.

[0378] "Emotional analysis technology" is a technology that evaluates and analyzes the emotional state of a user.

[0379] "Means of generating communication strategies" are techniques for proposing appropriate communication methods based on cultural background and emotional states.

[0380] "Means of providing proposals" refers to technologies that present generated communication strategies to users and help them in actual conversations.

[0381] In one embodiment of this invention, the intercultural communication support system consists of a server, a terminal, and a user.

[0382] The server comprehensively collects information related to different cultures and builds it into a cultural knowledge base. This base structures information on common misunderstandings between cultures and culture-specific communication styles. Furthermore, it analyzes the user's emotional state using sentiment analysis techniques. Specifically, the server integrates natural language processing and sentiment analysis techniques to analyze user input. Specific software used includes, for example, the Hugging Face Transformers library.

[0383] The device receives input from the user and also acquires nonverbal cues such as voice and facial expressions through the camera and microphone. This nonverbal information is used for emotion analysis, contributing to a detailed analysis of the user's emotional state.

[0384] Users interact with the system via their devices. Based on the analysis results, the system generates appropriate communication strategies tailored to the user's cultural background and emotional state, and provides this feedback to the user. This feedback helps users engage in cross-cultural interactions more smoothly and with greater confidence.

[0385] For example, if a user is speaking with a foreign client in a business meeting, the suggestions they receive might represent various strategies to mitigate cultural differences and facilitate effective communication.

[0386] The following prompt statements are possible inputs for a generative AI model:

[0387] Context: I am talking to someone from another country in a business meeting.

[0388] Input: "How should I respond when I encounter expressions specific to a different culture in a conversation?"

[0389] This allows users to leverage system suggestions and facilitate smooth, real-time cross-cultural communication.

[0390] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0391] Step 1:

[0392] The device receives voice input from the user and captures the voice data through the microphone. The voice data is converted to text using the Speech Recognition library. This converted text becomes the input for subsequent analysis processes.

[0393] Step 2:

[0394] The device captures the user's facial expressions through its camera and acquires them as image data using the OpenCV library. The acquired image data is then used as input for emotion analysis.

[0395] Step 3:

[0396] The server performs natural language processing on the acquired text data using the Hugging Face Transformers library. It understands the cultural background and context from the text content and obtains the analysis results. These analysis results become input for the next sentiment analysis step.

[0397] Step 4:

[0398] The server utilizes emotion analysis technology to evaluate the user's emotional state from input text and image data. In this process, the emotion engine specifically identifies the user's emotions and obtains analysis results. These results serve as output to deepen our understanding of the user's internal state.

[0399] Step 5:

[0400] The server generates an optimal communication strategy based on the analyzed cultural and emotional data. This strategy serves as a guideline for providing users with relevant suggestions using a generative AI model.

[0401] Step 6:

[0402] The terminal displays the communication strategy received from the server to the user. The user can use this feedback to facilitate smooth cross-cultural communication. Specific suggestions include appropriate expressions and dialogue techniques that take the other party's culture into consideration.

[0403] This series of processes enables users to avoid cross-cultural misunderstandings in real time and facilitate smooth communication.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] [Third Embodiment]

[0408] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0409] 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.

[0410] 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).

[0411] 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.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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".

[0420] The intercultural communication support system according to the present invention is a system based on the collection of intercultural information and the analysis of user input, and is implemented as follows.

[0421] The server collects vast amounts of information about different cultures from the internet and specialized databases to build a cultural knowledge base. This knowledge base includes common customs, business etiquette, and communication styles to be aware of in different cultural spheres.

[0422] The user accesses the system using a terminal and inputs information about their own cultural background and the cultural background of the person they wish to communicate with into the server. The terminal receives the input from the user and sends it to the server.

[0423] The server analyzes the received user input using natural language processing technology to understand the user's intentions and emotions. Based on this, the server identifies potential challenges related to cross-cultural communication, references relevant information from its knowledge base, and generates the optimal communication strategy for the user.

[0424] The terminal receives suggestions from the server and presents them to the user visually or audibly. Based on this information, the user can choose appropriate actions and engage in cross-cultural communication.

[0425] As a concrete example, consider a business meeting between a Japanese company and a British company. The user inputs a request via their device to review basic business etiquette related to Japanese culture. The server uses natural language processing technology to analyze the user's input and provides information about how to show respect and the importance of exchanging business cards in Japanese business culture. This information is presented to the user via their device, enabling them to adopt appropriate attitudes and behaviors during the meeting.

[0426] Furthermore, after the meeting, the device can display feedback on the user's communication behavior and suggest areas for improvement and success stories for the next meeting, thereby continuously improving the user's cross-cultural understanding.

[0427] The following describes the processing flow.

[0428] Step 1:

[0429] The server collects information about different cultures from the internet and specialized databases, and stores it as a cultural knowledge base. This knowledge base includes information on cultural customs, business etiquette, and communication styles from around the world.

[0430] Step 2:

[0431] Users access the system through a terminal. The terminal provides an interface that receives questions from the user regarding communication methods based on the other party's culture and specific situations.

[0432] Step 3:

[0433] The device sends the user's question to the server. The question includes information about the user's cultural background and the cultural background of the person they wish to communicate with.

[0434] Step 4:

[0435] The server receives user input data sent from the terminal and analyzes its content using natural language processing technology. This allows it to identify the user's intentions and emotions, and pinpoint communication challenges in light of their cultural background.

[0436] Step 5:

[0437] The server extracts relevant information from its knowledge base based on the analysis results and generates an optimal communication strategy for the user. This strategy includes specific language choices and guidelines for action.

[0438] Step 6:

[0439] The server sends the generated communication strategy to the terminal. The terminal presents this proposal to the user visually or audibly.

[0440] Step 7:

[0441] Users refer to the information presented on their devices and take appropriate actions in real-world communication scenarios.

[0442] Step 8:

[0443] After the conversation ends, the device provides feedback based on the user's choices and actions. This feedback includes successes and areas for improvement, serving as guidance for future communication.

[0444] (Example 1)

[0445] 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."

[0446] In intercultural communication, it is essential to mitigate misunderstandings and friction arising from differences in cultural backgrounds. However, traditional methods have struggled to efficiently collect and analyze detailed information about each culture, resulting in a lack of timely provision of concrete strategies for users to facilitate smooth intercultural communication.

[0447] 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.

[0448] In this invention, the server includes means for collecting information on different cultures from a global information network and specialized information sources, means for forming a cultural knowledge base based on the collected information, means for using natural language processing technology to receive and analyze user information, and means for presenting the generated dialogue strategy to the user visually or audibly. This enables the user to obtain an effective cross-cultural communication strategy.

[0449] "Information about different cultures" is a general term encompassing customs, social norms, business etiquette, and communication styles related to diverse cultures around the world.

[0450] A "global information network" refers to a globally accessible information network that utilizes the internet.

[0451] A "specialized information source" refers to a reliable source that provides highly specialized knowledge and data on a particular field or topic.

[0452] A "cultural knowledge base" is a structured collection of knowledge generated from collected culture-related information, which is used to support intercultural understanding.

[0453] A "user" is an individual or organization that inputs information and receives results through an intercultural communication support system.

[0454] "Natural language processing technology" is a technology that uses computers to process and analyze human language in order to understand its meaning.

[0455] A "generative model" refers to an algorithm that automatically generates dialogue strategies and information based on input data.

[0456] A "dialogue strategy" refers to a set of planned guidelines and methods for effectively conducting communication with a specific purpose.

[0457] "Means of visual or auditory presentation" refers to methods of providing information to users in a form that they can see or hear through displays, speakers, etc.

[0458] The intercultural communication support system according to the present invention is specifically implemented based on the collection of intercultural information and the analysis of user input. The embodiments of this system are described in detail below.

[0459] The server collects information on different cultures from a global information network and specialized information sources. Specifically, it can obtain culture-related data using, for example, a web scraping program developed in Python. Based on the collected data, this server forms a cultural knowledge base and stores it in a MySQL database, thereby building a vast information resource for intercultural understanding.

[0460] Users access the system through their terminal and input information about their own cultural background and the cultural background of the other party. This input information is provided in text format, for example, in a form on a web browser, such as "I come from an Asian cultural background and I am collaborating with European partners." The terminal sends the acquired user input information to the server, where it is processed.

[0461] The server uses natural language processing techniques to process the received input information. This process utilizes natural language processing libraries such as spaCy and Transformers to analyze the user's intent and emotions. Furthermore, a generative AI model generates the optimal communication strategy for the user. This ensures that the user receives specific and appropriate cultural characteristics and advice to be mindful of during interactions.

[0462] The generated communication strategy is presented to the user visually or audibly via the device. For example, the display might show information such as, "In European business meetings, direct and clear communication is preferred." Users can use this information to facilitate smooth communication across cultures.

[0463] As a concrete example, in a business meeting between a Japanese company and a British company, the user enters a prompt message via their terminal saying, "I would like to learn about British business etiquette." In response, the server generates a strategy such as, "In British culture, prior confirmation via email is important, and limited body language is recommended during conversations," and presents it to the user. In this way, the present invention effectively supports the user's cross-cultural adaptation and successful communication.

[0464] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0465] Step 1:

[0466] The server collects information about different cultures from global information networks such as the internet and specialized information sources. This information includes the unique customs and communication styles of each cultural sphere. This collection utilizes web scraping techniques, and sometimes data is obtained from APIs. The input is keywords related to a specific culture, and the output is raw data to form a cultural knowledge base.

[0467] Step 2:

[0468] The server analyzes the collected raw data and builds a cultural knowledge base. Specifically, it uses database software to classify the collected data by cultural area and extracts cultural features and patterns by performing text mining as needed. The input is raw data, and the output is a structured knowledge base.

[0469] Step 3:

[0470] Users input information about their own cultural background and the cultural background of the other party through their device. This is usually entered in text format into a web form. This information indicates the user's intentions and the background of the communication they seek, and the device sends this input to the server. The input is the user's cultural background information, and the output is data prepared for natural language processing.

[0471] Step 4:

[0472] The server analyzes the received user information using natural language processing techniques. Here, existing libraries (e.g., spaCy and Transformers) are used to understand the user's intent and sentiment in relation to the input text. The input is the text sent by the user, and the output is the analyzed intent and sentiment data.

[0473] Step 5:

[0474] The server utilizes a generative AI model based on user intent and sentiment data to generate appropriate communication strategies. This generation process combines predictive algorithms with information from a knowledge base to derive specific action guidelines and advice. The input is analyzed intent and sentiment data, and the output is a specific communication strategy.

[0475] Step 6:

[0476] The terminal presents the communication strategy received from the server to the user visually or audibly. This is achieved by displaying information on a screen or by using speech synthesis to read the content aloud. The input is the generated communication strategy, and the output is the information presented to the user visually or audibly.

[0477] Step 7:

[0478] Users engage in cross-cultural communication based on communication strategies presented by the system. They then provide feedback on their communication through the device. The input is feedback based on the user's real-world experience, and the output is used to identify areas for improvement and identify success stories for future interactions.

[0479] (Application Example 1)

[0480] 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."

[0481] In situations requiring intercultural communication, interactions between individuals with different cultural backgrounds can sometimes lead to insufficient understanding or misunderstandings. Therefore, there is a need for systems that support smoother and more accurate communication. In particular, in autonomous vehicles, providing guidance and information tailored to the cultural backgrounds of passengers is a challenge.

[0482] 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.

[0483] In this invention, the server includes means for collecting information about different cultures, means for analyzing user input using natural language processing technology to understand the cultural background, and means for generating an appropriate communication strategy based on the analysis results. This makes it possible to optimize voice guidance in autonomous vehicles while taking into account different cultural backgrounds.

[0484] "Information about different cultures" is a general term encompassing customs, values, and communication styles in different cultural spheres.

[0485] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0486] "Cultural background" refers to the characteristics and historical influences of the culture to which individuals belong.

[0487] A "communication strategy" refers to the methods of contact and information transmission established to facilitate smooth intercultural exchange.

[0488] "Optimizing voice guidance" means providing optimal voice guidance tailored to the characteristics of the user and the environment.

[0489] A "knowledge base" is a database that structurally organizes information and data, and aggregates knowledge related to a specific field.

[0490] The system for realizing this invention optimizes voice guidance within an autonomous vehicle according to the cultural background of the passengers, in order to support intercultural communication.

[0491] The server collects information on different cultures from the internet and specialized databases to build a cultural knowledge base. Using a natural language processing engine (e.g., Google Cloud Natural Language API), it analyzes the user's voice input to understand their intent and emotions. Based on the analyzed information, the server generates an appropriate communication strategy and optimizes voice guidance. The generated guidance is presented to passengers via the in-vehicle computer through displays and voice systems.

[0492] The terminal uses a voice recognition microphone to receive cultural background information and navigation needs entered by the user via voice. This input is sent to a server for analysis.

[0493] As a concrete example, if a Japanese tourist boards an autonomous vehicle in an international tourist destination, this system can provide audio guidance about local cultural customs and tourist attractions. This allows passengers to enjoy a comfortable and easy-to-understand navigation experience.

[0494] An example of a prompt sentence for a generative AI model is, "The passenger on the train is from Japan. Please provide helpful cultural advice for this country."

[0495] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0496] Step 1:

[0497] The device receives voice input from the user using a voice recognition microphone. This input includes the user's cultural background information and navigation preferences. The device converts this voice into a digital signal and sends it to the server.

[0498] Step 2:

[0499] The server analyzes the received digital audio signal using a natural language processing engine and converts it into text data. This provides information to understand the user's intent, emotions, and cultural background. The analyzed text data is then compared with a knowledge base.

[0500] Step 3:

[0501] The server references a knowledge base and generates an appropriate communication strategy based on the user's cultural background. This strategy includes information on cultural etiquette and tourist information. A generative AI model is used to formulate specific guidance content.

[0502] Step 4:

[0503] The server determines the content of the voice guidance based on the generated communication strategy and generates digital voice data. This data is output as guidance information via the in-vehicle computer.

[0504] Step 5:

[0505] The terminal provides passengers with voice guidance through the vehicle's speaker system. Through this voice guidance, users can receive appropriate cultural and tourist information, allowing them to travel to their destination with peace of mind.

[0506] 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.

[0507] The intercultural communication support system according to the present invention achieves advanced communication support that takes emotional elements into consideration by combining it with an emotion engine. An embodiment thereof is shown below.

[0508] The server first comprehensively collects information about different cultures to form a cultural knowledge base. This knowledge base structures detailed information about common misunderstandings that occur between cultures and culture-specific communication styles. Meanwhile, an emotion engine is built into the system to appropriately analyze the user's emotional state.

[0509] The user connects to the system via a terminal. The terminal transmits not only user input information but also non-verbal cues such as voice and facial expressions using the camera and microphone to the emotion engine. This process allows the user to receive appropriate support even in situations involving emotions such as anxiety, tension, or joy.

[0510] The server uses natural language processing technology to analyze information received from users, performing sentiment analysis in parallel with understanding the cultural background. Specifically, it derives communication strategies that match the user's emotional state from a knowledge base and generates optimal suggestions that take into account the cultural background and emotional state.

[0511] The terminal receives instructions from the server and presents the user with an appropriate communication strategy. Here, it can provide feedback that aligns with the user's emotions, creating a sense of security while assisting in problem-solving.

[0512] As a concrete example, consider a scenario where a Japanese company and a French company are conducting business negotiations. When a user finds it difficult to reconcile the Japanese politeness with the French intuitive negotiation style, they use the terminal to request support from the server. The server analyzes the user's emotions and suggests relaxed expressions of respect and presentation methods to alleviate tension. These suggestions are communicated to the user via the terminal, making it easier for the user to proceed with negotiations based on them.

[0513] In this way, this system, which combines emotional engines, provides support adapted to cultural and emotional backgrounds, embodying a practical means of facilitating smooth intercultural communication.

[0514] The following describes the processing flow.

[0515] Step 1:

[0516] The server collects information about different cultures from the internet and specialized databases to form a cultural knowledge base. This knowledge base includes customs, communication styles, and important manners specific to each culture.

[0517] Step 2:

[0518] Users access the system through a terminal and input the necessary information and support requests. The terminal provides an interface that accepts the user's cultural background and the topics they wish to learn about.

[0519] Step 3:

[0520] The device records the user's emotional state by capturing the user's voice input and facial expressions through the camera and microphone, and sending them to the emotion engine.

[0521] Step 4:

[0522] The server uses natural language processing technology to analyze user information and sentiment data obtained from the terminal. It understands the user's intentions and emotions and identifies potential communication challenges based on this understanding.

[0523] Step 5:

[0524] The emotion engine analyzes emotions from collected facial expression data and audio to determine whether the user is feeling anxiety, tension, or other similar emotions. This result influences the server's decision-making process.

[0525] Step 6:

[0526] Based on analysis results and sentiment data, the server derives the optimal communication strategy for the user from its knowledge base. This strategy is tailored to the user's emotional state and cultural background.

[0527] Step 7:

[0528] The server sends the generated communication strategy to the terminal. The terminal presents this strategy to the user visually or audibly, supporting the user's communication actions.

[0529] Step 8:

[0530] Users utilize the information presented on their devices and engage in dialogue with others according to the suggested communication strategy.

[0531] Step 9:

[0532] After a conversation or interaction ends, the device provides the user with feedback, including sentiment analysis results. This feedback allows the user to identify areas for improvement and successful examples in their communication style.

[0533] (Example 2)

[0534] 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."

[0535] In intercultural communication, overcoming cultural misunderstandings and emotional gaps presents a significant challenge. In particular, smooth communication with individuals from different cultural backgrounds requires not only verbal exchange but also an understanding of emotions and nonverbal cues. A system is needed to address this challenge and enable users to design appropriate communication strategies.

[0536] 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.

[0537] In this invention, the server includes means for collecting a wide range of information on different cultures and building a cultural knowledge base, means for collecting non-verbal emotional data in addition to user input information, and means for analyzing the information using natural language processing technology and identifying the user's emotional state using an emotion engine. This makes it possible to support users in implementing appropriate communication strategies across cultures.

[0538] "Different cultures" refer to cultures from different countries, regions, or social backgrounds, and mean that their cultural characteristics, values, and communication styles are diverse.

[0539] A "knowledge base" is a type of database that systematically organizes information and knowledge accumulated in a specific field, making it accessible as needed.

[0540] An "emotion engine" is a technical means by which a computer system recognizes emotions from a user's facial expressions and voice, and identifies their state.

[0541] "Natural language processing technology" is a technology that enables computers to understand and process human language, making it possible to analyze text and grasp its meaning.

[0542] A "generative AI model" refers to an algorithm that uses artificial intelligence to generate new data and information, especially text and images.

[0543] A "prompt sentence" is an example input or question used to extract specific information; it is a guiding sentence designed to help a generative AI model produce appropriate output.

[0544] "Feedback" is a response that provides information tailored to the user's actions and circumstances, encouraging further action or assisting in decision-making.

[0545] This invention provides a system for supporting intercultural communication. Its central components are a server, a terminal, and a user.

[0546] The server provides hardware and software for collecting, organizing, and analyzing large amounts of data related to different cultures. The cultural knowledge base functions as a constantly updated, complex database that draws information from a wide range of datasets. The server incorporates natural language processing technology and an emotion engine to analyze user-submitted text and non-verbal information (facial expressions, voice). The emotion engine is specifically designed to identify the user's emotional state and performs real-time sentiment analysis using advanced algorithms.

[0547] Users access the system through devices such as mobile phones and personal computers, and input and retrieve necessary information. These devices provide an interface for sending and receiving data with the server, and are equipped with devices for acquiring non-verbal information, such as cameras and microphones, which play a role in improving the accuracy of user sentiment data.

[0548] The generative AI model facilitates communication by generating prompts from analyzed data and providing them to the user. These prompts are optimized according to the user's situation, helping to bridge communication gaps across cultures. A specific example might be a prompt such as, "In business negotiations, please propose strategies to ease tensions, taking into account the cultural differences between Japanese and French companies." This prompt reflects the user's actual situation and provides guidance for offering more appropriate communication strategies.

[0549] Based on the hardware and software configuration described above, this system functions as a powerful tool to support effective intercultural communication.

[0550] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0551] Step 1:

[0552] The server collects comprehensive information related to different cultures. Input data includes cultural datasets and literature, which are used to build and update the database. Features are extracted from the datasets and aggregated as a cultural knowledge base, generating structured data that can be quickly referenced as needed.

[0553] Step 2:

[0554] The user connects to the system via a terminal and provides text-based input information. The terminal uses its camera and microphone to collect non-verbal information such as the user's voice and facial expressions, and sends it to the server. The input consists of text information and non-verbal hints, and this data is used in the next analysis step.

[0555] Step 3:

[0556] The server uses natural language processing technology to analyze the user's text information. Simultaneously, an emotion engine identifies the user's emotional state based on voice and facial expression data. It processes the input text data and nonverbal information and performs data analysis to understand the user's cultural background and emotional situation.

[0557] Step 4:

[0558] The server generates an optimal communication strategy based on the user's emotions and cultural knowledge base. This strategy is constructed from analyzed data and forms a dialogue plan that takes into account the user's current emotional state. The generated strategy is stored within the system and output in an executable format.

[0559] Step 5:

[0560] The terminal presents the user with a communication strategy received from the server. This includes prompts constructed using a generative AI model. The output consists of practical advice and suggestions tailored to the user's situation, presented in a format that is easy for the user to understand and act upon.

[0561] Step 6:

[0562] Users effectively communicate across cultures by following the suggested proposals and prompts. A feedback function provides real-time advice and suggestions for improvement based on the user's communication actions. This enables flexible responses tailored to different genres and situations.

[0563] (Application Example 2)

[0564] 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."

[0565] Cultural misunderstandings and emotional stress can arise in intercultural communication. In such situations, smooth dialogue and cooperation become difficult, creating a need for technologies that efficiently and consistently support intercultural communication.

[0566] 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.

[0567] In this invention, the server includes means for collecting information related to different cultures, means for analyzing user input using natural language processing technology to understand the cultural background, and means for analyzing the user's emotional state using emotion analysis technology and providing suggestions appropriate to the emotion based on the analysis results. This reduces misunderstandings and stress between cultures, enabling users to communicate with peace of mind.

[0568] A "system that supports intercultural communication" is a technology that helps people from different cultural backgrounds communicate smoothly with each other.

[0569] "Means of collecting information related to different cultures" refers to technologies that comprehensively collect data on different cultures and form a cultural knowledge base.

[0570] "Natural language processing technology" is a computer technology that analyzes user input to understand its meaning and cultural background.

[0571] "Emotional analysis technology" is a technology that evaluates and analyzes the emotional state of a user.

[0572] "Means of generating communication strategies" are techniques for proposing appropriate communication methods based on cultural background and emotional states.

[0573] "Means of providing proposals" refers to technologies that present generated communication strategies to users and help them in actual conversations.

[0574] In one embodiment of this invention, the intercultural communication support system consists of a server, a terminal, and a user.

[0575] The server comprehensively collects information related to different cultures and builds it into a cultural knowledge base. This base structures information on common misunderstandings between cultures and culture-specific communication styles. Furthermore, it analyzes the user's emotional state using sentiment analysis techniques. Specifically, the server integrates natural language processing and sentiment analysis techniques to analyze user input. Specific software used includes, for example, the Hugging Face Transformers library.

[0576] The device receives input from the user and also acquires nonverbal cues such as voice and facial expressions through the camera and microphone. This nonverbal information is used for emotion analysis, contributing to a detailed analysis of the user's emotional state.

[0577] Users interact with the system via their devices. Based on the analysis results, the system generates appropriate communication strategies tailored to the user's cultural background and emotional state, and provides this feedback to the user. This feedback helps users engage in cross-cultural interactions more smoothly and with greater confidence.

[0578] For example, if a user is speaking with a foreign client in a business meeting, the suggestions they receive might represent various strategies to mitigate cultural differences and facilitate effective communication.

[0579] The following prompt statements are possible inputs for a generative AI model:

[0580] Context: I am talking to someone from another country in a business meeting.

[0581] Input: "How should I respond when I encounter expressions specific to a different culture in a conversation?"

[0582] This allows users to leverage system suggestions and facilitate smooth, real-time cross-cultural communication.

[0583] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0584] Step 1:

[0585] The device receives voice input from the user and captures the voice data through the microphone. The voice data is converted to text using the Speech Recognition library. This converted text becomes the input for subsequent analysis processes.

[0586] Step 2:

[0587] The device captures the user's facial expressions through its camera and acquires them as image data using the OpenCV library. The acquired image data is then used as input for emotion analysis.

[0588] Step 3:

[0589] The server performs natural language processing on the acquired text data using the Hugging Face Transformers library. It understands the cultural background and context from the text content and obtains the analysis results. These analysis results become input for the next sentiment analysis step.

[0590] Step 4:

[0591] The server utilizes emotion analysis technology to evaluate the user's emotional state from input text and image data. In this process, the emotion engine specifically identifies the user's emotions and obtains analysis results. These results serve as output to deepen our understanding of the user's internal state.

[0592] Step 5:

[0593] The server generates an optimal communication strategy based on the analyzed cultural and emotional data. This strategy serves as a guideline for providing users with relevant suggestions using a generative AI model.

[0594] Step 6:

[0595] The terminal displays the communication strategy received from the server to the user. The user can use this feedback to facilitate smooth cross-cultural communication. Specific suggestions include appropriate expressions and dialogue techniques that take the other party's culture into consideration.

[0596] This series of processes enables users to avoid cross-cultural misunderstandings in real time and facilitate smooth communication.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] [Fourth Embodiment]

[0601] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0602] 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.

[0603] 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).

[0604] 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.

[0605] 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.

[0606] 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).

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] 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".

[0614] The intercultural communication support system according to the present invention is a system based on the collection of intercultural information and the analysis of user input, and is implemented as follows.

[0615] The server collects vast amounts of information about different cultures from the internet and specialized databases to build a cultural knowledge base. This knowledge base includes common customs, business etiquette, and communication styles to be aware of in different cultural spheres.

[0616] The user accesses the system using a terminal and inputs information about their own cultural background and the cultural background of the person they wish to communicate with into the server. The terminal receives the input from the user and sends it to the server.

[0617] The server analyzes the received user input using natural language processing technology to understand the user's intentions and emotions. Based on this, the server identifies potential challenges related to cross-cultural communication, references relevant information from its knowledge base, and generates the optimal communication strategy for the user.

[0618] The terminal receives suggestions from the server and presents them to the user visually or audibly. Based on this information, the user can choose appropriate actions and engage in cross-cultural communication.

[0619] As a concrete example, consider a business meeting between a Japanese company and a British company. The user inputs a request via their device to review basic business etiquette related to Japanese culture. The server uses natural language processing technology to analyze the user's input and provides information about how to show respect and the importance of exchanging business cards in Japanese business culture. This information is presented to the user via their device, enabling them to adopt appropriate attitudes and behaviors during the meeting.

[0620] Furthermore, after the meeting, the device can display feedback on the user's communication behavior and suggest areas for improvement and success stories for the next meeting, thereby continuously improving the user's cross-cultural understanding.

[0621] The following describes the processing flow.

[0622] Step 1:

[0623] The server collects information about different cultures from the internet and specialized databases, and stores it as a cultural knowledge base. This knowledge base includes information on cultural customs, business etiquette, and communication styles from around the world.

[0624] Step 2:

[0625] Users access the system through a terminal. The terminal provides an interface that receives questions from the user regarding communication methods based on the other party's culture and specific situations.

[0626] Step 3:

[0627] The device sends the user's question to the server. The question includes information about the user's cultural background and the cultural background of the person they wish to communicate with.

[0628] Step 4:

[0629] The server receives user input data sent from the terminal and analyzes its content using natural language processing technology. This allows it to identify the user's intentions and emotions, and pinpoint communication challenges in light of their cultural background.

[0630] Step 5:

[0631] The server extracts relevant information from its knowledge base based on the analysis results and generates an optimal communication strategy for the user. This strategy includes specific language choices and guidelines for action.

[0632] Step 6:

[0633] The server sends the generated communication strategy to the terminal. The terminal presents this proposal to the user visually or audibly.

[0634] Step 7:

[0635] Users refer to the information presented on their devices and take appropriate actions in real-world communication scenarios.

[0636] Step 8:

[0637] After the conversation ends, the device provides feedback based on the user's choices and actions. This feedback includes successes and areas for improvement, serving as guidance for future communication.

[0638] (Example 1)

[0639] 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".

[0640] In intercultural communication, it is essential to mitigate misunderstandings and friction arising from differences in cultural backgrounds. However, traditional methods have struggled to efficiently collect and analyze detailed information about each culture, resulting in a lack of timely provision of concrete strategies for users to facilitate smooth intercultural communication.

[0641] 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.

[0642] In this invention, the server includes means for collecting information on different cultures from a global information network and specialized information sources, means for forming a cultural knowledge base based on the collected information, means for using natural language processing technology to receive and analyze user information, and means for presenting the generated dialogue strategy to the user visually or audibly. This enables the user to obtain an effective cross-cultural communication strategy.

[0643] "Information about different cultures" is a general term encompassing customs, social norms, business etiquette, and communication styles related to diverse cultures around the world.

[0644] A "global information network" refers to a globally accessible information network that utilizes the internet.

[0645] A "specialized information source" refers to a reliable source that provides highly specialized knowledge and data on a particular field or topic.

[0646] A "cultural knowledge base" is a structured collection of knowledge generated from collected culture-related information, which is used to support intercultural understanding.

[0647] A "user" is an individual or organization that inputs information and receives results through an intercultural communication support system.

[0648] "Natural language processing technology" is a technology that uses computers to process and analyze human language in order to understand its meaning.

[0649] A "generative model" refers to an algorithm that automatically generates dialogue strategies and information based on input data.

[0650] A "dialogue strategy" refers to a set of planned guidelines and methods for effectively conducting communication with a specific purpose.

[0651] "Means of visual or auditory presentation" refers to methods of providing information to users in a form that they can see or hear through displays, speakers, etc.

[0652] The intercultural communication support system according to the present invention is specifically implemented based on the collection of intercultural information and the analysis of user input. The embodiments of this system are described in detail below.

[0653] The server collects information on different cultures from a global information network and specialized information sources. Specifically, it can obtain culture-related data using, for example, a web scraping program developed in Python. Based on the collected data, this server forms a cultural knowledge base and stores it in a MySQL database, thereby building a vast information resource for intercultural understanding.

[0654] Users access the system through their terminal and input information about their own cultural background and the cultural background of the other party. This input information is provided in text format, for example, in a form on a web browser, such as "I come from an Asian cultural background and I am collaborating with European partners." The terminal sends the acquired user input information to the server, where it is processed.

[0655] The server uses natural language processing techniques to process the received input information. This process utilizes natural language processing libraries such as spaCy and Transformers to analyze the user's intent and emotions. Furthermore, a generative AI model generates the optimal communication strategy for the user. This ensures that the user receives specific and appropriate cultural characteristics and advice to be mindful of during interactions.

[0656] The generated communication strategy is presented to the user visually or audibly via the device. For example, the display might show information such as, "In European business meetings, direct and clear communication is preferred." Users can use this information to facilitate smooth communication across cultures.

[0657] As a concrete example, in a business meeting between a Japanese company and a British company, the user enters a prompt message via their terminal saying, "I would like to learn about British business etiquette." In response, the server generates a strategy such as, "In British culture, prior confirmation via email is important, and limited body language is recommended during conversations," and presents it to the user. In this way, the present invention effectively supports the user's cross-cultural adaptation and successful communication.

[0658] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0659] Step 1:

[0660] The server collects information about different cultures from global information networks such as the internet and specialized information sources. This information includes the unique customs and communication styles of each cultural sphere. This collection utilizes web scraping techniques, and sometimes data is obtained from APIs. The input is keywords related to a specific culture, and the output is raw data to form a cultural knowledge base.

[0661] Step 2:

[0662] The server analyzes the collected raw data and builds a cultural knowledge base. Specifically, it uses database software to classify the collected data by cultural area and extracts cultural features and patterns by performing text mining as needed. The input is raw data, and the output is a structured knowledge base.

[0663] Step 3:

[0664] Users input information about their own cultural background and the cultural background of the other party through their device. This is usually entered in text format into a web form. This information indicates the user's intentions and the background of the communication they seek, and the device sends this input to the server. The input is the user's cultural background information, and the output is data prepared for natural language processing.

[0665] Step 4:

[0666] The server analyzes the received user information using natural language processing techniques. Here, existing libraries (e.g., spaCy and Transformers) are used to understand the user's intent and sentiment in relation to the input text. The input is the text sent by the user, and the output is the analyzed intent and sentiment data.

[0667] Step 5:

[0668] The server utilizes a generative AI model based on user intent and sentiment data to generate appropriate communication strategies. This generation process combines predictive algorithms with information from a knowledge base to derive specific action guidelines and advice. The input is analyzed intent and sentiment data, and the output is a specific communication strategy.

[0669] Step 6:

[0670] The terminal presents the communication strategy received from the server to the user visually or audibly. This is achieved by displaying information on a screen or by using speech synthesis to read the content aloud. The input is the generated communication strategy, and the output is the information presented to the user visually or audibly.

[0671] Step 7:

[0672] Users engage in cross-cultural communication based on communication strategies presented by the system. They then provide feedback on their communication through the device. The input is feedback based on the user's real-world experience, and the output is used to identify areas for improvement and identify success stories for future interactions.

[0673] (Application Example 1)

[0674] 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".

[0675] In situations requiring intercultural communication, interactions between individuals with different cultural backgrounds can sometimes lead to insufficient understanding or misunderstandings. Therefore, there is a need for systems that support smoother and more accurate communication. In particular, in autonomous vehicles, providing guidance and information tailored to the cultural backgrounds of passengers is a challenge.

[0676] 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.

[0677] In this invention, the server includes means for collecting information about different cultures, means for analyzing user input using natural language processing technology to understand the cultural background, and means for generating an appropriate communication strategy based on the analysis results. This makes it possible to optimize voice guidance in autonomous vehicles while taking into account different cultural backgrounds.

[0678] "Information about different cultures" is a general term encompassing customs, values, and communication styles in different cultural spheres.

[0679] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0680] "Cultural background" refers to the characteristics and historical influences of the culture to which individuals belong.

[0681] A "communication strategy" refers to the methods of contact and information transmission established to facilitate smooth intercultural exchange.

[0682] "Optimizing voice guidance" means providing optimal voice guidance tailored to the characteristics of the user and the environment.

[0683] A "knowledge base" is a database that structurally organizes information and data, and aggregates knowledge related to a specific field.

[0684] The system for realizing this invention optimizes voice guidance within an autonomous vehicle according to the cultural background of the passengers, in order to support intercultural communication.

[0685] The server collects information on different cultures from the internet and specialized databases to build a cultural knowledge base. Using a natural language processing engine (e.g., Google Cloud Natural Language API), it analyzes the user's voice input to understand their intent and emotions. Based on the analyzed information, the server generates an appropriate communication strategy and optimizes voice guidance. The generated guidance is presented to passengers via the in-vehicle computer through displays and voice systems.

[0686] The terminal uses a voice recognition microphone to receive cultural background information and navigation needs entered by the user via voice. This input is sent to a server for analysis.

[0687] As a concrete example, if a Japanese tourist boards an autonomous vehicle in an international tourist destination, this system can provide audio guidance about local cultural customs and tourist attractions. This allows passengers to enjoy a comfortable and easy-to-understand navigation experience.

[0688] An example of a prompt sentence for a generative AI model is, "The passenger on the train is from Japan. Please provide helpful cultural advice for this country."

[0689] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0690] Step 1:

[0691] The device receives voice input from the user using a voice recognition microphone. This input includes the user's cultural background information and navigation preferences. The device converts this voice into a digital signal and sends it to the server.

[0692] Step 2:

[0693] The server analyzes the received digital audio signal using a natural language processing engine and converts it into text data. This provides information to understand the user's intent, emotions, and cultural background. The analyzed text data is then compared with a knowledge base.

[0694] Step 3:

[0695] The server references a knowledge base and generates an appropriate communication strategy based on the user's cultural background. This strategy includes information on cultural etiquette and tourist information. A generative AI model is used to formulate specific guidance content.

[0696] Step 4:

[0697] The server determines the content of the voice guidance based on the generated communication strategy and generates digital voice data. This data is output as guidance information via the in-vehicle computer.

[0698] Step 5:

[0699] The terminal provides passengers with voice guidance through the vehicle's speaker system. Through this voice guidance, users can receive appropriate cultural and tourist information, allowing them to travel to their destination with peace of mind.

[0700] 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.

[0701] The intercultural communication support system according to the present invention achieves advanced communication support that takes emotional elements into consideration by combining it with an emotion engine. An embodiment thereof is shown below.

[0702] The server first comprehensively collects information about different cultures to form a cultural knowledge base. This knowledge base structures detailed information about common misunderstandings that occur between cultures and culture-specific communication styles. Meanwhile, an emotion engine is built into the system to appropriately analyze the user's emotional state.

[0703] The user connects to the system via a terminal. The terminal transmits not only user input information but also non-verbal cues such as voice and facial expressions using the camera and microphone to the emotion engine. This process allows the user to receive appropriate support even in situations involving emotions such as anxiety, tension, or joy.

[0704] The server uses natural language processing technology to analyze information received from users, performing sentiment analysis in parallel with understanding the cultural background. Specifically, it derives communication strategies that match the user's emotional state from a knowledge base and generates optimal suggestions that take into account the cultural background and emotional state.

[0705] The terminal receives instructions from the server and presents the user with an appropriate communication strategy. Here, it can provide feedback that aligns with the user's emotions, creating a sense of security while assisting in problem-solving.

[0706] As a concrete example, consider a scenario where a Japanese company and a French company are conducting business negotiations. When a user finds it difficult to reconcile the Japanese politeness with the French intuitive negotiation style, they use the terminal to request support from the server. The server analyzes the user's emotions and suggests relaxed expressions of respect and presentation methods to alleviate tension. These suggestions are communicated to the user via the terminal, making it easier for the user to proceed with negotiations based on them.

[0707] In this way, this system, which combines emotional engines, provides support adapted to cultural and emotional backgrounds, embodying a practical means of facilitating smooth intercultural communication.

[0708] The following describes the processing flow.

[0709] Step 1:

[0710] The server collects information about different cultures from the internet and specialized databases to form a cultural knowledge base. This knowledge base includes customs, communication styles, and important manners specific to each culture.

[0711] Step 2:

[0712] Users access the system through a terminal and input the necessary information and support requests. The terminal provides an interface that accepts the user's cultural background and the topics they wish to learn about.

[0713] Step 3:

[0714] The device records the user's emotional state by capturing the user's voice input and facial expressions through the camera and microphone, and sending them to the emotion engine.

[0715] Step 4:

[0716] The server uses natural language processing technology to analyze user information and sentiment data obtained from the terminal. It understands the user's intentions and emotions and identifies potential communication challenges based on this understanding.

[0717] Step 5:

[0718] The emotion engine analyzes emotions from collected facial expression data and audio to determine whether the user is feeling anxiety, tension, or other similar emotions. This result influences the server's decision-making process.

[0719] Step 6:

[0720] Based on analysis results and sentiment data, the server derives the optimal communication strategy for the user from its knowledge base. This strategy is tailored to the user's emotional state and cultural background.

[0721] Step 7:

[0722] The server sends the generated communication strategy to the terminal. The terminal presents this strategy to the user visually or audibly, supporting the user's communication actions.

[0723] Step 8:

[0724] Users utilize the information presented on their devices and engage in dialogue with others according to the suggested communication strategy.

[0725] Step 9:

[0726] After a conversation or interaction ends, the device provides the user with feedback, including sentiment analysis results. This feedback allows the user to identify areas for improvement and successful examples in their communication style.

[0727] (Example 2)

[0728] 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".

[0729] In intercultural communication, overcoming cultural misunderstandings and emotional gaps presents a significant challenge. In particular, smooth communication with individuals from different cultural backgrounds requires not only verbal exchange but also an understanding of emotions and nonverbal cues. A system is needed to address this challenge and enable users to design appropriate communication strategies.

[0730] 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.

[0731] In this invention, the server includes means for collecting a wide range of information on different cultures and building a cultural knowledge base, means for collecting non-verbal emotional data in addition to user input information, and means for analyzing the information using natural language processing technology and identifying the user's emotional state using an emotion engine. This makes it possible to support users in implementing appropriate communication strategies across cultures.

[0732] "Different cultures" refer to cultures from different countries, regions, or social backgrounds, and mean that their cultural characteristics, values, and communication styles are diverse.

[0733] A "knowledge base" is a type of database that systematically organizes information and knowledge accumulated in a specific field, making it accessible as needed.

[0734] An "emotion engine" is a technical means by which a computer system recognizes emotions from a user's facial expressions and voice, and identifies their state.

[0735] "Natural language processing technology" is a technology that enables computers to understand and process human language, making it possible to analyze text and grasp its meaning.

[0736] A "generative AI model" refers to an algorithm that uses artificial intelligence to generate new data and information, especially text and images.

[0737] A "prompt sentence" is an example input or question used to extract specific information; it is a guiding sentence designed to help a generative AI model produce appropriate output.

[0738] "Feedback" is a response that provides information tailored to the user's actions and circumstances, encouraging further action or assisting in decision-making.

[0739] This invention provides a system for supporting intercultural communication. Its central components are a server, a terminal, and a user.

[0740] The server provides hardware and software for collecting, organizing, and analyzing large amounts of data related to different cultures. The cultural knowledge base functions as a constantly updated, complex database that draws information from a wide range of datasets. The server incorporates natural language processing technology and an emotion engine to analyze user-submitted text and non-verbal information (facial expressions, voice). The emotion engine is specifically designed to identify the user's emotional state and performs real-time sentiment analysis using advanced algorithms.

[0741] Users access the system through devices such as mobile phones and personal computers, and input and retrieve necessary information. These devices provide an interface for sending and receiving data with the server, and are equipped with devices for acquiring non-verbal information, such as cameras and microphones, which play a role in improving the accuracy of user sentiment data.

[0742] The generative AI model facilitates communication by generating prompts from analyzed data and providing them to the user. These prompts are optimized according to the user's situation, helping to bridge communication gaps across cultures. A specific example might be a prompt such as, "In business negotiations, please propose strategies to ease tensions, taking into account the cultural differences between Japanese and French companies." This prompt reflects the user's actual situation and provides guidance for offering more appropriate communication strategies.

[0743] Based on the hardware and software configuration described above, this system functions as a powerful tool to support effective intercultural communication.

[0744] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0745] Step 1:

[0746] The server collects comprehensive information related to different cultures. Input data includes cultural datasets and literature, which are used to build and update the database. Features are extracted from the datasets and aggregated as a cultural knowledge base, generating structured data that can be quickly referenced as needed.

[0747] Step 2:

[0748] The user connects to the system via a terminal and provides text-based input information. The terminal uses its camera and microphone to collect non-verbal information such as the user's voice and facial expressions, and sends it to the server. The input consists of text information and non-verbal hints, and this data is used in the next analysis step.

[0749] Step 3:

[0750] The server uses natural language processing technology to analyze the user's text information. Simultaneously, an emotion engine identifies the user's emotional state based on voice and facial expression data. It processes the input text data and nonverbal information and performs data analysis to understand the user's cultural background and emotional situation.

[0751] Step 4:

[0752] The server generates an optimal communication strategy based on the user's emotions and cultural knowledge base. This strategy is constructed from analyzed data and forms a dialogue plan that takes into account the user's current emotional state. The generated strategy is stored within the system and output in an executable format.

[0753] Step 5:

[0754] The terminal presents the user with a communication strategy received from the server. This includes prompts constructed using a generative AI model. The output consists of practical advice and suggestions tailored to the user's situation, presented in a format that is easy for the user to understand and act upon.

[0755] Step 6:

[0756] Users effectively communicate across cultures by following the suggested proposals and prompts. A feedback function provides real-time advice and suggestions for improvement based on the user's communication actions. This enables flexible responses tailored to different genres and situations.

[0757] (Application Example 2)

[0758] 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".

[0759] Cultural misunderstandings and emotional stress can arise in intercultural communication. In such situations, smooth dialogue and cooperation become difficult, creating a need for technologies that efficiently and consistently support intercultural communication.

[0760] 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.

[0761] In this invention, the server includes means for collecting information related to different cultures, means for analyzing user input using natural language processing technology to understand the cultural background, and means for analyzing the user's emotional state using emotion analysis technology and providing suggestions appropriate to the emotion based on the analysis results. This reduces misunderstandings and stress between cultures, enabling users to communicate with peace of mind.

[0762] A "system that supports intercultural communication" is a technology that helps people from different cultural backgrounds communicate smoothly with each other.

[0763] "Means of collecting information related to different cultures" refers to technologies that comprehensively collect data on different cultures and form a cultural knowledge base.

[0764] "Natural language processing technology" is a computer technology that analyzes user input to understand its meaning and cultural background.

[0765] "Emotional analysis technology" is a technology that evaluates and analyzes the emotional state of a user.

[0766] "Means of generating communication strategies" are techniques for proposing appropriate communication methods based on cultural background and emotional states.

[0767] "Means of providing proposals" refers to technologies that present generated communication strategies to users and help them in actual conversations.

[0768] In one embodiment of this invention, the intercultural communication support system consists of a server, a terminal, and a user.

[0769] The server comprehensively collects information related to different cultures and builds it into a cultural knowledge base. This base structures information on common misunderstandings between cultures and culture-specific communication styles. Furthermore, it analyzes the user's emotional state using sentiment analysis techniques. Specifically, the server integrates natural language processing and sentiment analysis techniques to analyze user input. Specific software used includes, for example, the Hugging Face Transformers library.

[0770] The device receives input from the user and also acquires nonverbal cues such as voice and facial expressions through the camera and microphone. This nonverbal information is used for emotion analysis, contributing to a detailed analysis of the user's emotional state.

[0771] Users interact with the system via their devices. Based on the analysis results, the system generates appropriate communication strategies tailored to the user's cultural background and emotional state, and provides this feedback to the user. This feedback helps users engage in cross-cultural interactions more smoothly and with greater confidence.

[0772] For example, if a user is speaking with a foreign client in a business meeting, the suggestions they receive might represent various strategies to mitigate cultural differences and facilitate effective communication.

[0773] The following prompt statements are possible inputs for a generative AI model:

[0774] Context: I am talking to someone from another country in a business meeting.

[0775] Input: "How should I respond when I encounter expressions specific to a different culture in a conversation?"

[0776] This allows users to leverage system suggestions and facilitate smooth, real-time cross-cultural communication.

[0777] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0778] Step 1:

[0779] The device receives voice input from the user and captures the voice data through the microphone. The voice data is converted to text using the Speech Recognition library. This converted text becomes the input for subsequent analysis processes.

[0780] Step 2:

[0781] The device captures the user's facial expressions through its camera and acquires them as image data using the OpenCV library. The acquired image data is then used as input for emotion analysis.

[0782] Step 3:

[0783] The server performs natural language processing on the acquired text data using the Hugging Face Transformers library. It understands the cultural background and context from the text content and obtains the analysis results. These analysis results become input for the next sentiment analysis step.

[0784] Step 4:

[0785] The server utilizes emotion analysis technology to evaluate the user's emotional state from input text and image data. In this process, the emotion engine specifically identifies the user's emotions and obtains analysis results. These results serve as output to deepen our understanding of the user's internal state.

[0786] Step 5:

[0787] The server generates an optimal communication strategy based on the analyzed cultural and emotional data. This strategy serves as a guideline for providing users with relevant suggestions using a generative AI model.

[0788] Step 6:

[0789] The terminal displays the communication strategy received from the server to the user. The user can use this feedback to facilitate smooth cross-cultural communication. Specific suggestions include appropriate expressions and dialogue techniques that take the other party's culture into consideration.

[0790] This series of processes enables users to avoid cross-cultural misunderstandings in real time and facilitate smooth communication.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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."

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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 as being incorporated by reference.

[0812] The following is further disclosed regarding the embodiments described above.

[0813] (Claim 1)

[0814] To support intercultural communication,

[0815] Means of collecting information about different cultures,

[0816] A means of understanding cultural background by analyzing user input using natural language processing technology,

[0817] A means of generating an appropriate communication strategy based on the analysis results,

[0818] A means of presenting the generated strategy to the user,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, further comprising means for generating and presenting feedback based on the communication behavior selected by the user.

[0822] (Claim 3)

[0823] The system according to claim 1, further comprising means for building and updating a knowledge base on different cultures.

[0824] "Example 1"

[0825] (Claim 1)

[0826] Means of gathering information on different cultures from global information networks and specialized information sources,

[0827] A means of forming a cultural knowledge base based on collected information,

[0828] A means of receiving and analyzing user information using natural language processing technology,

[0829] A means of using a generative model to generate appropriate dialogue strategies, taking into account the cultural background and objectives of the users,

[0830] A means of presenting the generated dialogue strategy to the user visually or audibly,

[0831] A system that includes this.

[0832] (Claim 2)

[0833] The system according to claim 1, further comprising means for generating and providing improvements or success stories in response to the user's selected dialogue actions.

[0834] (Claim 3)

[0835] The system according to claim 1, further comprising means for maintaining and dynamically updating a knowledge base of different cultures.

[0836] "Application Example 1"

[0837] (Claim 1)

[0838] To support intercultural communication,

[0839] Means of collecting information about different cultures,

[0840] A means of understanding cultural background by analyzing user input using natural language processing technology,

[0841] A means of generating an appropriate communication strategy based on the analysis results,

[0842] A means of presenting the generated strategy to the user,

[0843] Means for optimizing audio guidance based on the cultural background of passengers,

[0844] A system that includes this.

[0845] (Claim 2)

[0846] The system according to claim 1, further comprising means for generating and presenting feedback based on the communication behavior selected by the user.

[0847] (Claim 3)

[0848] The system according to claim 1, further comprising means for building and updating a knowledge base on different cultures.

[0849] "Example 2 of combining an emotion engine"

[0850] (Claim 1)

[0851] A means of collecting information on different cultures from a wide range of perspectives and building a cultural knowledge base,

[0852] In addition to user input information, a means of collecting nonverbal emotional data,

[0853] A means of analyzing information using natural language processing technology and identifying the user's emotional state using an emotion engine,

[0854] Based on the analyzed data and knowledge base, we generate and present appropriate communication strategies to users.

[0855] A means of creating prompt sentences using a generative AI model to support user communication,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, further comprising means for generating and presenting feedback in an emotionally sensitive manner based on the user's selected communication behaviors or states.

[0859] (Claim 3)

[0860] The system according to claim 1, further comprising means for continuously maintaining an updatable cross-cultural knowledge base.

[0861] "Application example 2 when combining with an emotional engine"

[0862] (Claim 1)

[0863] To support intercultural communication,

[0864] Means of collecting information related to different cultures,

[0865] A means of understanding cultural background by analyzing user input using natural language processing technology,

[0866] A means of generating an appropriate communication strategy based on the analysis results,

[0867] A means of presenting the generated strategy to the user,

[0868] A means of analyzing a user's emotional state using emotion analysis technology and providing suggestions appropriate to their emotions based on the analysis results,

[0869] A system that includes this.

[0870] (Claim 2)

[0871] The system according to claim 1, further comprising means for generating and presenting feedback based on the communication behavior selected by the user.

[0872] (Claim 3)

[0873] The system according to claim 1, further comprising means for building and updating a knowledge base on different cultures. [Explanation of Symbols]

[0874] 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. To support intercultural communication, Means of collecting information about different cultures, A means of understanding cultural background by analyzing user input using natural language processing technology, A means of generating an appropriate communication strategy based on the analysis results, A means of presenting the generated strategy to the user, Means for optimizing audio guidance based on the cultural background of passengers, A system that includes this.

2. The system according to claim 1, further comprising means for generating and presenting feedback based on the communication behavior selected by the user.

3. The system according to claim 1, further comprising means for building and updating a knowledge base concerning different cultures.

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