System

Abstract

An object of the system according to the embodiment is to accurately translate expressions and cultural backgrounds unique to Japanese.SOLUTION: A system includes an analysis unit, a translation unit, and a provision unit. The analysis unit analyzes an expression or cultural background unique to Japanese by using the generated AI. The translation unit performs translation based on the expression or cultural background specific to Japanese analyzed by the analysis unit. The providing unit provides a result of the translation by the translation unit to a foreigner.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology has faced the challenge of making it difficult to accurately translate expressions and cultural backgrounds unique to the Japanese language.

[0005] The system according to the embodiment aims to accurately translate expressions and cultural backgrounds specific to the Japanese language. [Means for solving the problem]

[0006] The system according to the embodiment includes an analysis unit, a translation unit, and a provision unit. The analysis unit uses a generation AI to analyze expressions specific to the Japanese language or cultural background. The translation unit performs translation based on the expressions specific to the Japanese language or cultural background analyzed by the analysis unit. The provision unit provides the results translated by the translation unit to foreigners. [Effects of the Invention]

[0007] The system according to the embodiment can accurately translate expressions and cultural backgrounds specific to the Japanese language. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices 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), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The translation tool according to the embodiment of the present invention is a system that analyzes expressions and cultural background specific to the Japanese language and translates them in a way that is easy for foreigners to understand. This enables the translation tool to translate complex Japanese expressions and cultural background in a way that is easy for foreigners to understand.

[0029] A translation tool according to an embodiment includes an analysis unit, a translation unit, and a provision unit. The analysis unit uses a generation AI to analyze expressions or cultural background specific to the Japanese language. For example, the generation AI analyzes expressions or cultural background specific to the Japanese language using models such as GPT-3 and BERT. The analysis unit can also analyze idioms, proverbs, and cultural phrases as expressions specific to the Japanese language. For example, the generation AI analyzes the expression "dango over flowers" to understand the cultural meaning behind it. The analysis unit can also analyze historical, social, and religious backgrounds as cultural backgrounds. For example, the generation AI analyzes the cultural background of the word "Obon" to understand its meaning. The translation unit performs translation based on the expressions or cultural background specific to the Japanese language analyzed by the analysis unit. For example, the translation unit translates the expression "dango over flowers" to mean "valuing practical benefits." The translation unit can also translate the word "Obon" as "a traditional Japanese event for ancestral worship." Furthermore, the translation unit provides an appropriate translation based on the content analyzed by the analysis unit. The provision unit provides the results translated by the translation unit to foreigners. For example, the provision unit displays the translation results to foreigners through a web application or a mobile application. The provision unit can also send the translation results by email. This allows the translation tool according to the embodiment to translate expressions and cultural backgrounds unique to Japanese in a way that is easy for foreigners to understand. For example, this can help foreigners gain a deeper understanding of Japanese culture and language.

[0030] The analysis unit tracks the historical background or evolution of expressions unique to the Japanese language, enabling translations based on a deeper understanding. For example, the generation AI analyzes the historical background of the expression "dango over flowers" and tracks its evolution. For example, it understands that this expression has been used since the Edo period and translates it as meaning "emphasizing practical benefits." The analysis unit also analyzes the historical background of the expression "killing two birds with one stone" and tracks its evolution. For example, it understands that this expression comes from classical Chinese literature and translates it as meaning "gaining two benefits with one action." The analysis unit also analyzes the historical background of the expression "even monkeys fall from trees" and tracks its evolution. For example, it understands that this expression comes from classical Japanese literature and translates it as meaning "everyone can make mistakes." This allows translations based on a deeper understanding of the historical background and evolution of expressions unique to the Japanese language.

[0031] The analysis unit can simulate specific situations in which expressions unique to the Japanese language are used and provide appropriate translations. For example, the generation AI simulates a situation in which the expression "Dumplings are better than flowers" is used, understanding that it is used when choosing food at a festival and translating it to mean "prioritizing practical benefits." The analysis unit also simulates a situation in which the expression "Kill two birds with one stone" is used, understanding that it is used when explaining an efficient strategy in business and translating it to mean "gaining two benefits with one action." The analysis unit also simulates a situation in which the expression "Even monkeys fall from trees" is used, understanding that it is used when a professional athlete makes a mistake in a sports situation and translating it to mean "Anyone can make mistakes." This allows the system to simulate specific situations in which expressions unique to the Japanese language are used and provide appropriate translations.

[0032] The analysis unit can compare Japanese-specific expressions with similar expressions in other Asian languages and perform translation based on the commonalities and differences. For example, the generative AI compares the expression "dumplings rather than flowers" with a similar Chinese expression, analyzes the commonalities and differences, and then translates it. For instance, when comparing it with the Chinese expression "You won't have the strength to work until you've eaten," it translates to mean "emphasizing practical benefits." Also, the analysis unit compares the expression "to kill two birds with one stone" with a similar Korean expression, analyzes the commonalities and differences, and then translates it. For example, when comparing it with the Korean expression "????," it translates to mean "to gain two benefits from one action." Additionally, the analysis unit compares the expression "even a monkey can fall from a tree" with a similar Vietnamese expression, analyzes the commonalities and differences, and then translates it. For example, when comparing it with the Vietnamese expression "Con kh? c?ng co luc r?i kh?i cay," it translates to mean "anyone can fail." Thus, it can perform translation based on the commonalities and differences by comparing with similar expressions in other Asian languages.

[0033] The analysis unit can provide translations specialized for the industry or the field of expertise where Japanese-specific expressions are used. For example, the generative AI translates the expression "dumplings rather than flowers" specialized for the business industry. For instance, when explaining a business strategy that emphasizes practical benefits, it translates to mean "emphasizing practical benefits." Also, the analysis unit translates the expression "to kill two birds with one stone" specialized for the education field. For example, when explaining an efficient learning method, it translates to mean "to gain two benefits from one action." Additionally, the analysis unit translates the expression "even a monkey can fall from a tree" specialized for the sports industry. For example, when explaining a professional athlete's mistake, it translates to mean "anyone can fail." Thus, it can provide translations specialized for the industry or the field of expertise where Japanese-specific expressions are used.

[0034] When analyzing cultural background, the analysis unit can analyze video data or audio data and perform translation based on visual or audio information. For example, when the generation AI analyzes the cultural background of the word "Obon," the analysis unit analyzes related video data and translates it as "a traditional Japanese event to honor ancestors" based on visual information. When analyzing the cultural background of the word "Shichi-Go-San," the analysis unit analyzes related audio data and translates it as "a Japanese event to celebrate the growth of children" based on audio information. When analyzing the cultural background of the word "hanami," the analysis unit analyzes related video and audio data and translates it as "a traditional Japanese event to enjoy cherry blossoms" based on visual and audio information. This allows translation based on video and audio data when analyzing cultural background.

[0035] When analyzing cultural backgrounds, the analysis unit refers to literary works or historical documents, allowing for translations based on a deeper understanding. For example, when the generation AI analyzes the cultural background of the word "Obon," the analysis unit refers to related literary works and historical documents and translates it as "a traditional Japanese event to honor ancestors." When analyzing the cultural background of the word "Shichi-Go-San," the analysis unit refers to related literary works and historical documents and translates it as "a Japanese event to celebrate the growth of children." When analyzing the cultural background of the word "hanami," the analysis unit refers to related literary works and historical documents and translates it as "a traditional Japanese event to enjoy cherry blossoms." This allows for translations based on a deeper understanding by referring to literary works and historical documents when analyzing cultural backgrounds.

[0036] The analysis unit can compare a cultural background with similar backgrounds in other cultural spheres and perform translations based on similarities and differences. For example, the analysis unit's generation AI compares the word "Obon" with ancestor memorial services in other cultural spheres, analyzes the similarities and differences, and translates it as "a traditional Japanese ancestor memorial service." The analysis unit also compares the word "Shichi-Go-San" with events celebrating children's growth in other cultural spheres, analyzes the similarities and differences, and translates it as "a Japanese event celebrating children's growth." The analysis unit also compares the word "hanami" with events enjoying flowers in other cultural spheres, analyzes the similarities and differences, and translates it as "a traditional Japanese event enjoying cherry blossoms." This makes it possible to compare similar backgrounds in other cultural spheres and perform translations based on similarities and differences.

[0037] The analysis unit can provide translations that take into account contemporary social issues or trends that are influenced by cultural background. For example, the analysis unit uses the generation AI to analyze the cultural background of the word "Obon" and translate it as "a traditional Japanese event to honor ancestors" while taking into account the influence of that background on contemporary social issues and trends. The analysis unit also analyzes the cultural background of the word "Shichi-Go-San" and translates it as "a Japanese event to celebrate the growth of children" while taking into account the influence of that background on contemporary social issues and trends. The analysis unit also analyzes the cultural background of the word "hanami" (cherry blossom viewing) and translates it as "a traditional Japanese event to enjoy cherry blossoms" while taking into account the influence of that background on contemporary social issues and trends. This makes it possible to provide translations that take into account contemporary social issues and trends that are influenced by cultural background.

[0038] The analysis unit tracks the origin or evolution of words that contain meaning, enabling translations based on a deeper understanding. For example, the analysis unit analyzes the origin of the expression "bolt from the blue" and tracks its evolution. For example, the generation AI understands that this expression comes from a Chinese classic and translates it as meaning "a sudden surprise." The analysis unit also analyzes the origin of the expression "kill two birds with one stone" and tracks its evolution. For example, it understands that this expression comes from a Chinese classic and translates it as meaning "gain two benefits with one action." The analysis unit also analyzes the origin of the expression "even monkeys fall from trees" and tracks its evolution. For example, it understands that this expression comes from classical Japanese literature and translates it as meaning "everyone can make mistakes." This allows translations based on a deeper understanding by tracing the origin or evolution of words that contain meaning.

[0039] The analysis unit can simulate the situations in which the meaning-laden words are used and provide appropriate translations. For example, the generation AI can simulate situations in which the expression "bolt from the blue" is used, understand that it is used in a situation where one is surprised by a sudden event, and translate it as "sudden surprise." The analysis unit can also simulate situations in which the expression "kill two birds with one stone" is used, understand that it is used to explain an efficient strategy in a business situation, and translate it as "gain two benefits with one action." The analysis unit can also simulate situations in which the expression "even monkeys fall from trees" is used, understand that it is used when a professional athlete makes a mistake in a sports situation, and translate it as "anyone can make mistakes." This allows the system to simulate specific situations in which meaning-laden words are used and provide appropriate translations.

[0040] The analysis unit compares words that contain meaning with similar expressions in other languages ​​and can translate them based on similarities and differences. For example, the generation AI compares the expression "bolt from the blue" with similar English expressions, analyzing the similarities and differences and translating it. For example, it compares it with the English expression "bolt from the blue" and translates it as "a sudden surprise." The analysis unit also compares the expression "kill two birds with one stone" with similar French expressions and analyzes the similarities and differences and translates it. For example, it compares it with the French expression "faire d'une pierre deux coups" and translates it as "reap two benefits with one action." The analysis unit also compares the expression "even monkeys fall from trees" with similar Spanish expressions and analyzes the similarities and differences and translates it. For example, it compares it with the Spanish expression "Hasta el mejor escribano echa un borron" and translates it as "everyone makes mistakes sometimes." This allows you to compare similar expressions in other languages ​​and translate based on similarities and differences.

[0041] The analysis unit can provide translations specialized for the industry or field of expertise where the words with meanings are used. For example, the generation AI translates the expression "a bolt from the blue" to mean "a sudden surprise" when describing a sudden market fluctuation. The analysis unit also translates the expression "kill two birds with one stone" to mean "get two benefits with one action" when describing an efficient learning method. The analysis unit also translates the expression "even monkeys fall from trees" to mean "everyone can make mistakes" when describing a professional athlete's mistake. This makes it possible to provide translations specialized for industries or fields of expertise where words with meanings are used.

[0042] When analyzing a context, the analysis unit analyzes video data or audio data and can translate based on visual or audio information. For example, when the generation AI analyzes the context of the expression "Thank you for your help," the analysis unit analyzes the related video data and translates it as "Please take care of me" based on the visual information. When analyzing the context of the expression "Thank you for your help," the analysis unit analyzes the related audio data and translates it as "Thank you for your help" based on the audio information. When analyzing the context of the expression "Thank you for your help," the analysis unit analyzes the related video and audio data and translates it as "Thank you for your help" based on the visual and audio information. This allows translation to be performed based on video and audio data when analyzing a context.

[0043] When analyzing the context, the analysis unit refers to literary works or historical documents, allowing for translation based on a deeper understanding. For example, when the generation AI analyzes the context of the expression "yoroshiku onegaishimasu," the analysis unit refers to related literary works or historical documents and translates it as "yoroshiku onegaishimasu." Similarly, when analyzing the context of the expression "otsukaresama desu," the analysis unit refers to related literary works or historical documents and translates it as "otsukaresama." Similarly, when analyzing the context of the expression "o-sewa ni namari," the analysis unit refers to related literary works or historical documents and translates it as "o-sewa ni namari." This allows for translation based on a deeper understanding by referring to literary works or historical documents when analyzing the context.

[0044] The analysis unit can compare a context with similar contexts in other languages ​​and perform translation based on similarities and differences. For example, the generation AI compares the expression "Yoroshiku onegaishimasu" (Onegaishimasu) with similar contexts in English, analyzes similarities and differences, and translates it. For example, it compares it with the English "Thank you in advance" and translates it as "Douzo Yoroshiku." The analysis unit also compares the expression "Otsukaresama desu" (Thank you for your hard work) with similar contexts in French, analyzes similarities and differences, and translates it. For example, it compares it with the French "Bon travail" and translates it as "Otsukaresama." The analysis unit also compares the expression "Osewa ni namasu" (Thank you for your help) with similar contexts in Spanish, analyzes similarities and differences, and translates it. For example, it compares it with the Spanish "Gracias por su ayuda" (Thank you for your help) and translates it as "Osewa ni namasu." This allows comparisons with similar contexts in other languages ​​and translations based on similarities and differences.

[0045] The analysis unit can provide translations that take into account contemporary social issues or trends that are influenced by context. For example, the analysis unit analyzes the context of the expression "yoroshiku onegaishimasu" (one of my best wishes) and translates it as "douzoyoroshiku" (please take care of me) taking into account the impact of that context on contemporary social issues and trends. The analysis unit also analyzes the context of the expression "otsukaresama desu" (thank you for your hard work) and translates it as "otsukaresama" (thank you for your hard work) taking into account the impact of that context on contemporary social issues and trends. The analysis unit also analyzes the context of the expression "osewa ni namasu" (thank you for your help) and translates it as "osewa ni namasu" (thank you for your help) taking into account the impact of that context on contemporary social issues and trends. This makes it possible to provide translations that take into account contemporary social issues and trends that are influenced by context.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] When providing translation results, the analysis unit can refer to the user's past translation history and provide translations that match the user's preferences. For example, if a user previously translated "dango over flowers" as "prioritizing practical benefits," the same translation can be provided when a similar expression appears again. Also, if a user translates "killing two birds with one stone" as "gaining two benefits with one action," the same translation can be provided when a similar expression appears. Furthermore, if a user translates "even monkeys fall from trees" as "everyone makes mistakes sometimes," the same translation can be provided when a similar expression appears. This makes it possible to provide consistent translation results that match the user's preferences.

[0048] When providing translation results, the analysis unit can adjust the translation taking into account the user's current situation and environment. For example, if the user is in a business meeting, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user is in an educational setting, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user is participating in a sporting event, "Even monkeys fall from trees" can be translated as "Everyone makes mistakes sometimes." This allows the system to provide appropriate translation results according to the user's situation and environment.

[0049] When providing translation results, the analysis unit can adjust the translation taking into account the user's language level. For example, if the user is a beginner-level Japanese learner, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user is an intermediate-level Japanese learner, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user is an advanced-level Japanese learner, "Even monkeys fall from trees" can be translated as "Everyone can make mistakes." This makes it possible to provide appropriate translation results according to the user's language level.

[0050] When providing translation results, the analysis unit can adjust the translation taking into account the user's cultural background. For example, if the user is familiar with American culture, "Dumplings are better than flowers" can be translated as "Putting emphasis on practical benefits." If the user is familiar with Chinese culture, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user is familiar with European culture, "Even monkeys fall from trees" can be translated as "Everyone makes mistakes sometimes." This makes it possible to provide appropriate translation results according to the user's cultural background.

[0051] When providing translation results, the analysis unit can adjust the translation taking into account the user's field of expertise. For example, if the user is an expert in the business field, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user is an expert in the education field, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user is an expert in the sports field, "Even monkeys fall from trees" can be translated as "Everyone can make mistakes." This makes it possible to provide appropriate translation results according to the user's field of expertise.

[0052] The processing flow of the first embodiment will be briefly explained below.

[0053] Step 1: The analysis unit uses the generative AI to analyze expressions unique to Japanese or cultural background. For example, the generative AI uses models such as GPT-3 or BERT to analyze expressions unique to Japanese and cultural background. The analysis unit can also analyze idioms, proverbs, cultural phrases, and other expressions unique to Japanese. For example, the generative AI analyzes the expression "dango over flowers" and understands the cultural meaning behind it. Furthermore, the analysis unit can analyze historical, social, and religious backgrounds as cultural background. For example, the generative AI analyzes the cultural background of the word "Obon" and understands its meaning. Step 2: The translation unit performs translation based on the Japanese-specific expressions or cultural background analyzed by the analysis unit. For example, the translation unit translates the expression "dango over flowers" to mean "prioritizing practical benefits." The translation unit can also translate the word "Obon" as "a traditional Japanese event for ancestral worship." The translation unit then provides an appropriate translation based on the content analyzed by the analysis unit. Step 3: The providing unit provides the translation result to the foreigner. For example, the providing unit displays the translation result to the foreigner through a web application or a mobile application. The providing unit can also send the translation result by email.

[0054] (Example 2) The translation tool according to the embodiment of the present invention is a system that analyzes expressions and cultural background specific to the Japanese language and translates them in a way that is easy for foreigners to understand. This enables the translation tool to translate complex Japanese expressions and cultural background in a way that is easy for foreigners to understand.

[0055] A translation tool according to an embodiment includes an analysis unit, a translation unit, and a provision unit. The analysis unit uses a generation AI to analyze expressions or cultural background specific to the Japanese language. For example, the generation AI analyzes expressions or cultural background specific to the Japanese language using models such as GPT-3 and BERT. The analysis unit can also analyze idioms, proverbs, and cultural phrases as expressions specific to the Japanese language. For example, the generation AI analyzes the expression "dango over flowers" to understand the cultural meaning behind it. The analysis unit can also analyze historical, social, and religious backgrounds as cultural backgrounds. For example, the generation AI analyzes the cultural background of the word "Obon" to understand its meaning. The translation unit performs translation based on the expressions or cultural background specific to the Japanese language analyzed by the analysis unit. For example, the translation unit translates the expression "dango over flowers" to mean "valuing practical benefits." The translation unit can also translate the word "Obon" as "a traditional Japanese event for ancestral worship." Furthermore, the translation unit provides an appropriate translation based on the content analyzed by the analysis unit. The provision unit provides the results translated by the translation unit to foreigners. For example, the provision unit displays the translation results to foreigners through a web application or a mobile application. The provision unit can also send the translation results by email. This allows the translation tool according to the embodiment to translate expressions and cultural backgrounds unique to Japanese in a way that is easy for foreigners to understand. For example, this can help foreigners gain a deeper understanding of Japanese culture and language.

[0056] The analysis unit tracks the historical background or evolution of expressions unique to the Japanese language, enabling translations based on a deeper understanding. For example, the generation AI analyzes the historical background of the expression "dango over flowers" and tracks its evolution. For example, it understands that this expression has been used since the Edo period and translates it as meaning "emphasizing practical benefits." The analysis unit also analyzes the historical background of the expression "killing two birds with one stone" and tracks its evolution. For example, it understands that this expression comes from classical Chinese literature and translates it as meaning "gaining two benefits with one action." The analysis unit also analyzes the historical background of the expression "even monkeys fall from trees" and tracks its evolution. For example, it understands that this expression comes from classical Japanese literature and translates it as meaning "everyone can make mistakes." This allows translations based on a deeper understanding of the historical background and evolution of expressions unique to the Japanese language.

[0057] The analysis unit can simulate specific situations in which expressions unique to the Japanese language are used and provide appropriate translations. For example, the generation AI simulates a situation in which the expression "Dumplings are better than flowers" is used, understanding that it is used when choosing food at a festival and translating it to mean "prioritizing practical benefits." The analysis unit also simulates a situation in which the expression "Kill two birds with one stone" is used, understanding that it is used when explaining an efficient strategy in business and translating it to mean "gaining two benefits with one action." The analysis unit also simulates a situation in which the expression "Even monkeys fall from trees" is used, understanding that it is used when a professional athlete makes a mistake in a sports situation and translating it to mean "Anyone can make mistakes." This allows the system to simulate specific situations in which expressions unique to the Japanese language are used and provide appropriate translations.

[0058] The analysis unit can analyze the emotional meaning of Japanese-specific expressions using an emotion estimation function and perform translations that reflect that emotion. For example, the analysis unit analyzes the emotional nuance of the expression "dumplings rather than flowers" by a generative AI and translates it, for example, reflecting a positive emotion towards emphasizing practical benefits. Also, the analysis unit analyzes the emotional nuance of the expression "to kill two birds with one stone" and translates it, for example, reflecting a sense of satisfaction towards efficient actions. Also, the analysis unit analyzes the emotional nuance of the expression "even a monkey can fall from a tree" and translates it, for example, reflecting an emotion of empathy or comfort towards failure. Thus, it is possible to analyze the emotional nuance of Japanese-specific expressions and perform translations that reflect that emotion.

[0059] The analysis unit can compare Japanese-specific expressions with similar expressions in other Asian languages and perform translations based on the commonalities and differences. For example, the analysis unit compares the expression "dumplings rather than flowers" with a similar expression in Chinese by a generative AI, analyzes the commonalities and differences, and translates it. For example, when compared with "You need to eat before you have the strength to work", it is translated in the sense of "emphasizing practical benefits". Also, the analysis unit compares the expression "to kill two birds with one stone" with a similar expression in Korean, analyzes the commonalities and differences, and translates it. For example, when compared with "????" in Korean, it is translated in the sense of "to gain two benefits with one action". Also, the analysis unit compares the expression "even a monkey can fall from a tree" with a similar expression in Vietnamese, analyzes the commonalities and differences, and translates it. For example, when compared with "Con kh? c?ng co luc r?i kh?i cay" in Vietnamese, it is translated in the sense of "anyone can fail". Thus, it is possible to compare with similar expressions in other Asian languages and perform translations based on the commonalities and differences.

[0060] The analysis unit can provide translations specialized for the industry or field of expertise where expressions unique to Japanese are used. For example, the analysis unit uses a generation AI to translate the expression "dango over flowers" in a way that is specialized for the business industry. For example, when explaining a business strategy that emphasizes practical benefits, the analysis unit translates it to mean "emphasize practical benefits." The analysis unit also translates the expression "kill two birds with one stone" in a way that is specialized for the education field. For example, when explaining an efficient learning method, the analysis unit translates it to mean "get two benefits with one action." The analysis unit also translates the expression "even monkeys fall from trees" in a way that is specialized for the sports industry. For example, when explaining mistakes made by professional athletes, the analysis unit translates it to mean "anyone can make mistakes." This makes it possible to provide translations specialized for industries or fields of expertise where expressions unique to Japanese are used.

[0061] The analysis unit uses the emotion estimation function to analyze the emotional impact that Japanese-specific expressions have on foreigners and can perform translations that minimize that impact. For example, the generation AI analyzes the emotional impact that the expression "dango over flowers" has on foreigners, translating it to mean "prioritizing practical benefits" to avoid misunderstandings about prioritizing practical benefits. The analysis unit also analyzes the emotional impact that the expression "killing two birds with one stone" has on foreigners and translating it to mean "gaining two benefits with one action" to avoid misunderstandings about efficient behavior. The analysis unit also analyzes the emotional impact that the expression "even monkeys fall from trees" has on foreigners and translating it to mean "everyone can fail" to reflect feelings of empathy and comfort for failure. This allows for translations that minimize the emotional impact that Japanese-specific expressions have on foreigners.

[0062] When analyzing cultural background, the analysis unit can analyze video data or audio data and perform translation based on visual or audio information. For example, when the generation AI analyzes the cultural background of the word "Obon," the analysis unit analyzes related video data and translates it as "a traditional Japanese event to honor ancestors" based on visual information. When analyzing the cultural background of the word "Shichi-Go-San," the analysis unit analyzes related audio data and translates it as "a Japanese event to celebrate the growth of children" based on audio information. When analyzing the cultural background of the word "hanami," the analysis unit analyzes related video and audio data and translates it as "a traditional Japanese event to enjoy cherry blossoms" based on visual and audio information. This allows translation based on video and audio data when analyzing cultural background.

[0063] When analyzing cultural backgrounds, the analysis unit refers to literary works or historical documents, allowing for translations based on a deeper understanding. For example, when the generation AI analyzes the cultural background of the word "Obon," the analysis unit refers to related literary works and historical documents and translates it as "a traditional Japanese event to honor ancestors." When analyzing the cultural background of the word "Shichi-Go-San," the analysis unit refers to related literary works and historical documents and translates it as "a Japanese event to celebrate the growth of children." When analyzing the cultural background of the word "hanami," the analysis unit refers to related literary works and historical documents and translates it as "a traditional Japanese event to enjoy cherry blossoms." This allows for translations based on a deeper understanding by referring to literary works and historical documents when analyzing cultural backgrounds.

[0064] The analysis unit uses the emotion estimation function to analyze the emotional nuances of cultural backgrounds and can produce translations that reflect those emotions. For example, the analysis unit uses a generation AI to analyze the emotional nuances of the word "Obon" (bon festival), translating it as "a traditional Japanese event to honor ancestors" to reflect feelings of respect and gratitude for ancestor worship. The analysis unit also analyzes the emotional nuances of the word "Shichi-Go-San" (7-5-3), translating it as "a Japanese event to celebrate the growth of children" to reflect feelings of joy at celebrating a child's growth. The analysis unit also analyzes the emotional nuances of the word "hanami" (cherry blossom viewing), translating it as "a traditional Japanese event to enjoy cherry blossoms" to reflect feelings of joy and emotion at enjoying cherry blossoms. This makes it possible to analyze the emotional nuances of cultural backgrounds and produce translations that reflect those emotions.

[0065] The analysis unit can compare a cultural background with similar backgrounds in other cultural spheres and perform translations based on similarities and differences. For example, the analysis unit's generation AI compares the word "Obon" with ancestor memorial services in other cultural spheres, analyzes the similarities and differences, and translates it as "a traditional Japanese ancestor memorial service." The analysis unit also compares the word "Shichi-Go-San" with events celebrating children's growth in other cultural spheres, analyzes the similarities and differences, and translates it as "a Japanese event celebrating children's growth." The analysis unit also compares the word "hanami" with events enjoying flowers in other cultural spheres, analyzes the similarities and differences, and translates it as "a traditional Japanese event enjoying cherry blossoms." This makes it possible to compare similar backgrounds in other cultural spheres and perform translations based on similarities and differences.

[0066] The analysis unit can provide translations that take into account contemporary social issues or trends that are influenced by cultural background. For example, the analysis unit uses the generation AI to analyze the cultural background of the word "Obon" and translate it as "a traditional Japanese event to honor ancestors" while taking into account the influence of that background on contemporary social issues and trends. The analysis unit also analyzes the cultural background of the word "Shichi-Go-San" and translates it as "a Japanese event to celebrate the growth of children" while taking into account the influence of that background on contemporary social issues and trends. The analysis unit also analyzes the cultural background of the word "hanami" (cherry blossom viewing) and translates it as "a traditional Japanese event to enjoy cherry blossoms" while taking into account the influence of that background on contemporary social issues and trends. This makes it possible to provide translations that take into account contemporary social issues and trends that are influenced by cultural background.

[0067] The analysis unit uses the emotion estimation function to analyze the emotional impact that cultural background has on foreigners and can perform translations that minimize that impact. For example, the analysis unit uses a generation AI to analyze the emotional impact of the word "Obon" and translate it as "a traditional Japanese event to honor ancestors," reflecting feelings of respect and gratitude for ancestor worship. The analysis unit also analyzes the emotional impact of the word "Shichi-Go-San" and translates it as "a Japanese event to celebrate the growth of children," reflecting feelings of joy at celebrating a child's growth. The analysis unit also analyzes the emotional impact of the word "hanami" and translates it as "a traditional Japanese event to enjoy cherry blossoms," reflecting feelings of joy and emotion at enjoying cherry blossoms. This allows for translations that minimize the emotional impact that cultural background has on foreigners.

[0068] The analysis unit tracks the origin or evolution of words that contain meaning, enabling translations based on a deeper understanding. For example, the analysis unit analyzes the origin of the expression "bolt from the blue" and tracks its evolution. For example, the generation AI understands that this expression comes from a Chinese classic and translates it as meaning "a sudden surprise." The analysis unit also analyzes the origin of the expression "kill two birds with one stone" and tracks its evolution. For example, it understands that this expression comes from a Chinese classic and translates it as meaning "gain two benefits with one action." The analysis unit also analyzes the origin of the expression "even monkeys fall from trees" and tracks its evolution. For example, it understands that this expression comes from classical Japanese literature and translates it as meaning "everyone can make mistakes." This allows translations based on a deeper understanding by tracing the origin or evolution of words that contain meaning.

[0069] The analysis unit can simulate the situations in which the meaning-laden words are used and provide appropriate translations. For example, the generation AI can simulate situations in which the expression "bolt from the blue" is used, understand that it is used in a situation where one is surprised by a sudden event, and translate it as "sudden surprise." The analysis unit can also simulate situations in which the expression "kill two birds with one stone" is used, understand that it is used to explain an efficient strategy in a business situation, and translate it as "gain two benefits with one action." The analysis unit can also simulate situations in which the expression "even monkeys fall from trees" is used, understand that it is used when a professional athlete makes a mistake in a sports situation, and translate it as "anyone can make mistakes." This allows the system to simulate specific situations in which meaning-laden words are used and provide appropriate translations.

[0070] The analysis unit uses the emotion estimation function to analyze the emotional nuances of words that contain meaning and can produce translations that reflect those emotions. For example, the generation AI analyzes the emotional nuances of the expression "a bolt from the blue" and translates it to reflect, for example, feelings of surprise or shock at a sudden event. The analysis unit also analyzes the emotional nuances of the expression "killing two birds with one stone" and translates it to reflect, for example, feelings of satisfaction at efficient action. The analysis unit also analyzes the emotional nuances of the expression "even monkeys fall from trees" and translates it to reflect, for example, feelings of empathy and comfort at failure. In this way, the analysis unit can analyze the emotional nuances of words that contain meaning and produce translations that reflect those emotions.

[0071] The analysis unit compares words that contain meaning with similar expressions in other languages ​​and can translate them based on similarities and differences. For example, the generation AI compares the expression "bolt from the blue" with similar English expressions, analyzing the similarities and differences and translating it. For example, it compares it with the English expression "bolt from the blue" and translates it as "a sudden surprise." The analysis unit also compares the expression "kill two birds with one stone" with similar French expressions and analyzes the similarities and differences and translates it. For example, it compares it with the French expression "faire d'une pierre deux coups" and translates it as "reap two benefits with one action." The analysis unit also compares the expression "even monkeys fall from trees" with similar Spanish expressions and analyzes the similarities and differences and translates it. For example, it compares it with the Spanish expression "Hasta el mejor escribano echa un borron" and translates it as "everyone makes mistakes sometimes." This allows you to compare similar expressions in other languages ​​and translate based on similarities and differences.

[0072] The analysis unit can provide translations specialized for the industry or field of expertise where the words with meanings are used. For example, the generation AI translates the expression "a bolt from the blue" to mean "a sudden surprise" when describing a sudden market fluctuation. The analysis unit also translates the expression "kill two birds with one stone" to mean "get two benefits with one action" when describing an efficient learning method. The analysis unit also translates the expression "even monkeys fall from trees" to mean "everyone can make mistakes" when describing a professional athlete's mistake. This makes it possible to provide translations specialized for industries or fields of expertise where words with meanings are used.

[0073] The analysis unit uses the emotion estimation function to analyze the emotional impact that words loaded with meaning have on foreigners and can perform translations that minimize that impact. For example, the analysis unit uses a generation AI to analyze the emotional impact that the expression "a bolt from the blue" has on foreigners and translates it to reflect, for example, feelings of surprise or shock at a sudden event. The analysis unit also analyzes the emotional impact that the expression "killing two birds with one stone" has on foreigners and translates it to reflect, for example, feelings of satisfaction at efficient action. The analysis unit also analyzes the emotional impact that the expression "even monkeys fall from trees" has on foreigners and translates it to reflect, for example, feelings of empathy and comfort at failure. This makes it possible to perform translations that minimize the emotional impact that words loaded with meaning have on foreigners.

[0074] When analyzing a context, the analysis unit analyzes video data or audio data and can translate based on visual or audio information. For example, when the generation AI analyzes the context of the expression "Thank you for your help," the analysis unit analyzes the related video data and translates it as "Please take care of me" based on the visual information. When analyzing the context of the expression "Thank you for your help," the analysis unit analyzes the related audio data and translates it as "Thank you for your help" based on the audio information. When analyzing the context of the expression "Thank you for your help," the analysis unit analyzes the related video and audio data and translates it as "Thank you for your help" based on the visual and audio information. This allows translation to be performed based on video and audio data when analyzing a context.

[0075] When analyzing the context, the analysis unit refers to literary works or historical documents, allowing for translation based on a deeper understanding. For example, when the generation AI analyzes the context of the expression "yoroshiku onegaishimasu," the analysis unit refers to related literary works or historical documents and translates it as "yoroshiku onegaishimasu." Similarly, when analyzing the context of the expression "otsukaresama desu," the analysis unit refers to related literary works or historical documents and translates it as "otsukaresama." Similarly, when analyzing the context of the expression "o-sewa ni namari," the analysis unit refers to related literary works or historical documents and translates it as "o-sewa ni namari." This allows for translation based on a deeper understanding by referring to literary works or historical documents when analyzing the context.

[0076] The analysis unit uses the emotion estimation function to analyze the emotional nuances of the context and can perform a translation that reflects those emotions. For example, the analysis unit analyzes the emotional nuances of the expression "Thank you in advance" by the generation AI and translates it as "Thank you very much," reflecting, for example, feelings of politeness and respect. The analysis unit also analyzes the emotional nuances of the expression "Thank you for your hard work" and translates it as "Thank you for your hard work," reflecting, for example, feelings of appreciation. The analysis unit also analyzes the emotional nuances of the expression "Thank you for your help" and translates it as "Thank you for your help," reflecting, for example, feelings of gratitude and respect. In this way, the emotional nuances of the context can be analyzed and a translation that reflects those emotions can be performed.

[0077] The analysis unit can compare a context with similar contexts in other languages ​​and perform translation based on similarities and differences. For example, the generation AI compares the expression "Yoroshiku onegaishimasu" (Onegaishimasu) with similar contexts in English, analyzes similarities and differences, and translates it. For example, it compares it with the English "Thank you in advance" and translates it as "Douzo Yoroshiku." The analysis unit also compares the expression "Otsukaresama desu" (Thank you for your hard work) with similar contexts in French, analyzes similarities and differences, and translates it. For example, it compares it with the French "Bon travail" and translates it as "Otsukaresama." The analysis unit also compares the expression "Osewa ni namasu" (Thank you for your help) with similar contexts in Spanish, analyzes similarities and differences, and translates it. For example, it compares it with the Spanish "Gracias por su ayuda" (Thank you for your help) and translates it as "Osewa ni namasu." This allows comparisons with similar contexts in other languages ​​and translations based on similarities and differences.

[0078] The analysis unit can provide translations that take into account contemporary social issues or trends that are influenced by context. For example, the analysis unit analyzes the context of the expression "yoroshiku onegaishimasu" (one of my best wishes) and translates it as "douzoyoroshiku" (please take care of me) taking into account the impact of that context on contemporary social issues and trends. The analysis unit also analyzes the context of the expression "otsukaresama desu" (thank you for your hard work) and translates it as "otsukaresama" (thank you for your hard work) taking into account the impact of that context on contemporary social issues and trends. The analysis unit also analyzes the context of the expression "osewa ni namasu" (thank you for your help) and translates it as "osewa ni namasu" (thank you for your help) taking into account the impact of that context on contemporary social issues and trends. This makes it possible to provide translations that take into account contemporary social issues and trends that are influenced by context.

[0079] The analysis unit uses the emotion estimation function to analyze the emotional impact of the context on foreigners and can perform translations that minimize that impact. For example, the analysis unit analyzes the emotional impact of the expression "yoroshiku onegaishimasu" (one of my best wishes) and translates it as "douzoyoroshiku" (thank you for your help), reflecting feelings of politeness and respect. The analysis unit also analyzes the emotional impact of the expression "otsukaresama desu" (thank you for your hard work), translating it as "otsukaresama" (thank you for your hard work), reflecting feelings of appreciation. The analysis unit also analyzes the emotional impact of the expression "o-sekai ni na ni ni ni naru" (thank you for your help), translating it as "o-sekai ni na ni naru" (thank you for your help), reflecting feelings of gratitude and respect. This allows for translations that minimize the emotional impact of the context on foreigners.

[0080] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0081] The analysis unit can estimate the user's emotions and adjust the translation results based on the estimated user emotions. For example, if the user is feeling surprised, the translation unit can reflect that emotion and translate "a bolt from the blue" as "sudden surprise." If the user is feeling satisfied, the translation unit can translate "kill two birds with one stone" as "get two benefits with one action." If the user is feeling empathy or comfort, the translation unit can translate "even monkeys fall from trees" as "everyone can make mistakes." This makes it possible to provide translation results that correspond to the user's emotions.

[0082] When providing translation results, the analysis unit can refer to the user's past translation history and provide translations that match the user's preferences. For example, if a user previously translated "dango over flowers" as "prioritizing practical benefits," the same translation can be provided when a similar expression appears again. Also, if a user translates "killing two birds with one stone" as "gaining two benefits with one action," the same translation can be provided when a similar expression appears. Furthermore, if a user translates "even monkeys fall from trees" as "everyone makes mistakes sometimes," the same translation can be provided when a similar expression appears. This makes it possible to provide consistent translation results that match the user's preferences.

[0083] When providing translation results, the analysis unit can adjust the translation taking into account the user's current situation and environment. For example, if the user is in a business meeting, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user is in an educational setting, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user is participating in a sporting event, "Even monkeys fall from trees" can be translated as "Everyone makes mistakes sometimes." This allows the system to provide appropriate translation results according to the user's situation and environment.

[0084] The analysis unit can estimate the user's emotions and adjust the tone of the translation results based on the estimated user emotions. For example, if the user has positive emotions, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user feels satisfaction with efficient behavior, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user feels empathy or comfort for failure, "Even monkeys fall from trees" can be translated as "Everyone can fail." This makes it possible to provide translation results with a tone that matches the user's emotions.

[0085] When providing translation results, the analysis unit can adjust the translation taking into account the user's language level. For example, if the user is a beginner-level Japanese learner, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user is an intermediate-level Japanese learner, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user is an advanced-level Japanese learner, "Even monkeys fall from trees" can be translated as "Everyone can make mistakes." This makes it possible to provide appropriate translation results according to the user's language level.

[0086] The analysis unit can estimate the user's emotions and adjust the level of detail in the translation results based on the estimated user's emotions. For example, if the user is looking for detailed information, the translation unit can explain "bigger than flowers" in detail, meaning "prioritizing practical benefits." If the user is looking for concise information, the translation unit can briefly translate "kill two birds with one stone" as "gain two benefits with one action." Furthermore, if the user is feeling empathy or comfort, the translation unit can explain "even monkeys fall from trees" in detail, saying "everyone makes mistakes sometimes." This makes it possible to provide translation results with a level of detail that matches the user's emotions.

[0087] When providing translation results, the analysis unit can adjust the translation taking into account the user's cultural background. For example, if the user is familiar with American culture, "Dumplings are better than flowers" can be translated as "Putting emphasis on practical benefits." If the user is familiar with Chinese culture, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user is familiar with European culture, "Even monkeys fall from trees" can be translated as "Everyone makes mistakes sometimes." This makes it possible to provide appropriate translation results according to the user's cultural background.

[0088] The analysis unit can estimate the user's emotions and adjust the way the translation results are expressed based on the estimated user emotions. For example, if the user has positive emotions, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user feels satisfied with efficient behavior, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user feels empathy or comfort for failure, "Even monkeys fall from trees" can be translated as "Everyone can fail." This makes it possible to provide translation results that use expressions that match the user's emotions.

[0089] When providing translation results, the analysis unit can adjust the translation taking into account the user's field of expertise. For example, if the user is an expert in the business field, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user is an expert in the education field, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user is an expert in the sports field, "Even monkeys fall from trees" can be translated as "Everyone can make mistakes." This makes it possible to provide appropriate translation results according to the user's field of expertise.

[0090] The analysis unit can estimate the user's emotions and adjust the wording of the translation result based on the estimated user emotions. For example, if the user has positive emotions, "Dumplings are better than flowers" can be translated as "Prioritize practical benefits." If the user feels satisfaction with efficient behavior, "Kill two birds with one stone" can be translated as "Get two benefits with one action." Furthermore, if the user feels empathy or comfort for failure, "Even monkeys fall from trees" can be translated as "Everyone can fail." This makes it possible to provide translation results with wording that matches the user's emotions.

[0091] The processing flow of the second embodiment will be briefly explained below.

[0092] Step 1: The analysis unit uses the generative AI to analyze expressions unique to Japanese or cultural background. For example, the generative AI uses models such as GPT-3 or BERT to analyze expressions unique to Japanese and cultural background. The analysis unit can also analyze idioms, proverbs, cultural phrases, and other expressions unique to Japanese. For example, the generative AI analyzes the expression "dango over flowers" and understands the cultural meaning behind it. Furthermore, the analysis unit can analyze historical, social, and religious backgrounds as cultural background. For example, the generative AI analyzes the cultural background of the word "Obon" and understands its meaning. Step 2: The translation unit performs translation based on the Japanese-specific expressions or cultural background analyzed by the analysis unit. For example, the translation unit translates the expression "dango over flowers" to mean "prioritizing practical benefits." The translation unit can also translate the word "Obon" as "a traditional Japanese event for ancestral worship." The translation unit then provides an appropriate translation based on the content analyzed by the analysis unit. Step 3: The providing unit provides the translation result to the foreigner. For example, the providing unit displays the translation result to the foreigner through a web application or a mobile application. The providing unit can also send the translation result by email.

[0093] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0094] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0095] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0096] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0097] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0098] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0099] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0100] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0101] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0102] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0103] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0104] 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.

[0105] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0106] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0107] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0108] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0109] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0110] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0111] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0112] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0113] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0114] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0115] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0116] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0117] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0118] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0119] 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.

[0120] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0121] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0122] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0123] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0124] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0125] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0126] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0127] 7, a 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.

[0128] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0129] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0130] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0131] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0132] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0133] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0134] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0135] 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.

[0136] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0137] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0138] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0139] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0140] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0141] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0142] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0143] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0144] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0145] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0146] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0147] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0148] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0149] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0150] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0151] 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.

[0152] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0153] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0154] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific process may be a single processor.

[0155] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0156] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0157] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0158] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0159] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0160] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. An analysis part that uses generative AI to analyze expressions specific to Japanese or cultural background; a translation unit that performs translation based on the Japanese-specific expressions or cultural background analyzed by the analysis unit; a providing unit that provides the results of the translation by the translation unit to foreigners; A system characterized by:

2. The analysis unit Compare the Japanese-specific expressions with similar expressions in other Asian languages ​​and translate them based on similarities and differences.

2. The system of claim 1.

3. The analysis unit When analyzing cultural background, video or audio data is analyzed and translation is performed based on visual or auditory information.

2. The system of claim 1.

4. The analysis unit Trace the origin or evolution of words that contain meanings to translate with a deeper understanding 2. The system of claim 1.

5. The analysis unit Analyzes the emotional nuances of the context and translates to reflect those emotions 2. The system of claim 1.

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