system

Abstract

We provide the system. [Solution] A method for performing translation and interpretation in real time using a natural language processing engine, A means of collecting and analyzing market data to propose the optimal business strategy, A means of explaining laws and cultural practices by referring to databases on laws and culture, A means of identifying and listing potential partners who meet the business requirements, A means of analyzing user dialogue input and presenting problem-solving solutions, 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, the method 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] When small and medium-sized enterprises enter overseas markets, it is necessary to solve a variety of problems such as language barriers, cultural differences, complex regulations, and selection of local partners. In addition, since it is costly to hire experts to address these problems, there is a need to provide a means to support them cost-effectively.

Means for Solving the Problems

[0005] This invention provides a system equipped with real-time translation and interpretation using a natural language processing engine, market data analysis using machine learning, and an information provision method utilizing a database of laws and cultures. Based on the user's specific business conditions, this system matches them with appropriate local partners and provides immediate solutions to business challenges through interactive support. This enables comprehensive and cost-effective support for small and medium-sized enterprises expanding overseas.

[0006] A "natural language processing engine" is software that analyzes the language input by the user and accurately translates or interprets it into a different language.

[0007] "Market data" is a general term for information regarding economic trends, competitive landscape, and consumer behavior in a specific region or industry.

[0008] A "machine learning algorithm" is a technology that uses large amounts of data to enable computers to automatically learn patterns and rules, and then make predictions and decisions.

[0009] A "database" is a collection of information systematically organized for a specific purpose, and a system for quickly searching for and retrieving that information.

[0010] The term "potential partner" refers to companies or individuals that meet the business requirements and have the potential to work together.

[0011] "Interactive support" is a method of assistance in which the user and the computer interact back and forth to identify problems and suggest solutions. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] 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. Further, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] 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.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. 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).

[0019] 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."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] The system of this invention provides multifaceted support for the challenges faced by small and medium-sized enterprises (SMEs) in expanding overseas. The system operates based on three main elements: server, terminal, and user.

[0034] The server, at the core of the system, uses a natural language processing engine to translate text sent by users in real time, providing interpretation services. If a user inputs a business document in Japanese, the server translates it into the specified language and sends the translation result to the terminal. This process enables communication that transcends language barriers.

[0035] The server also has the capability to analyze market data. When a user requests information on a specific market, the server collects a vast amount of relevant data sets and performs analysis using machine learning algorithms. The analysis results are displayed visually on the user's device, supporting strategic business decisions.

[0036] The terminal functions as the user interface, accepting user input and displaying information from the server. When a user asks a question about a specific law or culture, the terminal sends a request to the server and presents the user with the information provided by the server. This makes it easier to understand local business customs and legal regulations.

[0037] Furthermore, the server has a function to match business partners. The server identifies partners that meet the user's requirements and provides the user with a list of evaluated candidates via the terminal. This allows users to efficiently find trustworthy partners.

[0038] As an interactive support system, the server analyzes user input using a machine learning model and immediately provides necessary solutions. When a user enters a specific business problem, the server retrieves appropriate past cases and solutions and advises the user to quickly resolve the issue.

[0039] As described above, the present invention provides comprehensive support in the areas of language, information analysis, legal assistance, partnership formation, and problem solving, and can help support success in diverse overseas business environments.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] Users input the information and actions they require (translation, data analysis, legal compliance checks, partner search, consultation, etc.) through the system's terminal.

[0043] Step 2:

[0044] The terminal receives user input and sends it to the server as a request in the appropriate format.

[0045] Step 3:

[0046] The server receives the request and selects the appropriate process. For example, if translation is needed, it calls natural language processing; if data analysis is needed, it calls a data analysis algorithm.

[0047] Step 4:

[0048] The server executes the specified process. For translation, it uses a natural language processing engine to translate the input text and generate an interpreted result. For data analysis, it analyzes relevant data using machine learning algorithms and generates market insights.

[0049] Step 5:

[0050] The server sends the generated results back to the terminal. This may include translation results, data analysis outputs, legal information, a list of potential partners, or problem solutions.

[0051] Step 6:

[0052] The terminal receives information from the server and displays it to the user. The user can then decide on their next action based on the information provided.

[0053] Step 7:

[0054] If the user has further questions or requests, the process is repeated from step 1.

[0055] (Example 1)

[0056] 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."

[0057] Many businesses are currently attempting to enter international markets, but they face challenges such as language barriers, difficulty obtaining market information, selecting appropriate business partners, and a lack of understanding of local laws and cultures. This makes effective strategy formulation and rapid decision-making difficult. A comprehensive support system is needed to address these issues.

[0058] 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.

[0059] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market information to propose optimal business strategies, means for explaining legal regulations and cultural practices by referring to databases on laws and culture, and means for presenting the analysis results in a visual format. This enables smooth communication in international markets with diverse languages ​​and cultures, and allows for accurate and efficient decision-making.

[0060] A "natural language processing engine" is a technology that allows computers to understand human language and convert it into an executable form, enabling real-time translation and interpretation.

[0061] "Market information" refers to data such as consumer trends, competitive landscape, and economic indicators in a specific market, and is fundamental information necessary for formulating business strategies.

[0062] A "machine learning algorithm" is a data processing technique used to analyze large amounts of data, find patterns within it, and build predictive models.

[0063] A "database of laws and cultures" is a source of information that systematically accumulates and organizes information on the laws and cultural practices of various countries, and serves as a supplementary tool for users to understand laws and cultures.

[0064] A "business partner" refers to another organization or individual with whom a cooperative relationship is established when promoting a business, and who is a partner with whom efforts are made to improve operational efficiency and expand the market.

[0065] "Interactive input" refers to information input in the form of questions and answers that users make to a server or system, with the aim of solving problems or obtaining information.

[0066] "Visual format" refers to a method of presentation that displays information in a visual form, such as graphs, charts, and diagrams, to make it easier to understand intuitively.

[0067] This invention is a support system designed to remove various barriers for small and medium-sized enterprises (SMEs) operating in the international market. This system consists of three elements: a server, a terminal, and a user, which work together to realize the invention.

[0068] The server is equipped with a natural language processing engine and translates business-related information entered by users in real time. For example, if a user enters "New product sales strategy for the Italian market" in Japanese, the server will translate it into Italian. Open-source multilingual tools can be used as the natural language processing engine for translation. The server also collects market information from multiple data sources and analyzes it using machine learning algorithms. As a result, it provides users with insights into optimal business strategies. The server uses open-source data visualization libraries to present information visually.

[0069] The terminal is an interface for users to input information and for the server to visually display the information it provides. For example, a user can send a request to the server by typing "I want to find a distribution partner in France" into the terminal. The terminal displays the translation results and market analysis results provided by the server as graphs and charts, allowing users to intuitively grasp the information.

[0070] This system can also provide detailed information on laws and culture. By referencing a comprehensive database, the server can, for example, answer a user's question about "the procedures required to establish a company in Italy" by providing information on local laws and cultural practices.

[0071] Furthermore, the server also features a business partner matching function. If a user requests an "environmentally conscious partner," the server narrows down the candidates that meet the criteria and displays a list on the user's device. This allows users to quickly find reliable collaborators.

[0072] As a concrete example, a user can input a prompt message to the generated AI model such as, "I want to sell traditional Japanese crafts in the American market. Please tell me about market research and sales strategies," and receive comprehensive support through the collaboration between the server and the terminal.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The user inputs business-related information through the terminal. For example, a prompt message such as "Please tell me about the distribution strategy for a new product in the Italian market" is used as input. Once input is received, the terminal prepares to send this information to the server.

[0076] Step 2:

[0077] The server analyzes the user's input text received from the terminal using a natural language processing engine. The analyzed data is translated into the specified language as needed. For example, if the user inputs in Japanese, the server will translate it into Italian, English, or another language. The output is the translated text.

[0078] Step 3:

[0079] The server collects market information based on the translated prompt text. The server retrieves data related to the Italian market from the internet and internal databases. Input information includes specific keywords related to the target market. Output is a dataset of relevant market information.

[0080] Step 4:

[0081] The server analyzes collected market data using machine learning algorithms. For example, it predicts competitive landscapes and market demand. The input is market data, and the output is insights useful for business strategies. Specifically, data cleansing and model application are performed.

[0082] Step 5:

[0083] The server visualizes the analysis results and generates them as graphs and charts. This allows users to intuitively understand market conditions based on the visual data displayed on their devices. The input is analytical insights, and the output is visualized information.

[0084] Step 6:

[0085] The terminal displays analysis results and visualization data sent from the server to the user. The user can then make decisions based on this information. Specifically, the terminal performs data rendering on a digital screen.

[0086] (Application Example 1)

[0087] 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."

[0088] In today's global business environment, small and medium-sized enterprises (SMEs) face complex challenges such as language barriers, cultural differences, region-specific laws and regulations, and the analysis of diverse market data. In particular, effective communication across different language regions, strategic decision-making, and the development of optimal marketing strategies are significant obstacles to international success. In addition, they are required to quickly and reliably find business partners and efficiently integrate these processes.

[0089] 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.

[0090] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market data to propose optimal business strategies, means for explaining laws and cultural customs by referring to a database of laws and cultures, and means for optimizing advertising to generate sales strategies in multilingual markets. This enables smooth international business exchange that transcends language and cultural barriers, allowing users to accurately grasp the most important business opportunities and formulate accurate strategies that meet diverse market conditions.

[0091] A "natural language processing engine" is a technology that translates text data from users into multiple languages ​​and performs language conversion in real time.

[0092] "Market data collection and analysis methods" refer to the process of collecting data on market trends and consumer behavior, and using machine learning algorithms to propose optimal business strategies to users.

[0093] A "database of laws and culture" is a source of information that systematically organizes information on laws and cultural practices, and provides accurate information in response to user inquiries.

[0094] "Ad optimization methods for generating sales strategies in multilingual markets" refers to technologies that generate advertising content that takes into account the language and culture of each market and deliver it to the appropriate target audience.

[0095] "Methods for identifying potential business partners" refer to methods for selecting appropriate companies and individuals based on the user's business conditions and listing highly reliable partners.

[0096] "User dialogue input analysis means" refers to technology that analyzes questions and requests from users and quickly provides corresponding solutions.

[0097] This invention is primarily implemented using three elements: a server, a terminal, and a user. Its specific form is described below.

[0098] The server functions as the core of this system, using a natural language processing engine to translate and interpret text sent by users in real time. It utilizes the Google Translate API to facilitate communication between languages. Furthermore, the server collects market data, analyzes it using machine learning algorithms such as Scikit-learn, and visualizes and proposes optimal business strategies to users.

[0099] The terminal functions as the user interface, receiving user input and presenting information from the server. It utilizes React Native to enable cross-platform use. Through the terminal, users can ask questions about local laws and culture and receive information retrieved from the database.

[0100] This system enables users to develop effective sales strategies in different markets and optimize advertising in multilingual markets. Furthermore, AI-powered user dialogue analysis facilitates rapid problem-solving.

[0101] For example, if a user is planning to enter the Spanish market from Japan, this system can generate an advertising strategy in Spanish and perform targeting based on market analysis. When the user enters a prompt such as, "I want to launch this product in the Spanish market, but what points should I keep in mind when creating marketing emails in Spanish?", appropriate advice and past success stories will be provided.

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The user accesses an input screen via a terminal and enters information about the target market and language. The input data is specific to the region where the user plans to expand. The text entered here is sent from the terminal to the server.

[0105] Step 2:

[0106] The server passes the received text data to a natural language processing engine for analysis. The purpose of this analysis is to understand the user's input and identify the requested translation or market information. As a result, the server obtains the translated text or market data to be analyzed.

[0107] Step 3:

[0108] The server collects market data and analyzes it using machine learning algorithms. Specifically, it applies statistical methods using Scikit-learn to analyze trends and competitive information in the user-specified market. As a result of the analysis, business insights tailored to the user's needs are generated.

[0109] Step 4:

[0110] The server generates advertising content based on collected and analyzed data to optimize sales strategies in multilingual markets. Ad copy and promotional content are created using a generative AI model, resulting in the construction of optimal advertising messages for the target market.

[0111] Step 5:

[0112] The terminal displays results sent from the server, presenting the user with the most suitable translation, marketing strategy, and market insights. This allows the user to determine what specific actions they should take. Furthermore, if the user has additional questions or wishes to make corrections, they can resend the information to the server through the terminal.

[0113] 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.

[0114] The system of this invention is designed as a multi-functional agent to support small and medium-sized enterprises in entering overseas markets. This system operates based on a server, terminals, an emotion engine, and user input.

[0115] The server, as the core of the system, performs translation functions using a natural language processing engine, data analysis functions, and legal and cultural navigation functions. For example, when a user is considering entering the French market, the server translates French documents into English, analyzes market trends, and proposes an entry strategy.

[0116] The emotion engine uses natural language processing technology to recognize the user's emotions in real time based on voice and text input from the user. This emotion information is used to personalize the various support services provided by the server; for example, if the user is feeling stressed, the server will present suggestions in a more careful and considerate manner.

[0117] The terminal provides a user interface, receiving user input and sending requests to the server. Through the interface, users can request market data, ask regulatory questions, or search for potential international business partners. The server's response is optimized and displayed on the terminal based on the user's emotional state, which has been analyzed by an emotion engine.

[0118] As a concrete example, suppose a user inquires about business etiquette in a certain country. In this case, the terminal sends the corresponding question to the server, and the server extracts relevant laws and cultural customs from its database. Meanwhile, the emotion engine analyzes the user's reaction, and if the user is feeling confused or anxious, the server provides more detailed explanations to resolve the issue.

[0119] This allows the present invention to improve the quality of interaction based on user emotions and support the success of overseas business activities.

[0120] The following describes the processing flow.

[0121] Step 1:

[0122] Users enter requests from their devices to perform specific business actions (e.g., language translation, data analysis, legal information retrieval, partner search, etc.).

[0123] Step 2:

[0124] The device receives user input, an emotion engine analyzes the user's voice and text to determine their emotional state, and sends the results to the server.

[0125] Step 3:

[0126] The server analyzes the user's request and selects a predetermined process (natural language processing, data analysis using machine learning, or information extraction from a legal database).

[0127] Step 4:

[0128] The server performs the necessary processing, for example, using a natural language processing engine to translate input text into a specified language, or analyzing market data to generate insights.

[0129] Step 5:

[0130] Based on the emotion analysis results from the emotion engine, the server selects a response that matches the user's emotional state and adjusts the content accordingly. For example, if the user is feeling anxious, more detailed information or additional explanations will be added.

[0131] Step 6:

[0132] The server sends the processing results and adjusted information back to the terminal.

[0133] Step 7:

[0134] The terminal displays information received from the server to the user, and the user can decide on their next action based on the presented information.

[0135] Step 8:

[0136] If the user has further questions or requests, the process is repeated from step 1.

[0137] (Example 2)

[0138] 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".

[0139] Companies aiming to enter global markets face complex challenges related to different languages, laws, and cultures. Traditional systems require significant time and resources to address these challenges, which is particularly burdensome for small and medium-sized enterprises (SMEs). Therefore, there is a need for the development of an integrated system that efficiently and effectively supports cross-cultural understanding and market strategy formulation.

[0140] 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.

[0141] In this invention, the server includes means for processing information using a natural language processing device, means for collecting and analyzing information data to make suggestions in response to user requests, and means for providing relevant information by referring to information on regulations and culture. This enables users to efficiently acquire information and receive support for decision-making regarding cross-cultural business development.

[0142] A "natural language processing device" is a device that utilizes technology to process and convert text and speech between different languages.

[0143] "Information data" refers to various types of information related to markets, laws, culture, etc., and is the data that is analyzed.

[0144] "Regulatory and cultural information" refers to knowledge and data about laws and cultural practices in a particular region or country.

[0145] "Emotional state" refers to the psychological response a user exhibits in a particular situation, and the system's response is adjusted based on this.

[0146] A "user interface" is the physical or logical means by which a user interacts with a computer system.

[0147] "Machine learning technology" is a technology that provides computer systems with the ability to learn from data and make predictions and decisions.

[0148] The system of this invention functions as a multi-functional agent to solve the various challenges that small and medium-sized enterprises face when entering overseas markets. Specifically, a server, terminal, and emotion engine work together as key components to provide the optimal solution according to the user's requirements.

[0149] The server is the heart of this system, using a natural language processing unit to perform real-time translation into foreign languages. The specific software used leverages common APIs. Furthermore, data analysis libraries can be used to collect and analyze information data. This allows for proposals tailored to the user's business needs.

[0150] The terminal serves as the user interface, directly receiving input from the user. This allows the user to proactively request market data and inquire about regulatory and cultural information. It receives responses from the server and presents the analyzed information to the user visually or audibly.

[0151] The emotion engine analyzes the user's emotional state and works to personalize the server's response. It utilizes emotion recognition technology based on voice and text input to enable interactions that take the user's psychological state into consideration.

[0152] As a concrete example, consider a scenario where a user asks about business etiquette in a particular country. The device sends this inquiry to the server, which retrieves and provides relevant information from a database of regulatory and cultural information. The sentiment engine analyzes the user's response and instructs the server to provide a more polite explanation if necessary.

[0153] An example of a prompt message would be, "Please provide information on business etiquette in France. Please explain in detail the points to be aware of and common customs." This allows users to efficiently obtain information through the system and conduct international business smoothly.

[0154] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0155] Step 1:

[0156] The user accesses the system using a terminal and enters a prompt such as, "Please provide information on business etiquette in France." The entered text data is sent from the terminal to the server.

[0157] Step 2:

[0158] The server analyzes the received prompt using natural language processing techniques. Specifically, it tokenizes the text, uses a parsing engine to understand the context, and extracts the information request. The input here is the prompt, and the output is the parsed information request.

[0159] Step 3:

[0160] The server generates queries to retrieve appropriate information data from the database based on the analysis results. The database contains international business etiquette and related regulatory information. The input is the analysis results, and the output is the relevant information data as the query result.

[0161] Step 4:

[0162] The server applies machine learning algorithms to the acquired data to extract the most relevant information based on the user's business needs. Specifically, it performs data filtering and ranking. The input is query results, and the output is refined data.

[0163] Step 5:

[0164] The emotion engine analyzes the user's response to input and evaluates their psychological state. The server uses this emotion data to adjust the tone and level of detail of the response. The input is the user's input response, and the output is the emotion evaluation result.

[0165] Step 6:

[0166] The server considers the sentiment assessment results and generates an optimized response. The final output not only satisfies the user's request but also provides emotionally sensitive information.

[0167] Step 7:

[0168] The terminal receives responses from the server and presents them to the user. The display method is text, and in some cases, audio, allowing the user to receive information concisely and clearly. The input is the server's final response, and the output is the information presented through the user interface.

[0169] (Application Example 2)

[0170] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0171] In today's international business environment, multilingual support and cross-cultural understanding are essential for small and medium-sized enterprises (SMEs) to effectively enter overseas markets. However, resources for addressing these challenges are currently limited. Furthermore, obtaining immediate, personalized feedback in language learning is difficult, and emotional support is lacking. Against this backdrop, there is a need to develop a system that efficiently proposes business strategies, supports language learning, and provides user-centric interactions.

[0172] 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.

[0173] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market data to propose optimal business strategies, and means for analyzing speech to support language learning and providing real-time feedback. This will enable multilingual support and promote cross-cultural understanding to facilitate international business for small and medium-sized enterprises, and further provide learning support that reduces stress for users, resulting in two-way communication that takes emotions into consideration.

[0174] A "natural language processing engine" is a technology that enables computers to understand and generate human language, and can perform language processing such as translation and interpretation in real time.

[0175] "Market data" refers to data that includes information about economic activity and consumer behavior, and is used in formulating business strategies.

[0176] A "database of laws and culture" is a collection of information that systematically organizes information about the laws and cultural customs of a particular country or region.

[0177] "Identifying potential partners" refers to the process of finding collaborators and partners suitable for business needs and compiling a list of them.

[0178] "Analysis of user dialogue input" refers to the act of analyzing user input, such as voice or text, to derive appropriate responses and suggestions.

[0179] "Language learning support" means providing real-time pronunciation checks and error feedback to help learners acquire a new language.

[0180] "Emotional analysis" is a technology that reads emotions from user voices and text information and uses it to improve the quality of interactions.

[0181] The system that implements this application analyzes voice and text data entered by the user and provides real-time translation and language learning support. The server uses a natural language processing engine to translate the input data into the desired language. Furthermore, it uses an emotion analysis engine to understand the user's emotional state and personalizes the interaction based on that information. This system uses software such as Google Cloud Natural Language API and AWS® Polly for speech recognition and natural language generation.

[0182] When a user is learning a language, the device has a function to point out pronunciation and grammatical errors in real time. For this purpose, the device is equipped with a microphone and speaker to collect and analyze the user's voice. It then generates appropriate feedback and delivers it to the user through the speaker.

[0183] For example, when a user pronounces "It's a nice day today" in French, the server analyzes it and provides real-time feedback on whether the pronunciation is correct. Furthermore, if sentiment analysis determines that the user is feeling stressed, the device will send an encouraging message such as "Relax and keep going."

[0184] An example of a prompt to a generative AI model is, "Please teach the generative AI how to detect emotions from the user's voice and provide appropriate feedback." This prompt allows the system to generate appropriate responses that match the user's emotions, improving the quality of the interaction.

[0185] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0186] Step 1:

[0187] To begin pronunciation practice, the user speaks a specific phrase into the device. The device uses its microphone to collect and record the audio data. This audio data becomes the input for the next process.

[0188] Step 2:

[0189] The device sends the collected audio data to the server. The server analyzes this audio data using the Google Cloud Natural Language API. As a result of the analysis, the data is output as text and audio features.

[0190] Step 3:

[0191] The server uses text data to perform translation and grammar checks, and evaluates the accuracy of pronunciation. It uses the DeepL API and Grammarly API to detect translation and grammatical errors. This results in correct pronunciation and grammatical corrections, which are then sent to the terminal.

[0192] Step 4:

[0193] The server analyzes the voice features using IBM Watson® Tone Analyzer to infer the user's emotions. Based on the results of this analysis, it evaluates whether the user is feeling tension or stress. This emotion information is also sent to the terminal.

[0194] Step 5:

[0195] The device provides visual and audible feedback to the user based on feedback received from the server. The speaker plays messages that point out errors and encourage relaxation (e.g., "Relax and continue"). Data processing involves techniques to present the server feedback to the user in an easily understandable way.

[0196] 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.

[0197] 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.

[0198] 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.

[0199] [Second Embodiment]

[0200] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0201] 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.

[0202] 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).

[0203] 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.

[0204] 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.

[0205] 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).

[0206] 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.

[0207] 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.

[0208] 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.

[0209] 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.

[0210] 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.

[0211] 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".

[0212] The system of this invention provides multifaceted support for the challenges faced by small and medium-sized enterprises (SMEs) in expanding overseas. The system operates based on three main elements: server, terminal, and user.

[0213] The server, at the core of the system, uses a natural language processing engine to translate text sent by users in real time, providing interpretation services. If a user inputs a business document in Japanese, the server translates it into the specified language and sends the translation result to the terminal. This process enables communication that transcends language barriers.

[0214] The server also has the capability to analyze market data. When a user requests information on a specific market, the server collects a vast amount of relevant data sets and performs analysis using machine learning algorithms. The analysis results are displayed visually on the user's device, supporting strategic business decisions.

[0215] The terminal functions as the user interface, accepting user input and displaying information from the server. When a user asks a question about a specific law or culture, the terminal sends a request to the server and presents the user with the information provided by the server. This makes it easier to understand local business customs and legal regulations.

[0216] Furthermore, the server has a function to match business partners. The server identifies partners that meet the user's requirements and provides the user with a list of evaluated candidates via the terminal. This allows users to efficiently find trustworthy partners.

[0217] As an interactive support system, the server analyzes user input using a machine learning model and immediately provides necessary solutions. When a user enters a specific business problem, the server retrieves appropriate past cases and solutions and advises the user to quickly resolve the issue.

[0218] As described above, the present invention provides comprehensive support in the areas of language, information analysis, legal assistance, partnership formation, and problem solving, and can help support success in diverse overseas business environments.

[0219] The following describes the processing flow.

[0220] Step 1:

[0221] Users input the information and actions they require (translation, data analysis, legal compliance checks, partner search, consultation, etc.) through the system's terminal.

[0222] Step 2:

[0223] The terminal receives user input and sends it to the server as a request in the appropriate format.

[0224] Step 3:

[0225] The server receives the request and selects the appropriate process. For example, if translation is needed, it calls natural language processing; if data analysis is needed, it calls a data analysis algorithm.

[0226] Step 4:

[0227] The server executes the specified process. For translation, it uses a natural language processing engine to translate the input text and generate an interpreted result. For data analysis, it analyzes relevant data using machine learning algorithms and generates market insights.

[0228] Step 5:

[0229] The server sends the generated results back to the terminal. This may include translation results, data analysis outputs, legal information, a list of potential partners, or problem solutions.

[0230] Step 6:

[0231] The terminal receives information from the server and displays it to the user. The user can then decide on their next action based on the information provided.

[0232] Step 7:

[0233] If the user has further questions or requests, the process is repeated from step 1.

[0234] (Example 1)

[0235] 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."

[0236] Many businesses are currently attempting to enter international markets, but they face challenges such as language barriers, difficulty obtaining market information, selecting appropriate business partners, and a lack of understanding of local laws and cultures. This makes effective strategy formulation and rapid decision-making difficult. A comprehensive support system is needed to address these issues.

[0237] 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.

[0238] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market information to propose optimal business strategies, means for explaining legal regulations and cultural practices by referring to databases on laws and culture, and means for presenting the analysis results in a visual format. This enables smooth communication in international markets with diverse languages ​​and cultures, and allows for accurate and efficient decision-making.

[0239] A "natural language processing engine" is a technology that allows computers to understand human language and convert it into an executable form, enabling real-time translation and interpretation.

[0240] "Market information" refers to data such as consumer trends, competitive landscape, and economic indicators in a specific market, and is fundamental information necessary for formulating business strategies.

[0241] A "machine learning algorithm" is a data processing technique used to analyze large amounts of data, find patterns within it, and build predictive models.

[0242] A "database of laws and cultures" is a source of information that systematically accumulates and organizes information on the laws and cultural practices of various countries, and serves as a supplementary tool for users to understand laws and cultures.

[0243] A "business partner" refers to another organization or individual with whom a cooperative relationship is established when promoting a business, and who is a partner with whom efforts are made to improve operational efficiency and expand the market.

[0244] "Interactive input" refers to information input in the form of questions and answers that users make to a server or system, with the aim of solving problems or obtaining information.

[0245] "Visual format" refers to a method of presentation that displays information in a visual form, such as graphs, charts, and diagrams, to make it easier to understand intuitively.

[0246] This invention is a support system designed to remove various barriers for small and medium-sized enterprises (SMEs) operating in the international market. This system consists of three elements: a server, a terminal, and a user, which work together to realize the invention.

[0247] The server is equipped with a natural language processing engine and translates business-related information entered by users in real time. For example, if a user enters "New product sales strategy for the Italian market" in Japanese, the server will translate it into Italian. Open-source multilingual tools can be used as the natural language processing engine for translation. The server also collects market information from multiple data sources and analyzes it using machine learning algorithms. As a result, it provides users with insights into optimal business strategies. The server uses open-source data visualization libraries to present information visually.

[0248] The terminal is an interface for users to input information and for the server to visually display the information it provides. For example, a user can send a request to the server by typing "I want to find a distribution partner in France" into the terminal. The terminal displays the translation results and market analysis results provided by the server as graphs and charts, allowing users to intuitively grasp the information.

[0249] This system can also provide detailed information on laws and culture. By referencing a comprehensive database, the server can, for example, answer a user's question about "the procedures required to establish a company in Italy" by providing information on local laws and cultural practices.

[0250] Furthermore, the server also features a business partner matching function. If a user requests an "environmentally conscious partner," the server narrows down the candidates that meet the criteria and displays a list on the user's device. This allows users to quickly find reliable collaborators.

[0251] As a concrete example, a user can input a prompt message to the generated AI model such as, "I want to sell traditional Japanese crafts in the American market. Please tell me about market research and sales strategies," and receive comprehensive support through the collaboration between the server and the terminal.

[0252] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0253] Step 1:

[0254] The user inputs business-related information through the terminal. For example, a prompt message such as "Please tell me about the distribution strategy for a new product in the Italian market" is used as input. Once input is received, the terminal prepares to send this information to the server.

[0255] Step 2:

[0256] The server analyzes the user's input text received from the terminal using a natural language processing engine. The analyzed data is translated into the specified language as needed. For example, if the user inputs in Japanese, the server will translate it into Italian, English, or another language. The output is the translated text.

[0257] Step 3:

[0258] The server collects market information based on the translated prompt text. The server retrieves data related to the Italian market from the internet and internal databases. Input information includes specific keywords related to the target market. Output is a dataset of relevant market information.

[0259] Step 4:

[0260] The server analyzes collected market data using machine learning algorithms. For example, it predicts competitive landscapes and market demand. The input is market data, and the output is insights useful for business strategies. Specifically, data cleansing and model application are performed.

[0261] Step 5:

[0262] The server visualizes the analysis results and generates them as graphs and charts. This allows users to intuitively understand market conditions based on the visual data displayed on their devices. The input is analytical insights, and the output is visualized information.

[0263] Step 6:

[0264] The terminal displays analysis results and visualization data sent from the server to the user. The user can then make decisions based on this information. Specifically, the terminal performs data rendering on a digital screen.

[0265] (Application Example 1)

[0266] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0267] In today's global business environment, small and medium-sized enterprises (SMEs) face complex challenges such as language barriers, cultural differences, region-specific laws and regulations, and the analysis of diverse market data. In particular, effective communication across different language regions, strategic decision-making, and the development of optimal marketing strategies are significant obstacles to international success. In addition, they are required to quickly and reliably find business partners and efficiently integrate these processes.

[0268] 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.

[0269] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market data to propose optimal business strategies, means for explaining laws and cultural customs by referring to a database of laws and cultures, and means for optimizing advertising to generate sales strategies in multilingual markets. This enables smooth international business exchange that transcends language and cultural barriers, allowing users to accurately grasp the most important business opportunities and formulate accurate strategies that meet diverse market conditions.

[0270] A "natural language processing engine" is a technology that translates text data from users into multiple languages ​​and performs language conversion in real time.

[0271] "Market data collection and analysis methods" refer to the process of collecting data on market trends and consumer behavior, and using machine learning algorithms to propose optimal business strategies to users.

[0272] A "database of laws and culture" is a source of information that systematically organizes information on laws and cultural practices, and provides accurate information in response to user inquiries.

[0273] "Ad optimization methods for generating sales strategies in multilingual markets" refers to technologies that generate advertising content that takes into account the language and culture of each market and deliver it to the appropriate target audience.

[0274] "Methods for identifying potential business partners" refer to methods for selecting appropriate companies and individuals based on the user's business conditions and listing highly reliable partners.

[0275] "User dialogue input analysis means" refers to technology that analyzes questions and requests from users and quickly provides corresponding solutions.

[0276] This invention is primarily implemented using three elements: a server, a terminal, and a user. Its specific form is described below.

[0277] The server functions as the core of this system, using a natural language processing engine to translate and interpret text sent by users in real time. It utilizes the Google Translate API to facilitate communication across multiple languages. Furthermore, the server collects market data, analyzes it using machine learning algorithms such as Scikit-learn, and visualizes and proposes optimal business strategies to users.

[0278] The terminal functions as the user interface, receiving user input and presenting information from the server. It utilizes React Native to enable cross-platform use. Through the terminal, users can ask questions about local laws and culture and receive information retrieved from the database.

[0279] With this system, users can formulate effective sales strategies in different markets and optimize advertisements in multilingual markets. Also, through the analysis of user conversations by the AI model, rapid problem-solving can be achieved.

[0280] As a specific example, when a user plans to expand into the Spanish market from Japan, this system can generate an advertising strategy in Spanish and perform targeting based on market analysis. When the user inputs a prompt sentence such as "I want to launch this product in the Spanish market, but what points should I keep in mind when creating marketing emails in Spanish?", appropriate advice and past success stories are presented.

[0281] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0282] Step 1:

[0283] The user accesses the input screen through the terminal and inputs information regarding the target market and language. The input data is specific matters regarding the region where the user plans to expand. The text input here is sent by the terminal to the server.

[0284] Step 2:

[0285] The server passes the received text data to the natural language processing engine for analysis. The purpose of this analysis is to understand the content of the user's input and identify the requested translation or market information. As a result, the server obtains the translated text or market data to be analyzed.

[0286] Step 3:

[0287] The server collects market data and analyzes it using machine learning algorithms. Specifically, it applies statistical methods using Scikit-learn to analyze trends and competitive information in the user-specified market. As a result of the analysis, business insights tailored to the user's needs are generated.

[0288] Step 4:

[0289] The server generates advertising content based on collected and analyzed data to optimize sales strategies in multilingual markets. Ad copy and promotional content are created using a generative AI model, resulting in the construction of optimal advertising messages for the target market.

[0290] Step 5:

[0291] The terminal displays results sent from the server, presenting the user with the most suitable translation, marketing strategy, and market insights. This allows the user to determine what specific actions they should take. Furthermore, if the user has additional questions or wishes to make corrections, they can resend the information to the server through the terminal.

[0292] 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.

[0293] The system of this invention is designed as a multi-functional agent to support small and medium-sized enterprises in entering overseas markets. This system operates based on a server, terminals, an emotion engine, and user input.

[0294] The server, as the core of the system, performs translation functions using a natural language processing engine, data analysis functions, and legal and cultural navigation functions. For example, when a user is considering entering the French market, the server translates French documents into English, analyzes market trends, and proposes an entry strategy.

[0295] The emotion engine uses natural language processing technology to recognize the user's emotions in real time based on voice and text input from the user. This emotion information is used to personalize the various support services provided by the server; for example, if the user is feeling stressed, the server will present suggestions in a more careful and considerate manner.

[0296] The terminal provides a user interface, receiving user input and sending requests to the server. Through the interface, users can request market data, ask regulatory questions, or search for potential international business partners. The server's response is optimized and displayed on the terminal based on the user's emotional state, which has been analyzed by an emotion engine.

[0297] As a concrete example, suppose a user inquires about business etiquette in a certain country. In this case, the terminal sends the corresponding question to the server, and the server extracts relevant laws and cultural customs from its database. Meanwhile, the emotion engine analyzes the user's reaction, and if the user is feeling confused or anxious, the server provides more detailed explanations to resolve the issue.

[0298] This allows the present invention to improve the quality of interaction based on user emotions and support the success of overseas business activities.

[0299] The following describes the processing flow.

[0300] Step 1:

[0301] The user inputs a request from the terminal to execute a specific business action (e.g., language translation, data analysis, obtaining regulatory information, finding partners, etc.).

[0302] Step 2:

[0303] The terminal receives the user's input content, analyzes the emotional state from the user's voice or text by the emotion engine, and sends the result to the server.

[0304] Step 3:

[0305] The server analyzes the user's request and selects a predetermined process (natural language processing, data analysis by machine learning, information extraction from a regulatory database).

[0306] Step 4:

[0307] The server executes the required process, for example, uses a natural language processing engine to translate the input text into a specified language, or analyzes market data to generate insights.

[0308] Step 5:

[0309] Based on the emotion analysis result from the emotion engine, the server selects a countermeasure suitable for the user's emotional state and adjusts the content according to the result. For example, if the user is worried, more detailed information or additional explanations are added.

[0310] Step 6:

[0311] The server sends the processing result and the adjusted information back to the terminal.

[0312] Step 7:

[0313] The terminal displays the information received from the server to the user, and the user can determine the next action based on the presented information.

[0314] Step 8:

[0315] If the user has further questions or requests, the process is repeated from step 1.

[0316] (Example 2)

[0317] 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".

[0318] Companies aiming to enter global markets face complex challenges related to different languages, laws, and cultures. Traditional systems require significant time and resources to address these challenges, which is particularly burdensome for small and medium-sized enterprises (SMEs). Therefore, there is a need for the development of an integrated system that efficiently and effectively supports cross-cultural understanding and market strategy formulation.

[0319] 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.

[0320] In this invention, the server includes means for processing information using a natural language processing device, means for collecting and analyzing information data to make suggestions in response to user requests, and means for providing relevant information by referring to information on regulations and culture. This enables users to efficiently acquire information and receive support for decision-making regarding cross-cultural business development.

[0321] A "natural language processing device" is a device that utilizes technology to process and convert text and speech between different languages.

[0322] "Information data" refers to various types of information related to markets, laws, culture, etc., and is the data that is analyzed.

[0323] "Regulatory and cultural information" refers to knowledge and data about laws and cultural practices in a particular region or country.

[0324] "Emotional state" refers to the psychological response a user exhibits in a particular situation, and the system's response is adjusted based on this.

[0325] A "user interface" is the physical or logical means by which a user interacts with a computer system.

[0326] "Machine learning technology" is a technology that provides computer systems with the ability to learn from data and make predictions and decisions.

[0327] The system of this invention functions as a multi-functional agent to solve the various challenges that small and medium-sized enterprises face when entering overseas markets. Specifically, a server, terminal, and emotion engine work together as key components to provide the optimal solution according to the user's requirements.

[0328] The server is the heart of this system, using a natural language processing unit to perform real-time translation into foreign languages. The specific software used leverages common APIs. Furthermore, data analysis libraries can be used to collect and analyze information data. This allows for proposals tailored to the user's business needs.

[0329] The terminal serves as the user interface, directly receiving input from the user. This allows the user to proactively request market data and inquire about regulatory and cultural information. It receives responses from the server and presents the analyzed information to the user visually or audibly.

[0330] The emotion engine analyzes the user's emotional state and works to personalize the server's response. It utilizes emotion recognition technology based on voice and text input to enable interactions that take the user's psychological state into consideration.

[0331] As a concrete example, consider a scenario where a user asks about business etiquette in a particular country. The device sends this inquiry to the server, which retrieves and provides relevant information from a database of regulatory and cultural information. The sentiment engine analyzes the user's response and instructs the server to provide a more polite explanation if necessary.

[0332] An example of a prompt message would be, "Please provide information on business etiquette in France. Please explain in detail the points to be aware of and common customs." This allows users to efficiently obtain information through the system and conduct international business smoothly.

[0333] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0334] Step 1:

[0335] The user accesses the system using a terminal and enters a prompt such as, "Please provide information on business etiquette in France." The entered text data is sent from the terminal to the server.

[0336] Step 2:

[0337] The server analyzes the received prompt using natural language processing techniques. Specifically, it tokenizes the text, uses a parsing engine to understand the context, and extracts the information request. The input here is the prompt, and the output is the parsed information request.

[0338] Step 3:

[0339] The server generates queries to retrieve appropriate information data from the database based on the analysis results. The database contains international business etiquette and related regulatory information. The input is the analysis results, and the output is the relevant information data as the query result.

[0340] Step 4:

[0341] The server applies machine learning algorithms to the acquired data to extract the most relevant information based on the user's business needs. Specifically, it performs data filtering and ranking. The input is query results, and the output is refined data.

[0342] Step 5:

[0343] The emotion engine analyzes the user's response to input and evaluates their psychological state. The server uses this emotion data to adjust the tone and level of detail of the response. The input is the user's input response, and the output is the emotion evaluation result.

[0344] Step 6:

[0345] The server considers the sentiment assessment results and generates an optimized response. The final output not only satisfies the user's request but also provides emotionally sensitive information.

[0346] Step 7:

[0347] The terminal receives responses from the server and presents them to the user. The display method is text, and in some cases, audio, allowing the user to receive information concisely and clearly. The input is the server's final response, and the output is the information presented through the user interface.

[0348] (Application Example 2)

[0349] 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."

[0350] In today's international business environment, multilingual support and cross-cultural understanding are essential for small and medium-sized enterprises (SMEs) to effectively enter overseas markets. However, resources for addressing these challenges are currently limited. Furthermore, obtaining immediate, personalized feedback in language learning is difficult, and emotional support is lacking. Against this backdrop, there is a need to develop a system that efficiently proposes business strategies, supports language learning, and provides user-centric interactions.

[0351] 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.

[0352] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market data to propose optimal business strategies, and means for analyzing speech to support language learning and providing real-time feedback. This will enable multilingual support and promote cross-cultural understanding to facilitate international business for small and medium-sized enterprises, and further provide learning support that reduces stress for users, resulting in two-way communication that takes emotions into consideration.

[0353] A "natural language processing engine" is a technology that enables computers to understand and generate human language, and can perform language processing such as translation and interpretation in real time.

[0354] "Market data" refers to data that includes information about economic activity and consumer behavior, and is used in formulating business strategies.

[0355] A "database of laws and culture" is a collection of information that systematically organizes information about the laws and cultural customs of a particular country or region.

[0356] "Identifying potential partners" refers to the process of finding collaborators and partners suitable for business needs and compiling a list of them.

[0357] "Analysis of user dialogue input" refers to the act of analyzing user input, such as voice or text, to derive appropriate responses and suggestions.

[0358] "Language learning support" means providing real-time pronunciation checks and error feedback to help learners acquire a new language.

[0359] "Emotional analysis" is a technology that reads emotions from user voices and text information and uses it to improve the quality of interactions.

[0360] The system that implements this application analyzes voice and text data entered by the user and provides real-time translation and language learning support. The server uses a natural language processing engine to translate the input data into the desired language. Furthermore, it uses an emotion analysis engine to understand the user's emotional state and personalizes the interaction based on that information. This system uses software such as Google Cloud Natural Language API and AWS Polly for speech recognition and natural language generation.

[0361] When a user is learning a language, the device has a function to point out pronunciation and grammatical errors in real time. For this purpose, the device is equipped with a microphone and speaker to collect and analyze the user's voice. It then generates appropriate feedback and delivers it to the user through the speaker.

[0362] For example, when a user pronounces "It's a nice day today" in French, the server analyzes it and provides real-time feedback on whether the pronunciation is correct. Furthermore, if sentiment analysis determines that the user is feeling stressed, the device will send an encouraging message such as "Relax and keep going."

[0363] An example of a prompt to a generative AI model is, "Please teach the generative AI how to detect emotions from the user's voice and provide appropriate feedback." This prompt allows the system to generate appropriate responses that match the user's emotions, improving the quality of the interaction.

[0364] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0365] Step 1:

[0366] To begin pronunciation practice, the user speaks a specific phrase into the device. The device uses its microphone to collect and record the audio data. This audio data becomes the input for the next process.

[0367] Step 2:

[0368] The device sends the collected audio data to the server. The server analyzes this audio data using the Google Cloud Natural Language API. As a result of the analysis, the data is output as text and audio features.

[0369] Step 3:

[0370] The server uses text data to perform translation and grammar checks, and evaluates the accuracy of pronunciation. It uses the DeepL API and Grammarly API to detect translation and grammatical errors. This results in correct pronunciation and grammatical corrections, which are then sent to the terminal.

[0371] Step 4:

[0372] The server analyzes the voice features using IBM Watson's Tone Analyzer to infer the user's emotions. Based on the results of this analysis, it evaluates whether the user is feeling tension or stress. This emotional information is also sent to the terminal.

[0373] Step 5:

[0374] The device provides visual and audible feedback to the user based on feedback received from the server. The speaker plays messages that point out errors and encourage relaxation (e.g., "Relax and continue"). Data processing involves techniques to present the server feedback to the user in an easily understandable way.

[0375] 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.

[0376] 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.

[0377] 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.

[0378] [Third Embodiment]

[0379] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0380] 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.

[0381] 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).

[0382] 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.

[0383] 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.

[0384] 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).

[0385] 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.

[0386] 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.

[0387] 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.

[0388] 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.

[0389] 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.

[0390] 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".

[0391] The system of this invention provides multifaceted support for the challenges faced by small and medium-sized enterprises (SMEs) in expanding overseas. The system operates based on three main elements: server, terminal, and user.

[0392] The server, at the core of the system, uses a natural language processing engine to translate text sent by users in real time, providing interpretation services. If a user inputs a business document in Japanese, the server translates it into the specified language and sends the translation result to the terminal. This process enables communication that transcends language barriers.

[0393] The server also has the capability to analyze market data. When a user requests information on a specific market, the server collects a vast amount of relevant data sets and performs analysis using machine learning algorithms. The analysis results are displayed visually on the user's device, supporting strategic business decisions.

[0394] The terminal functions as the user interface, accepting user input and displaying information from the server. When a user asks a question about a specific law or culture, the terminal sends a request to the server and presents the user with the information provided by the server. This makes it easier to understand local business customs and legal regulations.

[0395] Furthermore, the server has a function to match business partners. The server identifies partners that meet the user's requirements and provides the user with a list of evaluated candidates via the terminal. This allows users to efficiently find trustworthy partners.

[0396] As an interactive support system, the server analyzes user input using a machine learning model and immediately provides necessary solutions. When a user enters a specific business problem, the server retrieves appropriate past cases and solutions and advises the user to quickly resolve the issue.

[0397] As described above, the present invention provides comprehensive support in the areas of language, information analysis, legal assistance, partnership formation, and problem solving, and can help support success in diverse overseas business environments.

[0398] The following describes the processing flow.

[0399] Step 1:

[0400] Users input the information and actions they require (translation, data analysis, legal compliance checks, partner search, consultation, etc.) through the system's terminal.

[0401] Step 2:

[0402] The terminal receives user input and sends it to the server as a request in the appropriate format.

[0403] Step 3:

[0404] The server receives the request and selects the appropriate process. For example, if translation is needed, it calls natural language processing; if data analysis is needed, it calls a data analysis algorithm.

[0405] Step 4:

[0406] The server executes the specified process. For translation, it uses a natural language processing engine to translate the input text and generate an interpreted result. For data analysis, it analyzes relevant data using machine learning algorithms and generates market insights.

[0407] Step 5:

[0408] The server sends the generated results back to the terminal. This may include translation results, data analysis outputs, legal information, a list of potential partners, or problem solutions.

[0409] Step 6:

[0410] The terminal receives information from the server and displays it to the user. The user can then decide on their next action based on the information provided.

[0411] Step 7:

[0412] If the user has further questions or requests, the process is repeated from step 1.

[0413] (Example 1)

[0414] 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."

[0415] Many businesses are currently attempting to enter international markets, but they face challenges such as language barriers, difficulty obtaining market information, selecting appropriate business partners, and a lack of understanding of local laws and cultures. This makes effective strategy formulation and rapid decision-making difficult. A comprehensive support system is needed to address these issues.

[0416] 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.

[0417] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market information to propose optimal business strategies, means for explaining legal regulations and cultural practices by referring to databases on laws and culture, and means for presenting the analysis results in a visual format. This enables smooth communication in international markets with diverse languages ​​and cultures, and allows for accurate and efficient decision-making.

[0418] A "natural language processing engine" is a technology that allows computers to understand human language and convert it into an executable form, enabling real-time translation and interpretation.

[0419] "Market information" refers to data such as consumer trends, competitive landscape, and economic indicators in a specific market, and is fundamental information necessary for formulating business strategies.

[0420] A "machine learning algorithm" is a data processing technique used to analyze large amounts of data, find patterns within it, and build predictive models.

[0421] A "database of laws and cultures" is a source of information that systematically accumulates and organizes information on the laws and cultural practices of various countries, and serves as a supplementary tool for users to understand laws and cultures.

[0422] A "business partner" refers to another organization or individual with whom a cooperative relationship is established when promoting a business, and who is a partner with whom efforts are made to improve operational efficiency and expand the market.

[0423] "Interactive input" refers to information input in the form of questions and answers that users make to a server or system, with the aim of solving problems or obtaining information.

[0424] "Visual format" refers to a method of presentation that displays information in a visual form, such as graphs, charts, and diagrams, to make it easier to understand intuitively.

[0425] This invention is a support system designed to remove various barriers for small and medium-sized enterprises (SMEs) operating in the international market. This system consists of three elements: a server, a terminal, and a user, which work together to realize the invention.

[0426] The server is equipped with a natural language processing engine and translates business-related information entered by users in real time. For example, if a user enters "New product sales strategy for the Italian market" in Japanese, the server will translate it into Italian. Open-source multilingual tools can be used as the natural language processing engine for translation. The server also collects market information from multiple data sources and analyzes it using machine learning algorithms. As a result, it provides users with insights into optimal business strategies. The server uses open-source data visualization libraries to present information visually.

[0427] The terminal is an interface for users to input information and for the server to visually display the information it provides. For example, a user can send a request to the server by typing "I want to find a distribution partner in France" into the terminal. The terminal displays the translation results and market analysis results provided by the server as graphs and charts, allowing users to intuitively grasp the information.

[0428] This system can also provide detailed information on laws and culture. By referencing a comprehensive database, the server can, for example, answer a user's question about "the procedures required to establish a company in Italy" by providing information on local laws and cultural practices.

[0429] Furthermore, the server also features a business partner matching function. If a user requests an "environmentally conscious partner," the server narrows down the candidates that meet the criteria and displays a list on the user's device. This allows users to quickly find reliable collaborators.

[0430] As a concrete example, a user can input a prompt message to the generated AI model such as, "I want to sell traditional Japanese crafts in the American market. Please tell me about market research and sales strategies," and receive comprehensive support through the collaboration between the server and the terminal.

[0431] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0432] Step 1:

[0433] The user inputs business-related information through the terminal. For example, a prompt message such as "Please tell me about the distribution strategy for a new product in the Italian market" is used as input. Once input is received, the terminal prepares to send this information to the server.

[0434] Step 2:

[0435] The server analyzes the user's input text received from the terminal using a natural language processing engine. The analyzed data is translated into the specified language as needed. For example, if the user inputs in Japanese, the server will translate it into Italian, English, or another language. The output is the translated text.

[0436] Step 3:

[0437] The server collects market information based on the translated prompt text. The server retrieves data related to the Italian market from the internet and internal databases. Input information includes specific keywords related to the target market. Output is a dataset of relevant market information.

[0438] Step 4:

[0439] The server analyzes collected market data using machine learning algorithms. For example, it predicts competitive landscapes and market demand. The input is market data, and the output is insights useful for business strategies. Specifically, data cleansing and model application are performed.

[0440] Step 5:

[0441] The server visualizes the analysis results and generates them as graphs and charts. This allows users to intuitively understand market conditions based on the visual data displayed on their devices. The input is analytical insights, and the output is visualized information.

[0442] Step 6:

[0443] The terminal displays analysis results and visualization data sent from the server to the user. The user can then make decisions based on this information. Specifically, the terminal performs data rendering on a digital screen.

[0444] (Application Example 1)

[0445] 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."

[0446] In today's global business environment, small and medium-sized enterprises (SMEs) face complex challenges such as language barriers, cultural differences, region-specific laws and regulations, and the analysis of diverse market data. In particular, effective communication across different language regions, strategic decision-making, and the development of optimal marketing strategies are significant obstacles to international success. In addition, they are required to quickly and reliably find business partners and efficiently integrate these processes.

[0447] 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.

[0448] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market data to propose optimal business strategies, means for explaining laws and cultural customs by referring to a database of laws and cultures, and means for optimizing advertising to generate sales strategies in multilingual markets. This enables smooth international business exchange that transcends language and cultural barriers, allowing users to accurately grasp the most important business opportunities and formulate accurate strategies that meet diverse market conditions.

[0449] A "natural language processing engine" is a technology that translates text data from users into multiple languages ​​and performs language conversion in real time.

[0450] "Market data collection and analysis methods" refer to the process of collecting data on market trends and consumer behavior, and using machine learning algorithms to propose optimal business strategies to users.

[0451] A "database of laws and culture" is a source of information that systematically organizes information on laws and cultural practices, and provides accurate information in response to user inquiries.

[0452] "Ad optimization methods for generating sales strategies in multilingual markets" refers to technologies that generate advertising content that takes into account the language and culture of each market and deliver it to the appropriate target audience.

[0453] "Methods for identifying potential business partners" refer to methods for selecting appropriate companies and individuals based on the user's business conditions and listing highly reliable partners.

[0454] "User dialogue input analysis means" refers to technology that analyzes questions and requests from users and quickly provides corresponding solutions.

[0455] This invention is primarily implemented using three elements: a server, a terminal, and a user. Its specific form is described below.

[0456] The server functions as the core of this system, using a natural language processing engine to translate and interpret text sent by users in real time. It utilizes the Google Translate API to facilitate communication across multiple languages. Furthermore, the server collects market data, analyzes it using machine learning algorithms such as Scikit-learn, and visualizes and proposes optimal business strategies to users.

[0457] The terminal functions as the user interface, receiving user input and presenting information from the server. It utilizes React Native to enable cross-platform use. Through the terminal, users can ask questions about local laws and culture and receive information retrieved from the database.

[0458] This system enables users to develop effective sales strategies in different markets and optimize advertising in multilingual markets. Furthermore, AI-powered user dialogue analysis facilitates rapid problem-solving.

[0459] For example, if a user is planning to enter the Spanish market from Japan, this system can generate an advertising strategy in Spanish and perform targeting based on market analysis. When the user enters a prompt such as, "I want to launch this product in the Spanish market, but what points should I keep in mind when creating marketing emails in Spanish?", appropriate advice and past success stories will be provided.

[0460] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0461] Step 1:

[0462] The user accesses an input screen via a terminal and enters information about the target market and language. The input data is specific to the region where the user plans to expand. The text entered here is sent from the terminal to the server.

[0463] Step 2:

[0464] The server passes the received text data to a natural language processing engine for analysis. The purpose of this analysis is to understand the user's input and identify the requested translation or market information. As a result, the server obtains the translated text or market data to be analyzed.

[0465] Step 3:

[0466] The server collects market data and analyzes it using machine learning algorithms. Specifically, it applies statistical methods using Scikit-learn to analyze trends and competitive information in the user-specified market. As a result of the analysis, business insights tailored to the user's needs are generated.

[0467] Step 4:

[0468] The server generates advertising content based on collected and analyzed data to optimize sales strategies in multilingual markets. Ad copy and promotional content are created using a generative AI model, resulting in the construction of optimal advertising messages for the target market.

[0469] Step 5:

[0470] The terminal displays results sent from the server, presenting the user with the most suitable translation, marketing strategy, and market insights. This allows the user to determine what specific actions they should take. Furthermore, if the user has additional questions or wishes to make corrections, they can resend the information to the server through the terminal.

[0471] 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.

[0472] The system of this invention is designed as a multi-functional agent to support small and medium-sized enterprises in entering overseas markets. This system operates based on a server, terminals, an emotion engine, and user input.

[0473] The server, as the core of the system, performs translation functions using a natural language processing engine, data analysis functions, and legal and cultural navigation functions. For example, when a user is considering entering the French market, the server translates French documents into English, analyzes market trends, and proposes an entry strategy.

[0474] The emotion engine uses natural language processing technology to recognize the user's emotions in real time based on voice and text input from the user. This emotion information is used to personalize the various support services provided by the server; for example, if the user is feeling stressed, the server will present suggestions in a more careful and considerate manner.

[0475] The terminal provides a user interface, receiving user input and sending requests to the server. Through the interface, users can request market data, ask regulatory questions, or search for potential international business partners. The server's response is optimized and displayed on the terminal based on the user's emotional state, which has been analyzed by an emotion engine.

[0476] As a concrete example, suppose a user inquires about business etiquette in a certain country. In this case, the terminal sends the corresponding question to the server, and the server extracts relevant laws and cultural customs from its database. Meanwhile, the emotion engine analyzes the user's reaction, and if the user is feeling confused or anxious, the server provides more detailed explanations to resolve the issue.

[0477] This allows the present invention to improve the quality of interaction based on user emotions and support the success of overseas business activities.

[0478] The following describes the processing flow.

[0479] Step 1:

[0480] Users enter requests from their devices to perform specific business actions (e.g., language translation, data analysis, legal information retrieval, partner search, etc.).

[0481] Step 2:

[0482] The device receives user input, an emotion engine analyzes the user's voice and text to determine their emotional state, and sends the results to the server.

[0483] Step 3:

[0484] The server analyzes the user's request and selects a predetermined process (natural language processing, data analysis using machine learning, or information extraction from a legal database).

[0485] Step 4:

[0486] The server performs the necessary processing, for example, using a natural language processing engine to translate input text into a specified language, or analyzing market data to generate insights.

[0487] Step 5:

[0488] Based on the emotion analysis results from the emotion engine, the server selects a response that matches the user's emotional state and adjusts the content accordingly. For example, if the user is feeling anxious, more detailed information or additional explanations will be added.

[0489] Step 6:

[0490] The server sends the processing results and adjusted information back to the terminal.

[0491] Step 7:

[0492] The terminal displays information received from the server to the user, and the user can decide on their next action based on the presented information.

[0493] Step 8:

[0494] If the user has further questions or requests, the process is repeated from step 1.

[0495] (Example 2)

[0496] 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."

[0497] Companies aiming to enter global markets face complex challenges related to different languages, laws, and cultures. Traditional systems require significant time and resources to address these challenges, which is particularly burdensome for small and medium-sized enterprises (SMEs). Therefore, there is a need for the development of an integrated system that efficiently and effectively supports cross-cultural understanding and market strategy formulation.

[0498] 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.

[0499] In this invention, the server includes means for processing information using a natural language processing device, means for collecting and analyzing information data to make suggestions in response to user requests, and means for providing relevant information by referring to information on regulations and culture. This enables users to efficiently acquire information and receive support for decision-making regarding cross-cultural business development.

[0500] A "natural language processing device" is a device that utilizes technology to process and convert text and speech between different languages.

[0501] "Information data" refers to various types of information related to markets, laws, culture, etc., and is the data that is analyzed.

[0502] "Regulatory and cultural information" refers to knowledge and data about laws and cultural practices in a particular region or country.

[0503] "Emotional state" refers to the psychological response a user exhibits in a particular situation, and the system's response is adjusted based on this.

[0504] A "user interface" is the physical or logical means by which a user interacts with a computer system.

[0505] "Machine learning technology" is a technology that provides computer systems with the ability to learn from data and make predictions and decisions.

[0506] The system of this invention functions as a multi-functional agent to solve the various challenges that small and medium-sized enterprises face when entering overseas markets. Specifically, a server, terminal, and emotion engine work together as key components to provide the optimal solution according to the user's requirements.

[0507] The server is the heart of this system, using a natural language processing unit to perform real-time translation into foreign languages. The specific software used leverages common APIs. Furthermore, data analysis libraries can be used to collect and analyze information data. This allows for proposals tailored to the user's business needs.

[0508] The terminal serves as the user interface, directly receiving input from the user. This allows the user to proactively request market data and inquire about regulatory and cultural information. It receives responses from the server and presents the analyzed information to the user visually or audibly.

[0509] The emotion engine analyzes the user's emotional state and works to personalize the server's response. It utilizes emotion recognition technology based on voice and text input to enable interactions that take the user's psychological state into consideration.

[0510] As a concrete example, consider a scenario where a user asks about business etiquette in a particular country. The device sends this inquiry to the server, which retrieves and provides relevant information from a database of regulatory and cultural information. The sentiment engine analyzes the user's response and instructs the server to provide a more polite explanation if necessary.

[0511] An example of a prompt message would be, "Please provide information on business etiquette in France. Please explain in detail the points to be aware of and common customs." This allows users to efficiently obtain information through the system and conduct international business smoothly.

[0512] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0513] Step 1:

[0514] The user accesses the system using a terminal and enters a prompt such as, "Please provide information on business etiquette in France." The entered text data is sent from the terminal to the server.

[0515] Step 2:

[0516] The server analyzes the received prompt using natural language processing techniques. Specifically, it tokenizes the text, uses a parsing engine to understand the context, and extracts the information request. The input here is the prompt, and the output is the parsed information request.

[0517] Step 3:

[0518] The server generates queries to retrieve appropriate information data from the database based on the analysis results. The database contains international business etiquette and related regulatory information. The input is the analysis results, and the output is the relevant information data as the query result.

[0519] Step 4:

[0520] The server applies machine learning algorithms to the acquired data to extract the most relevant information based on the user's business needs. Specifically, it performs data filtering and ranking. The input is query results, and the output is refined data.

[0521] Step 5:

[0522] The emotion engine analyzes the user's response to input and evaluates their psychological state. The server uses this emotion data to adjust the tone and level of detail of the response. The input is the user's input response, and the output is the emotion evaluation result.

[0523] Step 6:

[0524] The server considers the sentiment assessment results and generates an optimized response. The final output not only satisfies the user's request but also provides emotionally sensitive information.

[0525] Step 7:

[0526] The terminal receives responses from the server and presents them to the user. The display method is text, and in some cases, audio, allowing the user to receive information concisely and clearly. The input is the server's final response, and the output is the information presented through the user interface.

[0527] (Application Example 2)

[0528] 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."

[0529] In today's international business environment, multilingual support and cross-cultural understanding are essential for small and medium-sized enterprises (SMEs) to effectively enter overseas markets. However, resources for addressing these challenges are currently limited. Furthermore, obtaining immediate, personalized feedback in language learning is difficult, and emotional support is lacking. Against this backdrop, there is a need to develop a system that efficiently proposes business strategies, supports language learning, and provides user-centric interactions.

[0530] 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.

[0531] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market data to propose optimal business strategies, and means for analyzing speech to support language learning and providing real-time feedback. This will enable multilingual support and promote cross-cultural understanding to facilitate international business for small and medium-sized enterprises, and further provide learning support that reduces stress for users, resulting in two-way communication that takes emotions into consideration.

[0532] A "natural language processing engine" is a technology that enables computers to understand and generate human language, and can perform language processing such as translation and interpretation in real time.

[0533] "Market data" refers to data that includes information about economic activity and consumer behavior, and is used in formulating business strategies.

[0534] A "database of laws and culture" is a collection of information that systematically organizes information about the laws and cultural customs of a particular country or region.

[0535] "Identifying potential partners" refers to the process of finding collaborators and partners suitable for business needs and compiling a list of them.

[0536] "Analysis of user dialogue input" refers to the act of analyzing user input, such as voice or text, to derive appropriate responses and suggestions.

[0537] "Language learning support" means providing real-time pronunciation checks and error feedback to help learners acquire a new language.

[0538] "Emotional analysis" is a technology that reads emotions from user voices and text information and uses it to improve the quality of interactions.

[0539] The system that implements this application analyzes voice and text data entered by the user and provides real-time translation and language learning support. The server uses a natural language processing engine to translate the input data into the desired language. Furthermore, it uses an emotion analysis engine to understand the user's emotional state and personalizes the interaction based on that information. This system uses software such as Google Cloud Natural Language API and AWS Polly for speech recognition and natural language generation.

[0540] When a user is learning a language, the device has a function to point out pronunciation and grammatical errors in real time. For this purpose, the device is equipped with a microphone and speaker to collect and analyze the user's voice. It then generates appropriate feedback and delivers it to the user through the speaker.

[0541] For example, when a user pronounces "It's a nice day today" in French, the server analyzes it and provides real-time feedback on whether the pronunciation is correct. Furthermore, if sentiment analysis determines that the user is feeling stressed, the device will send an encouraging message such as "Relax and keep going."

[0542] An example of a prompt to a generative AI model is, "Please teach the generative AI how to detect emotions from the user's voice and provide appropriate feedback." This prompt allows the system to generate appropriate responses that match the user's emotions, improving the quality of the interaction.

[0543] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0544] Step 1:

[0545] To begin pronunciation practice, the user speaks a specific phrase into the device. The device uses its microphone to collect and record the audio data. This audio data becomes the input for the next process.

[0546] Step 2:

[0547] The device sends the collected audio data to the server. The server analyzes this audio data using the Google Cloud Natural Language API. As a result of the analysis, the data is output as text and audio features.

[0548] Step 3:

[0549] The server uses text data to perform translation and grammar checks, and evaluates the accuracy of pronunciation. It uses the DeepL API and Grammarly API to detect translation and grammatical errors. This results in correct pronunciation and grammatical corrections, which are then sent to the terminal.

[0550] Step 4:

[0551] The server analyzes the voice features using IBM Watson's Tone Analyzer to infer the user's emotions. Based on the results of this analysis, it evaluates whether the user is feeling tension or stress. This emotional information is also sent to the terminal.

[0552] Step 5:

[0553] The device provides visual and audible feedback to the user based on feedback received from the server. The speaker plays messages that point out errors and encourage relaxation (e.g., "Relax and continue"). Data processing involves techniques to present the server feedback to the user in an easily understandable way.

[0554] 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.

[0555] 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.

[0556] 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.

[0557] [Fourth Embodiment]

[0558] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0559] 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.

[0560] 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).

[0561] 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.

[0562] 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.

[0563] 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).

[0564] 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.

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] 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".

[0571] The system of this invention provides multifaceted support for the challenges faced by small and medium-sized enterprises (SMEs) in expanding overseas. The system operates based on three main elements: server, terminal, and user.

[0572] The server, at the core of the system, uses a natural language processing engine to translate text sent by users in real time, providing interpretation services. If a user inputs a business document in Japanese, the server translates it into the specified language and sends the translation result to the terminal. This process enables communication that transcends language barriers.

[0573] The server also has the capability to analyze market data. When a user requests information on a specific market, the server collects a vast amount of relevant data sets and performs analysis using machine learning algorithms. The analysis results are displayed visually on the user's device, supporting strategic business decisions.

[0574] The terminal functions as the user interface, accepting user input and displaying information from the server. When a user asks a question about a specific law or culture, the terminal sends a request to the server and presents the user with the information provided by the server. This makes it easier to understand local business customs and legal regulations.

[0575] Furthermore, the server has a function to match business partners. The server identifies partners that meet the user's requirements and provides the user with a list of evaluated candidates via the terminal. This allows users to efficiently find trustworthy partners.

[0576] As an interactive support system, the server analyzes user input using a machine learning model and immediately provides necessary solutions. When a user enters a specific business problem, the server retrieves appropriate past cases and solutions and advises the user to quickly resolve the issue.

[0577] As described above, the present invention provides comprehensive support in the areas of language, information analysis, legal assistance, partnership formation, and problem solving, and can help support success in diverse overseas business environments.

[0578] The following describes the processing flow.

[0579] Step 1:

[0580] Users input the information and actions they require (translation, data analysis, legal compliance checks, partner search, consultation, etc.) through the system's terminal.

[0581] Step 2:

[0582] The terminal receives user input and sends it to the server as a request in the appropriate format.

[0583] Step 3:

[0584] The server receives the request and selects the appropriate process. For example, if translation is needed, it calls natural language processing; if data analysis is needed, it calls a data analysis algorithm.

[0585] Step 4:

[0586] The server executes the specified process. For translation, it uses a natural language processing engine to translate the input text and generate an interpreted result. For data analysis, it analyzes relevant data using machine learning algorithms and generates market insights.

[0587] Step 5:

[0588] The server sends the generated results back to the terminal. This may include translation results, data analysis outputs, legal information, a list of potential partners, or problem solutions.

[0589] Step 6:

[0590] The terminal receives information from the server and displays it to the user. The user can then decide on their next action based on the information provided.

[0591] Step 7:

[0592] If the user has further questions or requests, the process is repeated from step 1.

[0593] (Example 1)

[0594] 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".

[0595] Many businesses are currently attempting to enter international markets, but they face challenges such as language barriers, difficulty obtaining market information, selecting appropriate business partners, and a lack of understanding of local laws and cultures. This makes effective strategy formulation and rapid decision-making difficult. A comprehensive support system is needed to address these issues.

[0596] 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.

[0597] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market information to propose optimal business strategies, means for explaining legal regulations and cultural practices by referring to databases on laws and culture, and means for presenting the analysis results in a visual format. This enables smooth communication in international markets with diverse languages ​​and cultures, and allows for accurate and efficient decision-making.

[0598] A "natural language processing engine" is a technology that allows computers to understand human language and convert it into an executable form, enabling real-time translation and interpretation.

[0599] "Market information" refers to data such as consumer trends, competitive landscape, and economic indicators in a specific market, and is fundamental information necessary for formulating business strategies.

[0600] A "machine learning algorithm" is a data processing technique used to analyze large amounts of data, find patterns within it, and build predictive models.

[0601] A "database of laws and cultures" is a source of information that systematically accumulates and organizes information on the laws and cultural practices of various countries, and serves as a supplementary tool for users to understand laws and cultures.

[0602] A "business partner" refers to another organization or individual with whom a cooperative relationship is established when promoting a business, and who is a partner with whom efforts are made to improve operational efficiency and expand the market.

[0603] "Interactive input" refers to information input in the form of questions and answers that users make to a server or system, with the aim of solving problems or obtaining information.

[0604] "Visual format" refers to a method of presentation that displays information in a visual form, such as graphs, charts, and diagrams, to make it easier to understand intuitively.

[0605] This invention is a support system designed to remove various barriers for small and medium-sized enterprises (SMEs) operating in the international market. This system consists of three elements: a server, a terminal, and a user, which work together to realize the invention.

[0606] The server is equipped with a natural language processing engine and translates business-related information entered by users in real time. For example, if a user enters "New product sales strategy for the Italian market" in Japanese, the server will translate it into Italian. Open-source multilingual tools can be used as the natural language processing engine for translation. The server also collects market information from multiple data sources and analyzes it using machine learning algorithms. As a result, it provides users with insights into optimal business strategies. The server uses open-source data visualization libraries to present information visually.

[0607] The terminal is an interface for users to input information and for the server to visually display the information it provides. For example, a user can send a request to the server by typing "I want to find a distribution partner in France" into the terminal. The terminal displays the translation results and market analysis results provided by the server as graphs and charts, allowing users to intuitively grasp the information.

[0608] This system can also provide detailed information on laws and culture. By referencing a comprehensive database, the server can, for example, answer a user's question about "the procedures required to establish a company in Italy" by providing information on local laws and cultural practices.

[0609] Furthermore, the server also features a business partner matching function. If a user requests an "environmentally conscious partner," the server narrows down the candidates that meet the criteria and displays a list on the user's device. This allows users to quickly find reliable collaborators.

[0610] As a concrete example, a user can input a prompt message to the generated AI model such as, "I want to sell traditional Japanese crafts in the American market. Please tell me about market research and sales strategies," and receive comprehensive support through the collaboration between the server and the terminal.

[0611] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0612] Step 1:

[0613] The user inputs business-related information through the terminal. For example, a prompt message such as "Please tell me about the distribution strategy for a new product in the Italian market" is used as input. Once input is received, the terminal prepares to send this information to the server.

[0614] Step 2:

[0615] The server analyzes the user's input text received from the terminal using a natural language processing engine. The analyzed data is translated into the specified language as needed. For example, if the user inputs in Japanese, the server will translate it into Italian, English, or another language. The output is the translated text.

[0616] Step 3:

[0617] The server collects market information based on the translated prompt text. The server retrieves data related to the Italian market from the internet and internal databases. Input information includes specific keywords related to the target market. Output is a dataset of relevant market information.

[0618] Step 4:

[0619] The server analyzes collected market data using machine learning algorithms. For example, it predicts competitive landscapes and market demand. The input is market data, and the output is insights useful for business strategies. Specifically, data cleansing and model application are performed.

[0620] Step 5:

[0621] The server visualizes the analysis results and generates them as graphs and charts. This allows users to intuitively understand market conditions based on the visual data displayed on their devices. The input is analytical insights, and the output is visualized information.

[0622] Step 6:

[0623] The terminal displays analysis results and visualization data sent from the server to the user. The user can then make decisions based on this information. Specifically, the terminal performs data rendering on a digital screen.

[0624] (Application Example 1)

[0625] 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".

[0626] In today's global business environment, small and medium-sized enterprises (SMEs) face complex challenges such as language barriers, cultural differences, region-specific laws and regulations, and the analysis of diverse market data. In particular, effective communication across different language regions, strategic decision-making, and the development of optimal marketing strategies are significant obstacles to international success. In addition, they are required to quickly and reliably find business partners and efficiently integrate these processes.

[0627] 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.

[0628] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market data to propose optimal business strategies, means for explaining laws and cultural customs by referring to a database of laws and cultures, and means for optimizing advertising to generate sales strategies in multilingual markets. This enables smooth international business exchange that transcends language and cultural barriers, allowing users to accurately grasp the most important business opportunities and formulate accurate strategies that meet diverse market conditions.

[0629] A "natural language processing engine" is a technology that translates text data from users into multiple languages ​​and performs language conversion in real time.

[0630] "Market data collection and analysis methods" refer to the process of collecting data on market trends and consumer behavior, and using machine learning algorithms to propose optimal business strategies to users.

[0631] A "database of laws and culture" is a source of information that systematically organizes information on laws and cultural practices, and provides accurate information in response to user inquiries.

[0632] "Ad optimization methods for generating sales strategies in multilingual markets" refers to technologies that generate advertising content that takes into account the language and culture of each market and deliver it to the appropriate target audience.

[0633] "Methods for identifying potential business partners" refer to methods for selecting appropriate companies and individuals based on the user's business conditions and listing highly reliable partners.

[0634] "User dialogue input analysis means" refers to technology that analyzes questions and requests from users and quickly provides corresponding solutions.

[0635] This invention is primarily implemented using three elements: a server, a terminal, and a user. Its specific form is described below.

[0636] The server functions as the core of this system, using a natural language processing engine to translate and interpret text sent by users in real time. It utilizes the Google Translate API to facilitate communication across multiple languages. Furthermore, the server collects market data, analyzes it using machine learning algorithms such as Scikit-learn, and visualizes and proposes optimal business strategies to users.

[0637] The terminal functions as the user interface, receiving user input and presenting information from the server. It utilizes React Native to enable cross-platform use. Through the terminal, users can ask questions about local laws and culture and receive information retrieved from the database.

[0638] This system enables users to develop effective sales strategies in different markets and optimize advertising in multilingual markets. Furthermore, AI-powered user dialogue analysis facilitates rapid problem-solving.

[0639] For example, if a user is planning to enter the Spanish market from Japan, this system can generate an advertising strategy in Spanish and perform targeting based on market analysis. When the user enters a prompt such as, "I want to launch this product in the Spanish market, but what points should I keep in mind when creating marketing emails in Spanish?", appropriate advice and past success stories will be provided.

[0640] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0641] Step 1:

[0642] The user accesses an input screen via a terminal and enters information about the target market and language. The input data is specific to the region where the user plans to expand. The text entered here is sent from the terminal to the server.

[0643] Step 2:

[0644] The server passes the received text data to a natural language processing engine for analysis. The purpose of this analysis is to understand the user's input and identify the requested translation or market information. As a result, the server obtains the translated text or market data to be analyzed.

[0645] Step 3:

[0646] The server collects market data and analyzes it using machine learning algorithms. Specifically, it applies statistical methods using Scikit-learn to analyze trends and competitive information in the user-specified market. As a result of the analysis, business insights tailored to the user's needs are generated.

[0647] Step 4:

[0648] The server generates advertising content based on collected and analyzed data to optimize sales strategies in multilingual markets. Ad copy and promotional content are created using a generative AI model, resulting in the construction of optimal advertising messages for the target market.

[0649] Step 5:

[0650] The terminal displays results sent from the server, presenting the user with the most suitable translation, marketing strategy, and market insights. This allows the user to determine what specific actions they should take. Furthermore, if the user has additional questions or wishes to make corrections, they can resend the information to the server through the terminal.

[0651] 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.

[0652] The system of this invention is designed as a multi-functional agent to support small and medium-sized enterprises in entering overseas markets. This system operates based on a server, terminals, an emotion engine, and user input.

[0653] The server, as the core of the system, performs translation functions using a natural language processing engine, data analysis functions, and legal and cultural navigation functions. For example, when a user is considering entering the French market, the server translates French documents into English, analyzes market trends, and proposes an entry strategy.

[0654] The emotion engine uses natural language processing technology to recognize the user's emotions in real time based on voice and text input from the user. This emotion information is used to personalize the various support services provided by the server; for example, if the user is feeling stressed, the server will present suggestions in a more careful and considerate manner.

[0655] The terminal provides a user interface, receiving user input and sending requests to the server. Through the interface, users can request market data, ask regulatory questions, or search for potential international business partners. The server's response is optimized and displayed on the terminal based on the user's emotional state, which has been analyzed by an emotion engine.

[0656] As a concrete example, suppose a user inquires about business etiquette in a certain country. In this case, the terminal sends the corresponding question to the server, and the server extracts relevant laws and cultural customs from its database. Meanwhile, the emotion engine analyzes the user's reaction, and if the user is feeling confused or anxious, the server provides more detailed explanations to resolve the issue.

[0657] This allows the present invention to improve the quality of interaction based on user emotions and support the success of overseas business activities.

[0658] The following describes the processing flow.

[0659] Step 1:

[0660] Users enter requests from their devices to perform specific business actions (e.g., language translation, data analysis, legal information retrieval, partner search, etc.).

[0661] Step 2:

[0662] The device receives user input, an emotion engine analyzes the user's voice and text to determine their emotional state, and sends the results to the server.

[0663] Step 3:

[0664] The server analyzes the user's request and selects a predetermined process (natural language processing, data analysis using machine learning, or information extraction from a legal database).

[0665] Step 4:

[0666] The server performs the necessary processing, for example, using a natural language processing engine to translate input text into a specified language, or analyzing market data to generate insights.

[0667] Step 5:

[0668] Based on the emotion analysis results from the emotion engine, the server selects a response that matches the user's emotional state and adjusts the content accordingly. For example, if the user is feeling anxious, more detailed information or additional explanations will be added.

[0669] Step 6:

[0670] The server sends the processing results and adjusted information back to the terminal.

[0671] Step 7:

[0672] The terminal displays information received from the server to the user, and the user can decide on their next action based on the presented information.

[0673] Step 8:

[0674] If the user has further questions or requests, the process is repeated from step 1.

[0675] (Example 2)

[0676] 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".

[0677] Companies aiming to enter global markets face complex challenges related to different languages, laws, and cultures. Traditional systems require significant time and resources to address these challenges, which is particularly burdensome for small and medium-sized enterprises (SMEs). Therefore, there is a need for the development of an integrated system that efficiently and effectively supports cross-cultural understanding and market strategy formulation.

[0678] 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.

[0679] In this invention, the server includes means for processing information using a natural language processing device, means for collecting and analyzing information data to make suggestions in response to user requests, and means for providing relevant information by referring to information on regulations and culture. This enables users to efficiently acquire information and receive support for decision-making regarding cross-cultural business development.

[0680] A "natural language processing device" is a device that utilizes technology to process and convert text and speech between different languages.

[0681] "Information data" refers to various types of information related to markets, laws, culture, etc., and is the data that is analyzed.

[0682] "Regulatory and cultural information" refers to knowledge and data about laws and cultural practices in a particular region or country.

[0683] "Emotional state" refers to the psychological response a user exhibits in a particular situation, and the system's response is adjusted based on this.

[0684] A "user interface" is the physical or logical means by which a user interacts with a computer system.

[0685] "Machine learning technology" is a technology that provides computer systems with the ability to learn from data and make predictions and decisions.

[0686] The system of this invention functions as a multi-functional agent to solve the various challenges that small and medium-sized enterprises face when entering overseas markets. Specifically, a server, terminal, and emotion engine work together as key components to provide the optimal solution according to the user's requirements.

[0687] The server is the heart of this system, using a natural language processing unit to perform real-time translation into foreign languages. The specific software used leverages common APIs. Furthermore, data analysis libraries can be used to collect and analyze information data. This allows for proposals tailored to the user's business needs.

[0688] The terminal serves as the user interface, directly receiving input from the user. This allows the user to proactively request market data and inquire about regulatory and cultural information. It receives responses from the server and presents the analyzed information to the user visually or audibly.

[0689] The emotion engine analyzes the user's emotional state and works to personalize the server's response. It utilizes emotion recognition technology based on voice and text input to enable interactions that take the user's psychological state into consideration.

[0690] As a concrete example, consider a scenario where a user asks about business etiquette in a particular country. The device sends this inquiry to the server, which retrieves and provides relevant information from a database of regulatory and cultural information. The sentiment engine analyzes the user's response and instructs the server to provide a more polite explanation if necessary.

[0691] An example of a prompt message would be, "Please provide information on business etiquette in France. Please explain in detail the points to be aware of and common customs." This allows users to efficiently obtain information through the system and conduct international business smoothly.

[0692] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0693] Step 1:

[0694] The user accesses the system using a terminal and enters a prompt such as, "Please provide information on business etiquette in France." The entered text data is sent from the terminal to the server.

[0695] Step 2:

[0696] The server analyzes the received prompt using natural language processing techniques. Specifically, it tokenizes the text, uses a parsing engine to understand the context, and extracts the information request. The input here is the prompt, and the output is the parsed information request.

[0697] Step 3:

[0698] The server generates queries to retrieve appropriate information data from the database based on the analysis results. The database contains international business etiquette and related regulatory information. The input is the analysis results, and the output is the relevant information data as the query result.

[0699] Step 4:

[0700] The server applies machine learning algorithms to the acquired data to extract the most relevant information based on the user's business needs. Specifically, it performs data filtering and ranking. The input is query results, and the output is refined data.

[0701] Step 5:

[0702] The emotion engine analyzes the user's response to input and evaluates their psychological state. The server uses this emotion data to adjust the tone and level of detail of the response. The input is the user's input response, and the output is the emotion evaluation result.

[0703] Step 6:

[0704] The server considers the sentiment assessment results and generates an optimized response. The final output not only satisfies the user's request but also provides emotionally sensitive information.

[0705] Step 7:

[0706] The terminal receives responses from the server and presents them to the user. The display method is text, and in some cases, audio, allowing the user to receive information concisely and clearly. The input is the server's final response, and the output is the information presented through the user interface.

[0707] (Application Example 2)

[0708] 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".

[0709] In today's international business environment, multilingual support and cross-cultural understanding are essential for small and medium-sized enterprises (SMEs) to effectively enter overseas markets. However, resources for addressing these challenges are currently limited. Furthermore, obtaining immediate, personalized feedback in language learning is difficult, and emotional support is lacking. Against this backdrop, there is a need to develop a system that efficiently proposes business strategies, supports language learning, and provides user-centric interactions.

[0710] 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.

[0711] In this invention, the server includes means for performing translation and interpretation in real time using a natural language processing engine, means for collecting and analyzing market data to propose optimal business strategies, and means for analyzing speech to support language learning and providing real-time feedback. This will enable multilingual support and promote cross-cultural understanding to facilitate international business for small and medium-sized enterprises, and further provide learning support that reduces stress for users, resulting in two-way communication that takes emotions into consideration.

[0712] A "natural language processing engine" is a technology that enables computers to understand and generate human language, and can perform language processing such as translation and interpretation in real time.

[0713] "Market data" refers to data that includes information about economic activity and consumer behavior, and is used in formulating business strategies.

[0714] A "database of laws and culture" is a collection of information that systematically organizes information about the laws and cultural customs of a particular country or region.

[0715] "Identifying potential partners" refers to the process of finding collaborators and partners suitable for business needs and compiling a list of them.

[0716] "Analysis of user dialogue input" refers to the act of analyzing user input, such as voice or text, to derive appropriate responses and suggestions.

[0717] "Language learning support" means providing real-time pronunciation checks and error feedback to help learners acquire a new language.

[0718] "Emotional analysis" is a technology that reads emotions from user voices and text information and uses it to improve the quality of interactions.

[0719] The system that implements this application analyzes voice and text data entered by the user and provides real-time translation and language learning support. The server uses a natural language processing engine to translate the input data into the desired language. Furthermore, it uses an emotion analysis engine to understand the user's emotional state and personalizes the interaction based on that information. This system uses software such as Google Cloud Natural Language API and AWS Polly for speech recognition and natural language generation.

[0720] When a user is learning a language, the device has a function to point out pronunciation and grammatical errors in real time. For this purpose, the device is equipped with a microphone and speaker to collect and analyze the user's voice. It then generates appropriate feedback and delivers it to the user through the speaker.

[0721] For example, when a user pronounces "It's a nice day today" in French, the server analyzes it and provides real-time feedback on whether the pronunciation is correct. Furthermore, if sentiment analysis determines that the user is feeling stressed, the device will send an encouraging message such as "Relax and keep going."

[0722] An example of a prompt to a generative AI model is, "Please teach the generative AI how to detect emotions from the user's voice and provide appropriate feedback." This prompt allows the system to generate appropriate responses that match the user's emotions, improving the quality of the interaction.

[0723] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0724] Step 1:

[0725] To begin pronunciation practice, the user speaks a specific phrase into the device. The device uses its microphone to collect and record the audio data. This audio data becomes the input for the next process.

[0726] Step 2:

[0727] The device sends the collected audio data to the server. The server analyzes this audio data using the Google Cloud Natural Language API. As a result of the analysis, the data is output as text and audio features.

[0728] Step 3:

[0729] The server uses text data to perform translation and grammar checks, and evaluates the accuracy of pronunciation. It uses the DeepL API and Grammarly API to detect translation and grammatical errors. This results in correct pronunciation and grammatical corrections, which are then sent to the terminal.

[0730] Step 4:

[0731] The server analyzes the voice features using IBM Watson's Tone Analyzer to infer the user's emotions. Based on the results of this analysis, it evaluates whether the user is feeling tension or stress. This emotional information is also sent to the terminal.

[0732] Step 5:

[0733] The device provides visual and audible feedback to the user based on feedback received from the server. The speaker plays messages that point out errors and encourage relaxation (e.g., "Relax and continue"). Data processing involves techniques to present the server feedback to the user in an easily understandable way.

[0734] 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.

[0735] 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.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] 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."

[0743] 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.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0755] The following is further disclosed regarding the embodiments described above.

[0756] (Claim 1)

[0757] A method for performing translation and interpretation in real time using a natural language processing engine,

[0758] A means of collecting and analyzing market data to propose the optimal business strategy,

[0759] A means of explaining laws and cultural practices by referring to databases on laws and culture,

[0760] A means of identifying and listing potential partners who meet the business requirements,

[0761] A means of analyzing user dialogue input and presenting problem-solving solutions,

[0762] A system that includes this.

[0763] (Claim 2)

[0764] The system according to claim 1, wherein a translation / interpretation means using a natural language processing engine analyzes multilingual input and generates translation results in real time in a desired language pair.

[0765] (Claim 3)

[0766] The system according to claim 1, wherein the market data analysis means analyzes the collected data using a machine learning algorithm to generate insights that are optimal for the user's business needs.

[0767] "Example 1"

[0768] (Claim 1)

[0769] A method for performing translation and interpretation in real time using a natural language processing engine,

[0770] A means of collecting and analyzing market information to propose the optimal business strategy,

[0771] A means of explaining legal regulations and cultural practices by referring to databases on laws and culture,

[0772] A means of identifying and listing potential collaborators that are suitable for the work conditions,

[0773] A means of analyzing user dialogue input to suggest solutions to problems,

[0774] A means of presenting the analysis results in a visual format,

[0775] A system that includes this.

[0776] (Claim 2)

[0777] The system according to claim 1, wherein a translation / interpretation means using a natural language processing engine analyzes multilingual input and generates translation results in real time in a desired language pair.

[0778] (Claim 3)

[0779] The system according to claim 1, wherein the market information analysis means analyzes the collected information using a machine learning algorithm and generates insights that are optimal for the user's business needs.

[0780] "Application Example 1"

[0781] (Claim 1)

[0782] A method for performing translation and interpretation in real time using a natural language processing engine,

[0783] A means of collecting and analyzing market data to propose the optimal business strategy,

[0784] A means of explaining laws and cultural practices by referring to databases on laws and culture,

[0785] A means of identifying and listing potential partners who meet the business requirements,

[0786] A means of analyzing user dialogue input and presenting problem-solving solutions,

[0787] Means for optimizing advertising to generate sales strategies in multilingual markets,

[0788] A system that includes this.

[0789] (Claim 2)

[0790] The system according to claim 1, wherein a translation / interpretation means using a natural language processing engine analyzes multilingual input and generates translation results in real time in a desired language pair.

[0791] (Claim 3)

[0792] The system according to claim 1, wherein the market data analysis means analyzes the collected data using a machine learning algorithm to generate insights that are optimal for the user's business needs.

[0793] "Example 2 of combining an emotion engine"

[0794] (Claim 1)

[0795] A means of performing information processing using a natural language processing device,

[0796] A means of collecting and analyzing information data to make suggestions that meet user requirements,

[0797] Means of providing relevant information by referring to regulatory and cultural information,

[0798] A means of analyzing the emotional state based on user input and adjusting the response accordingly,

[0799] A means of displaying a response through a user interface,

[0800] A system that includes this.

[0801] (Claim 2)

[0802] The system according to claim 1, wherein a natural language processing device analyzes data in multiple languages ​​and converts it into a desired language.

[0803] (Claim 3)

[0804] The system according to claim 1, wherein an information data analysis device analyzes collected data using machine learning technology to generate optimal insights.

[0805] "Application example 2 when combining with an emotional engine"

[0806] (Claim 1)

[0807] A method for performing translation and interpretation in real time using a natural language processing engine,

[0808] A means of collecting and analyzing market data to propose the optimal business strategy,

[0809] A means of explaining laws and cultural practices by referring to databases on laws and culture,

[0810] A means of identifying and listing potential partners who meet the business requirements,

[0811] A means of analyzing user dialogue input and presenting problem-solving solutions,

[0812] A means of analyzing speech and providing real-time feedback to support language learning,

[0813] A means of analyzing user emotions and personalizing interactions,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, wherein a translation / interpretation means using a natural language processing engine analyzes multilingual input and generates translation results in real time in a desired language pair.

[0817] (Claim 3)

[0818] The system according to claim 1, wherein the market data analysis means analyzes the collected data using a machine learning algorithm to generate insights that are optimal for the user's business needs. [Explanation of Symbols]

[0819] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A method for performing translation and interpretation in real time using a natural language processing engine, A means of collecting and analyzing market data to propose the optimal business strategy, A means of explaining laws and cultural practices by referring to databases on laws and culture, A means of identifying and listing potential partners who meet the business requirements, A means of analyzing user dialogue input and presenting problem-solving solutions, A system that includes this.

2. The system according to claim 1, wherein a translation / interpretation means using a natural language processing engine analyzes multilingual input and generates translation results in a desired language pair in real time.

3. The system according to claim 1, wherein the market data analysis means analyzes the collected data using a machine learning algorithm to generate insights that are optimal for the user's business needs.

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