system

Abstract

The system according to the embodiment aims to enable beginners to receive advice in real time while learning mahjong. [Solution] A system according to an embodiment includes a tutorial function, an advice function, and a support function. The tutorial function provides a tutorial using AR. The advice function provides real-time advice based on the content learned through the tutorial function. The support function provides communication support based on information obtained through the advice function.

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 the drawback of lacking real-time support for beginners learning the rules and strategies of mahjong.

[0005] The system according to the embodiment aims to enable beginners to receive advice in real time while learning mahjong. [Means for solving the problem]

[0006] The system according to the embodiment includes a tutorial function, an advice function, and a support function. The tutorial function provides a tutorial using AR. The advice function provides real-time advice based on the content learned through the tutorial function. The support function provides communication support based on the information obtained through the advice function. [Effects of the Invention]

[0007] The system according to the embodiment allows beginners to receive real-time advice while learning mahjong. [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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[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) A mahjong support system according to an embodiment of the present invention provides tutorials and coaching functions using augmented reality (AR) for beginners who want to enjoy mahjong at offline mahjong parlors. This mahjong support system allows users to launch an app and learn mahjong rules, tile types, and hand explanations through AR. Then, users can receive real-time advice during the game. For example, advice is displayed on which tiles to discard and which hands to aim for. This helps to address common hurdles for beginners and supports a smooth initial experience. Furthermore, the mahjong support system is designed to allow beginners who are anxious about communicating with mahjong parlor staff or playing against other players to enjoy mahjong with confidence. For example, the system supports communication with parlor staff and teaches necessary etiquette and rules during matches against other players. This allows even beginners to enjoy mahjong with confidence. Furthermore, the mahjong support system contributes to the revitalization of the mahjong industry by collaborating with the industry to create a welcoming environment for beginners. For example, the system provides information on events and campaigns aimed at beginners, creating an environment that makes it easy for beginners to participate. This system can be expanded to other table games, becoming a powerful tool that will boost the industry beyond the scope of the application. For example, similar tutorial and coaching functions could be provided for other table games such as poker and chess to help beginners enjoy the game. This allows beginners to smoothly learn and enjoy mahjong.

[0029] The mahjong support system according to the embodiment includes a tutorial function, an advice function, and a support function. The tutorial function uses AR to provide explanations of mahjong rules, tile types, and hand combinations. For example, when a user launches the app, the tutorial function visually explains the basic rules of mahjong using AR technology. The tutorial function also provides explanations of tile types and hand combinations, making it easier for beginners to understand the basics of mahjong. For example, AR technology can be used to visually display the names of each tile and hand combinations. Furthermore, the tutorial function provides interactive functions that allow users to learn while actually manipulating tiles. For example, when a user selects a tile, detailed information about that tile is displayed. The advice function provides real-time advice on which tile to discard and which hand to aim for. For example, when a user selects a tile during a game, the advice function displays the next tile to discard and the hand to aim for in real time. The advice function can also provide customized advice based on the user's playing style. For example, if a user prefers an aggressive playing style, the advice function suggests an aggressive strategy. The support function teaches the user the manners and rules necessary for communicating with staff at a mahjong parlor and playing against other players. For example, the support function teaches the user greetings and manners when entering a mahjong parlor. The support function can also display the rules and manners necessary during a match in real time. For example, if the user has trouble during a match, the support function provides appropriate advice. As a result, the mahjong support system according to the embodiment allows beginners to smoothly learn and enjoy mahjong.

[0030] The mahjong support system has a function for horizontal expansion to other table games. The function for horizontal expansion to other table games supports other table games such as poker and chess. For example, in the case of poker, the mahjong support system can provide explanations of poker rules and hands using AR. It can also provide advice in real time during a poker game. For example, it displays advice on which card to discard next and which hand to aim for. It also provides a support function that teaches the etiquette and rules necessary during a poker game. For example, if a player is in trouble during a poker game, the support function provides appropriate advice. In the case of chess, the mahjong support system can provide chess rules and strategies using AR. For example, it visually explains basic chess piece movements and strategies. It can also provide advice in real time during a chess game. For example, it displays advice on which piece to move next and which strategy to adopt. It also provides a support function that teaches the etiquette and rules necessary during a chess game. For example, if a player is in trouble during a chess game, the support function provides appropriate advice. This makes it possible to support other table games.

[0031] The mahjong support system has an event information provision function. The event information provision function provides, for example, information on events and campaigns for beginners. For example, the mahjong support system can provide information on mahjong classes and tournaments for beginners. It can also collaborate with the mahjong industry to plan events that are easy for beginners to participate in and provide information about them. For example, it can provide information on mahjong tournaments and social gatherings for beginners. Furthermore, the mahjong support system can provide event information customized based on the user's interests. For example, if a user lives in a specific area, it can provide information on mahjong events held in that area. Also, if the user belongs to a specific mahjong club, it can provide information on events held at that club. This makes it possible to provide event information for beginners.

[0032] The tutorial function can use AR to provide explanations of mahjong rules, tile types, and hand combinations. The explanations of mahjong rules, tile types, and hand combinations include, for example, basic rules and hand combinations. For example, when a user launches the app, the tutorial function uses AR technology to visually explain the basic rules of mahjong. The tutorial function also provides explanations of tile types and hand combinations, making it easier for beginners to understand the basics of mahjong. For example, AR technology can be used to visually display the names of each tile and hand combinations. Furthermore, the tutorial function provides an interactive function that allows users to learn by actually manipulating tiles. For example, when a user selects a tile, detailed information about that tile is displayed. This makes it easier for beginners to learn the basics of mahjong.

[0033] The advice function can provide real-time advice on which tile to discard and which hand to aim for. Real-time advice includes, for example, suggestions for the next tile to discard and the hand to aim for. For example, when a user selects a tile during a game, the advice function displays the next tile to discard and the hand to aim for in real time. The advice function can also provide customized advice based on the user's playing style. For example, if the user prefers an offensive playing style, the advice function can suggest an offensive strategy. Furthermore, the advice function can analyze the user's past playing history and provide optimal advice based on that. For example, the advice function can provide advice on how to avoid making the same mistakes based on mistakes made by the user in the past. This allows beginners to make appropriate decisions during the game.

[0034] The support function can teach etiquette and rules while communicating with mahjong parlor staff and playing against other players. Examples of etiquette and rules include greetings upon entering the parlor and etiquette during a match. For example, the support function can teach the user how to greet and behave when entering a mahjong parlor. The support function can also display the rules and etiquette necessary during a match in real time. For example, if a user has difficulty during a match, the support function can provide appropriate advice. Furthermore, the support function can estimate the user's emotions and adjust the communication support method based on that information. For example, if the user is nervous, the support function can support communication with kind words. This allows beginners to enjoy mahjong with peace of mind.

[0035] The tutorial function can evaluate the user's level of understanding in real time during the tutorial and customize the content according to the user's level of understanding. To evaluate the user's level of understanding, for example, quizzes or tests are used. For example, the tutorial function may present a quiz after the user completes a specific step and evaluate the user's level of understanding based on the result. The tutorial function can also evaluate the user's level of understanding based on the user's reaction time and the accuracy of the operation. For example, the tutorial function may measure the reaction time when the user performs a specific operation and evaluate the user's level of understanding based on the measured reaction time. Furthermore, the tutorial function customizes the content based on the evaluated level of understanding. For example, if the user does not understand, the tutorial function may provide additional explanations or examples. If the user understands, the tutorial function may proceed to the next step. If the user only partially understands, the tutorial function may re-explain certain points. This makes it possible to provide an optimal tutorial according to the user's level of understanding.

[0036] The tutorial function can suggest the optimal learning sequence by referring to the user's past learning history during the tutorial. To refer to the past learning history, for example, the user's learning database is used. For example, the tutorial function retrieves what the user has learned in the past from the database and suggests what to learn next based on that. It can also suggest that the user re-study content that they were weak at in the past. For example, it can encourage the user to re-study a topic that they had insufficient understanding in the past. It can also skip content that the user was strong at in the past and move on to the next step. For example, it can skip content that the user has already mastered and move on to more advanced content. This makes it possible to provide the optimal learning sequence based on the user's past learning history.

[0037] The tutorial function can teach rules and etiquette based on the user's geographical location information during the tutorial. To take geographical location information into consideration, for example, GPS technology can be used. For example, the tutorial function can obtain the user's current location using GPS and teach the mahjong rules and etiquette specific to that region. For example, if the user is in a specific region, the tutorial function can explain the mahjong rules specific to that region. Also, if the user is in a different cultural sphere, the tutorial function can teach the etiquette of that cultural sphere. For example, if the user is traveling, the tutorial function can introduce the rules specific to the region they are visiting. This allows the user to learn the rules and etiquette specific to that region.

[0038] The tutorial function can analyze the user's social media activity during the tutorial and provide related learning content. To analyze social media activity, for example, the user's posts and participating groups can be analyzed. For example, if the user posts about mahjong on social media, the tutorial function can provide a tutorial related to that content. Also, if the user is a member of a specific mahjong group, the tutorial function can teach the rules and strategies of that group. Furthermore, if the user is watching a video about mahjong, the tutorial function can provide learning content related to that video. For example, a related tutorial can be provided based on the content of the video the user watched. This makes it possible to provide optimal learning content based on the user's social media activity.

[0039] The advice function can analyze the user's past play history when providing advice and provide optimal advice. To analyze the past play history, for example, the user's play database is used. For example, the advice function can retrieve mistakes the user has made in the past from the database and provide advice to avoid making the same mistakes based on that information. It can also suggest similar strategies based on strategies that have been successful for the user in the past. Furthermore, the function can analyze the user's past play style and provide advice that matches that. For example, if the user prefers an aggressive play style, it can suggest an aggressive strategy. This makes it possible to provide optimal advice based on the user's past play history.

[0040] The advice function can update the content of advice in real time based on the user's current game situation when providing advice. To take the current game situation into consideration, for example, the user's tiles and the opponent's moves can be analyzed. For example, if the user has a specific tile, the advice function can provide advice based on that tile. Also, if the user is aiming for a specific hand, the advice function can provide advice based on that hand. Furthermore, the advice function can analyze the user's opponent's moves and provide advice based on them. For example, if the opponent is adopting a specific strategy, advice to counter that strategy can be provided. This makes it possible to provide optimal advice based on the user's current game situation.

[0041] The advice function can take into account the user's geographical location information when providing advice and suggest strategies specific to that region. To take geographical location information into account, for example, GPS technology can be used. For example, the advice function can obtain the user's current location using GPS and suggest mahjong strategies specific to that region. For example, if the user is in a specific region, the advice function can explain mahjong strategies specific to that region. Also, if the user is in a different cultural sphere, the advice function can teach strategies for that cultural sphere. For example, if the user is traveling, the advice function can introduce strategies specific to the region they are visiting. This allows the user to learn strategies specific to that region.

[0042] The advice function can analyze the user's social media activity when providing advice and provide relevant advice. To analyze social media activity, for example, the user's posts and participating groups can be analyzed. For example, if the user posts about mahjong on social media, the advice function can provide advice related to that content. Also, if the user is a member of a specific mahjong group, the advice function can teach strategies for that group. Furthermore, if the user is watching a video about mahjong, the advice function can provide advice related to that video. For example, relevant advice can be provided based on the content of the video the user has watched. This makes it possible to provide optimal advice based on the user's social media activity.

[0043] The support function can analyze the user's past communication history when providing support and provide the most appropriate support method. To analyze the past communication history, for example, the user's communication database is used. For example, the support function can retrieve communication methods that the user has had difficulty with in the past from the database and provide support that avoids the same methods based on that. It can also suggest similar methods based on communication methods that the user has had success with in the past. Furthermore, the user's past communication style can be analyzed and support that matches that can be provided. For example, if the user prefers a conversational style, conversational support can be provided. This makes it possible to provide the most appropriate support based on the user's past communication history.

[0044] The support function can update the content of support in real time based on the user's current match situation when providing support. To take the current match situation into consideration, for example, the user's tiles and the opponent's moves can be analyzed. For example, if the user has a specific tile, the support function can provide support based on that tile. Also, if the user is aiming for a specific hand, the support function can provide support based on that hand. Furthermore, the support function can analyze the user's opponent's moves and provide support based on that. For example, if the opponent is employing a specific strategy, the support function can provide support to counter that strategy. This makes it possible to provide optimal support based on the user's current match situation.

[0045] The support function can take into account the user's geographical location information when providing support and teach local manners and rules. To take geographical location information into account, for example, GPS technology can be used. For example, the support function can obtain the user's current location using GPS and teach local mahjong manners and rules. For example, if the user is in a specific area, the support function can explain local mahjong manners. Also, if the user is in a different cultural area, the support function can teach the rules of that cultural area. For example, if the user is traveling, the support function can introduce local manners for the area they are visiting. This allows the user to learn local manners and rules.

[0046] The support function can analyze a user's social media activity when providing support and provide relevant support. To analyze social media activity, for example, the user's posts and participating groups are analyzed. For example, if a user posts about mahjong on social media, the support function can provide support related to that content. Also, if the user is a member of a specific mahjong group, the support function can teach the etiquette and rules of that group. Furthermore, if the user is watching a video about mahjong, the support function can provide support related to that video. For example, relevant support can be provided based on the content of the video the user watched. This makes it possible to provide optimal support based on the user's social media activity.

[0047] The horizontal expansion function for other table games can suggest the optimal learning order when learning the rules and strategies of other table games by referring to the user's past game history. To refer to the past game history, for example, the user's game database is used. For example, the horizontal expansion function for other table games can retrieve what the user has previously learned from the database and suggest what to learn next based on that. It can also suggest that the user restudy content that the user was weak at in the past. For example, it can encourage the user to restudy topics that the user did not fully understand in the past. It can also omit content that the user was strong at in the past and move on to the next step. For example, it can skip content that the user has already mastered and move on to more advanced content. This makes it possible to provide the optimal learning order based on the user's past game history.

[0048] The function for expanding to other table games can teach regional rules and etiquette during tutorials of other table games by taking into account the user's geographic location information. For example, GPS technology can be used to consider geographic location information. For example, the function for expanding to other table games can obtain the user's current location using GPS and teach regional table game rules and etiquette. For example, if the user is in a specific region, the function can explain regional table game rules. Furthermore, if the user is in a different cultural region, the function can also teach the etiquette of that cultural region. For example, if the user is traveling, the function can introduce regional rules for the region they are visiting. This allows the user to learn regional rules and etiquette.

[0049] The event information provision function can analyze the user's past participation history when providing event information and suggest the most suitable event. To analyze the past participation history, for example, a user participation database is used. For example, the event information provision function retrieves events the user has previously attended from the database and suggests similar events based on that. It can also suggest related events based on events the user has enjoyed in the past. Furthermore, the user's past participation history is analyzed to suggest the most suitable event. For example, if a user likes events of a specific genre, events related to that genre are suggested. This makes it possible to provide the most suitable event based on the user's past participation history.

[0050] The event information provision function can suggest region-specific events by taking into account the user's geographical location information when providing event information. To take geographical location information into account, for example, GPS technology can be used. For example, the event information provision function can obtain the user's current location using GPS and suggest region-specific events. For example, if the user is in a specific region, the function can explain region-specific events. Also, if the user is in a different cultural sphere, the function can teach the user about events in that cultural sphere. For example, if the user is traveling, the function can introduce region-specific events for the region they are visiting. This makes it possible to provide region-specific event information.

[0051] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0052] The mahjong support system may further include a play style learning unit that learns the user's play style and provides individually optimized advice. For example, the play style learning unit collects data on the user's past plays and classifies the user's play style into categories such as aggressive, defensive, and balanced. Next, the play style learning unit analyzes the trends in tiles and hands selected by the user during the game and provides advice optimized for that play style in real time. Furthermore, the play style learning unit can predict what choices the user will make in specific situations and customize advice based on the prediction. This allows the user to receive advice tailored to their play style and learn mahjong more effectively.

[0053] The mahjong support system can further include a learning plan suggestion unit that analyzes the user's past playing history and proposes an optimal learning plan. For example, the learning plan suggestion unit collects data on the user's past plays and analyzes which parts the user struggled with and which hands the user excels at. Then, based on the analysis results, the system proposes an optimal learning plan for the user. For example, if the user does not understand a particular hand, the system can provide a detailed tutorial on that hand. Also, if the user wants to master a specific strategy, the system can suggest a practice mode specialized for that strategy. This allows the user to overcome their weaknesses and learn mahjong efficiently.

[0054] The mahjong support system can further include a region-adaptive tutorial unit that teaches region-specific mahjong rules and etiquette based on the user's geographical location information. For example, the region-adaptive tutorial unit obtains the user's current location using GPS and provides region-specific mahjong rules and etiquette. For example, if the user is in the Kansai region, the region-specific rules and etiquette can be explained. Also, if the user is overseas, the region-specific mahjong rules and etiquette can be taught. This allows the user to learn appropriate mahjong playing methods according to their region.

[0055] The mahjong support system may further include a social media linking unit that analyzes the user's social media activity and provides related learning content. For example, if the user posts about mahjong on social media, the social media linking unit may provide tutorials and advice related to that content. Also, if the user is a member of a specific mahjong group, the social media linking unit may teach the rules and strategies of that group. Furthermore, if the user is watching a video about mahjong, the social media linking unit may provide learning content related to that video. This makes it possible to provide optimal learning content based on the user's social media activity.

[0056] The mahjong support system can further include a communication history analysis unit that analyzes the user's past communication history and provides the optimal support method. For example, the communication history analysis unit collects data on the user's past communications and analyzes what support was effective. Next, based on the analysis results, the optimal support method for the user is proposed. For example, if the user prefers interactive support, interactive support is provided. Also, if the user is not good at a particular support method, that method is avoided. In this way, the optimal support can be provided based on the user's past communication history.

[0057] The mahjong support system can further include a region-adaptive event suggestion unit that suggests region-specific events based on the user's geographical location information. For example, the region-adaptive event suggestion unit acquires the user's current location using GPS and provides event information specific to that region. For example, if the user is in a specific region, it can explain mahjong events specific to that region. Also, if the user is in a different cultural sphere, it can also teach events in that cultural sphere. This allows the user to obtain appropriate event information according to their region.

[0058] The processing flow of the first embodiment will be briefly explained below.

[0059] Step 1: The tutorial function uses AR to provide explanations of the rules of mahjong, the types of tiles, and the different hands. When the user launches the app, AR technology is used to visually explain the basic rules of mahjong and explain the different types of tiles and the different hands. In addition, the app provides interactive features that allow users to learn by actually manipulating the tiles. For example, when the user selects a tile, detailed information about that tile is displayed. Step 2: The advice function provides real-time advice on which tiles to discard and which hand to aim for. When a user selects a tile during the game, the next tile to discard and the hand to aim for are displayed in real time. It also provides customized advice based on the user's playing style. For example, if a user prefers an aggressive playing style, it will suggest an aggressive strategy. Step 3: The support function teaches the necessary etiquette and rules when communicating with mahjong parlor staff and playing against other players. It teaches the user how to greet and behave when entering a mahjong parlor, and displays the necessary rules and etiquette in real time during a match. For example, if a user has trouble during a match, the support function will provide appropriate advice.

[0060] (Example 2) A mahjong support system according to an embodiment of the present invention provides tutorials and coaching functions using augmented reality (AR) for beginners who want to enjoy mahjong at offline mahjong parlors. This mahjong support system allows users to launch an app and learn mahjong rules, tile types, and hand explanations through AR. Then, users can receive real-time advice during the game. For example, advice is displayed on which tiles to discard and which hands to aim for. This helps to address common hurdles for beginners and supports a smooth initial experience. Furthermore, the mahjong support system is designed to allow beginners who are anxious about communicating with mahjong parlor staff or playing against other players to enjoy mahjong with confidence. For example, the system supports communication with parlor staff and teaches necessary etiquette and rules during matches against other players. This allows even beginners to enjoy mahjong with confidence. Furthermore, the mahjong support system contributes to the revitalization of the mahjong industry by collaborating with the industry to create a welcoming environment for beginners. For example, the system provides information on events and campaigns aimed at beginners, creating an environment that makes it easy for beginners to participate. This system can be expanded to other table games, becoming a powerful tool that will boost the industry beyond the scope of the application. For example, similar tutorial and coaching functions could be provided for other table games such as poker and chess to help beginners enjoy the game. This allows beginners to smoothly learn and enjoy mahjong.

[0061] The mahjong support system according to the embodiment includes a tutorial function, an advice function, and a support function. The tutorial function uses AR to provide explanations of mahjong rules, tile types, and hand combinations. For example, when a user launches the app, the tutorial function visually explains the basic rules of mahjong using AR technology. The tutorial function also provides explanations of tile types and hand combinations, making it easier for beginners to understand the basics of mahjong. For example, AR technology can be used to visually display the names of each tile and hand combinations. Furthermore, the tutorial function provides interactive functions that allow users to learn while actually manipulating tiles. For example, when a user selects a tile, detailed information about that tile is displayed. The advice function provides real-time advice on which tile to discard and which hand to aim for. For example, when a user selects a tile during a game, the advice function displays the next tile to discard and the hand to aim for in real time. The advice function can also provide customized advice based on the user's playing style. For example, if a user prefers an aggressive playing style, the advice function suggests an aggressive strategy. The support function teaches the user the manners and rules necessary for communicating with staff at a mahjong parlor and playing against other players. For example, the support function teaches the user greetings and manners when entering a mahjong parlor. The support function can also display the rules and manners necessary during a match in real time. For example, if the user has trouble during a match, the support function provides appropriate advice. As a result, the mahjong support system according to the embodiment allows beginners to smoothly learn and enjoy mahjong.

[0062] The mahjong support system has a function for horizontal expansion to other table games. The function for horizontal expansion to other table games supports other table games such as poker and chess. For example, in the case of poker, the mahjong support system can provide explanations of poker rules and hands using AR. It can also provide advice in real time during a poker game. For example, it displays advice on which card to discard next and which hand to aim for. It also provides a support function that teaches the etiquette and rules necessary during a poker game. For example, if a player is in trouble during a poker game, the support function provides appropriate advice. In the case of chess, the mahjong support system can provide chess rules and strategies using AR. For example, it visually explains basic chess piece movements and strategies. It can also provide advice in real time during a chess game. For example, it displays advice on which piece to move next and which strategy to adopt. It also provides a support function that teaches the etiquette and rules necessary during a chess game. For example, if a player is in trouble during a chess game, the support function provides appropriate advice. This makes it possible to support other table games.

[0063] The mahjong support system has an event information provision function. The event information provision function provides, for example, information on events and campaigns for beginners. For example, the mahjong support system can provide information on mahjong classes and tournaments for beginners. It can also collaborate with the mahjong industry to plan events that are easy for beginners to participate in and provide information about them. For example, it can provide information on mahjong tournaments and social gatherings for beginners. Furthermore, the mahjong support system can provide event information customized based on the user's interests. For example, if a user lives in a specific area, it can provide information on mahjong events held in that area. Also, if the user belongs to a specific mahjong club, it can provide information on events held at that club. This makes it possible to provide event information for beginners.

[0064] The tutorial function can use AR to provide explanations of mahjong rules, tile types, and hand combinations. The explanations of mahjong rules, tile types, and hand combinations include, for example, basic rules and hand combinations. For example, when a user launches the app, the tutorial function uses AR technology to visually explain the basic rules of mahjong. The tutorial function also provides explanations of tile types and hand combinations, making it easier for beginners to understand the basics of mahjong. For example, AR technology can be used to visually display the names of each tile and hand combinations. Furthermore, the tutorial function provides an interactive function that allows users to learn by actually manipulating tiles. For example, when a user selects a tile, detailed information about that tile is displayed. This makes it easier for beginners to learn the basics of mahjong.

[0065] The advice function can provide real-time advice on which tile to discard and which hand to aim for. Real-time advice includes, for example, suggestions for the next tile to discard and the hand to aim for. For example, when a user selects a tile during a game, the advice function displays the next tile to discard and the hand to aim for in real time. The advice function can also provide customized advice based on the user's playing style. For example, if the user prefers an offensive playing style, the advice function can suggest an offensive strategy. Furthermore, the advice function can analyze the user's past playing history and provide optimal advice based on that. For example, the advice function can provide advice on how to avoid making the same mistakes based on mistakes made by the user in the past. This allows beginners to make appropriate decisions during the game.

[0066] The support function can teach etiquette and rules while communicating with mahjong parlor staff and playing against other players. Examples of etiquette and rules include greetings upon entering the parlor and etiquette during a match. For example, the support function can teach the user how to greet and behave when entering a mahjong parlor. The support function can also display the rules and etiquette necessary during a match in real time. For example, if a user has difficulty during a match, the support function can provide appropriate advice. Furthermore, the support function can estimate the user's emotions and adjust the communication support method based on that information. For example, if the user is nervous, the support function can support communication with kind words. This allows beginners to enjoy mahjong with peace of mind.

[0067] The tutorial function can estimate the user's emotions and adjust the speed of the tutorial based on the estimated user emotions. To estimate the user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the tutorial function captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. Furthermore, the tutorial function adjusts the speed of the tutorial based on the estimated emotion. For example, if the user is impatient, the tutorial speed can be slowed down to make it easier to understand. On the other hand, if the user is relaxed, the tutorial speed can be kept normal. This makes it possible to provide an optimal tutorial according to the user's emotions.

[0068] The tutorial function can evaluate the user's level of understanding in real time during the tutorial and customize the content according to the user's level of understanding. To evaluate the user's level of understanding, for example, quizzes or tests are used. For example, the tutorial function may present a quiz after the user completes a specific step and evaluate the user's level of understanding based on the result. The tutorial function can also evaluate the user's level of understanding based on the user's reaction time and the accuracy of the operation. For example, the tutorial function may measure the reaction time when the user performs a specific operation and evaluate the user's level of understanding based on the measured reaction time. Furthermore, the tutorial function customizes the content based on the evaluated level of understanding. For example, if the user does not understand, the tutorial function may provide additional explanations or examples. If the user understands, the tutorial function may proceed to the next step. If the user only partially understands, the tutorial function may re-explain certain points. This makes it possible to provide an optimal tutorial according to the user's level of understanding.

[0069] The tutorial function can suggest the optimal learning sequence by referring to the user's past learning history during the tutorial. To refer to the past learning history, for example, the user's learning database is used. For example, the tutorial function retrieves what the user has learned in the past from the database and suggests what to learn next based on that. It can also suggest that the user re-study content that they were weak at in the past. For example, it can encourage the user to re-study a topic that they had insufficient understanding in the past. It can also skip content that the user was strong at in the past and move on to the next step. For example, it can skip content that the user has already mastered and move on to more advanced content. This makes it possible to provide the optimal learning sequence based on the user's past learning history.

[0070] The tutorial function can estimate the user's emotions and change the tutorial content based on the estimated user emotions. To estimate the user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the tutorial function captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. Furthermore, the tutorial function changes the tutorial content based on the estimated emotions. For example, if the user is feeling anxious, it can focus on explaining basic content. If the user is confident, it can add practical content. Furthermore, if the user shows interest, it can provide detailed information. This makes it possible to provide optimal tutorial content according to the user's emotions.

[0071] The tutorial function can teach rules and etiquette based on the user's geographical location information during the tutorial. To take geographical location information into consideration, for example, GPS technology can be used. For example, the tutorial function can obtain the user's current location using GPS and teach the mahjong rules and etiquette specific to that region. For example, if the user is in a specific region, the tutorial function can explain the mahjong rules specific to that region. Also, if the user is in a different cultural sphere, the tutorial function can teach the etiquette of that cultural sphere. For example, if the user is traveling, the tutorial function can introduce the rules specific to the region they are visiting. This allows the user to learn the rules and etiquette specific to that region.

[0072] The tutorial function can analyze the user's social media activity during the tutorial and provide related learning content. To analyze social media activity, for example, the user's posts and participating groups can be analyzed. For example, if the user posts about mahjong on social media, the tutorial function can provide a tutorial related to that content. Also, if the user is a member of a specific mahjong group, the tutorial function can teach the rules and strategies of that group. Furthermore, if the user is watching a video about mahjong, the tutorial function can provide learning content related to that video. For example, a related tutorial can be provided based on the content of the video the user watched. This makes it possible to provide optimal learning content based on the user's social media activity.

[0073] The advice function can estimate the user's emotions and adjust the way the advice is expressed based on the estimated user's emotions. To estimate the user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the advice function captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. Furthermore, the advice function adjusts the way the advice is expressed based on the estimated emotion. For example, if the user is nervous, the advice function provides gentle advice. If the user is relaxed, the advice function provides detailed advice. If the user is impatient, the advice function provides concise and quick advice. This makes it possible to provide optimal advice according to the user's emotions.

[0074] The advice function can analyze the user's past play history when providing advice and provide optimal advice. To analyze the past play history, for example, the user's play database is used. For example, the advice function can retrieve mistakes the user has made in the past from the database and provide advice to avoid making the same mistakes based on that information. It can also suggest similar strategies based on strategies that have been successful for the user in the past. Furthermore, the function can analyze the user's past play style and provide advice that matches that. For example, if the user prefers an aggressive play style, it can suggest an aggressive strategy. This makes it possible to provide optimal advice based on the user's past play history.

[0075] The advice function can update the content of advice in real time based on the user's current game situation when providing advice. To take the current game situation into consideration, for example, the user's tiles and the opponent's moves can be analyzed. For example, if the user has a specific tile, the advice function can provide advice based on that tile. Also, if the user is aiming for a specific hand, the advice function can provide advice based on that hand. Furthermore, the advice function can analyze the user's opponent's moves and provide advice based on them. For example, if the opponent is adopting a specific strategy, advice to counter that strategy can be provided. This makes it possible to provide optimal advice based on the user's current game situation.

[0076] The advice function can estimate the user's emotions and determine the priority of advice based on the estimated user emotions. To estimate the user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the advice function captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. Furthermore, the advice function determines the priority of advice based on the estimated emotions. For example, if the user is anxious, the most important advice is provided first. If the user is relaxed, detailed advice is provided sequentially. If the user is anxious, advice that gives a sense of security is provided first. This makes it possible to provide the optimal priority of advice according to the user's emotions.

[0077] The advice function can take into account the user's geographical location information when providing advice and suggest strategies specific to that region. To take geographical location information into account, for example, GPS technology can be used. For example, the advice function can obtain the user's current location using GPS and suggest mahjong strategies specific to that region. For example, if the user is in a specific region, the advice function can explain mahjong strategies specific to that region. Also, if the user is in a different cultural sphere, the advice function can teach strategies for that cultural sphere. For example, if the user is traveling, the advice function can introduce strategies specific to the region they are visiting. This allows the user to learn strategies specific to that region.

[0078] The advice function can analyze the user's social media activity when providing advice and provide relevant advice. To analyze social media activity, for example, the user's posts and participating groups can be analyzed. For example, if the user posts about mahjong on social media, the advice function can provide advice related to that content. Also, if the user is a member of a specific mahjong group, the advice function can teach strategies for that group. Furthermore, if the user is watching a video about mahjong, the advice function can provide advice related to that video. For example, relevant advice can be provided based on the content of the video the user has watched. This makes it possible to provide optimal advice based on the user's social media activity.

[0079] The support function can estimate the user's emotions and adjust the communication support method based on the estimated user emotions. To estimate the user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the support function captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, it can analyze the tone and speed of the voice and calculate an emotion score. Furthermore, the support function adjusts the communication support method based on the estimated emotions. For example, if the user is nervous, it can support communication with gentle words. If the user is relaxed, it can provide detailed communication support. If the user is impatient, it can provide concise and quick communication support. This makes it possible to provide optimal communication support according to the user's emotions.

[0080] The support function can analyze the user's past communication history when providing support and provide the most appropriate support method. To analyze the past communication history, for example, the user's communication database is used. For example, the support function can retrieve communication methods that the user has had difficulty with in the past from the database and provide support that avoids the same methods based on that. It can also suggest similar methods based on communication methods that the user has had success with in the past. Furthermore, the user's past communication style can be analyzed and support that matches that can be provided. For example, if the user prefers a conversational style, conversational support can be provided. This makes it possible to provide the most appropriate support based on the user's past communication history.

[0081] The support function can update the content of support in real time based on the user's current match situation when providing support. To take the current match situation into consideration, for example, the user's tiles and the opponent's moves can be analyzed. For example, if the user has a specific tile, the support function can provide support based on that tile. Also, if the user is aiming for a specific hand, the support function can provide support based on that hand. Furthermore, the support function can analyze the user's opponent's moves and provide support based on that. For example, if the opponent is employing a specific strategy, the support function can provide support to counter that strategy. This makes it possible to provide optimal support based on the user's current match situation.

[0082] The support function can estimate the user's emotions and determine the priority of support based on the estimated user emotions. To estimate the user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the support function captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. Furthermore, the support function determines the priority of support based on the estimated emotions. For example, if the user is anxious, the most important support is provided first. If the user is relaxed, detailed support is provided sequentially. If the user is anxious, support that gives a sense of security is provided first. This makes it possible to provide optimal support priorities according to the user's emotions.

[0083] The support function can take into account the user's geographical location information when providing support and teach local manners and rules. To take geographical location information into account, for example, GPS technology can be used. For example, the support function can obtain the user's current location using GPS and teach local mahjong manners and rules. For example, if the user is in a specific area, the support function can explain local mahjong manners. Also, if the user is in a different cultural area, the support function can teach the rules of that cultural area. For example, if the user is traveling, the support function can introduce local manners for the area they are visiting. This allows the user to learn local manners and rules.

[0084] The support function can analyze a user's social media activity when providing support and provide relevant support. To analyze social media activity, for example, the user's posts and participating groups are analyzed. For example, if a user posts about mahjong on social media, the support function can provide support related to that content. Also, if the user is a member of a specific mahjong group, the support function can teach the etiquette and rules of that group. Furthermore, if the user is watching a video about mahjong, the support function can provide support related to that video. For example, relevant support can be provided based on the content of the video the user watched. This makes it possible to provide optimal support based on the user's social media activity.

[0085] The function for expanding to other table games can estimate a user's emotions and adjust the tutorial content for other table games based on the estimated user emotions. To estimate a user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the function for expanding to other table games can capture a user's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. It can also record the user's voice and estimate their emotions using voice analysis technology. For example, it can analyze the tone and speed of the voice to calculate an emotion score. Furthermore, the function for expanding to other table games can adjust the tutorial content based on the estimated emotions. For example, if the user feels anxious, it can focus on explaining basic content. If the user feels confident, it can add more advanced content. Furthermore, if the user shows interest, it can provide more detailed information. This makes it possible to provide optimal tutorial content tailored to the user's emotions.

[0086] The horizontal expansion function for other table games can suggest the optimal learning order when learning the rules and strategies of other table games by referring to the user's past game history. To refer to the past game history, for example, the user's game database is used. For example, the horizontal expansion function for other table games can retrieve what the user has previously learned from the database and suggest what to learn next based on that. It can also suggest that the user restudy content that the user was weak at in the past. For example, it can encourage the user to restudy topics that the user did not fully understand in the past. It can also omit content that the user was strong at in the past and move on to the next step. For example, it can skip content that the user has already mastered and move on to more advanced content. This makes it possible to provide the optimal learning order based on the user's past game history.

[0087] The function for expanding to other table games can estimate a user's emotions and change the advice content for other table games based on the estimated user emotions. To estimate a user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the function for expanding to other table games can capture a user's facial expressions with a camera and estimate the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, the tone and speed of the voice can be analyzed to calculate an emotion score. Furthermore, the function for expanding to other table games can change the advice content based on the estimated emotion. For example, if the user feels anxious, basic advice can be provided. If the user feels confident, more practical advice can be added. Furthermore, if the user shows interest, detailed advice can be provided. This makes it possible to provide optimal advice content according to the user's emotions.

[0088] The function for expanding to other table games can teach regional rules and etiquette during tutorials of other table games by taking into account the user's geographic location information. For example, GPS technology can be used to consider geographic location information. For example, the function for expanding to other table games can obtain the user's current location using GPS and teach regional table game rules and etiquette. For example, if the user is in a specific region, the function can explain regional table game rules. Furthermore, if the user is in a different cultural region, the function can also teach the etiquette of that cultural region. For example, if the user is traveling, the function can introduce regional rules for the region they are visiting. This allows the user to learn regional rules and etiquette.

[0089] The event information provision function can estimate a user's emotions and adjust the display method of event information based on the estimated user emotions. To estimate a user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the event information provision function captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, it can analyze the tone and speed of the voice and calculate an emotion score. Furthermore, the event information provision function adjusts the display method of event information based on the estimated emotion. For example, if the user is excited, a visually stimulating display method is provided. Furthermore, if the user is relaxed, a calming display method is provided. Furthermore, if the user is anxious, a display method that gives a sense of security is provided. This makes it possible to provide an optimal display method of event information according to the user's emotions.

[0090] The event information provision function can analyze the user's past participation history when providing event information and suggest the most suitable event. To analyze the past participation history, for example, a user participation database is used. For example, the event information provision function retrieves events the user has previously attended from the database and suggests similar events based on that. It can also suggest related events based on events the user has enjoyed in the past. Furthermore, the user's past participation history is analyzed to suggest the most suitable event. For example, if a user likes events of a specific genre, events related to that genre are suggested. This makes it possible to provide the most suitable event based on the user's past participation history.

[0091] The event information provision function can estimate a user's emotions and determine the priority of event information based on the estimated user emotions. To estimate a user's emotions, for example, facial expression recognition technology or voice analysis technology is used. For example, the event information provision function captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. It can also record the user's voice and estimate the emotion using voice analysis technology. For example, it can analyze the tone and speed of the voice and calculate an emotion score. Furthermore, the event information provision function determines the priority of event information based on the estimated emotions. For example, if the user is excited, the most interesting event information is provided first. Furthermore, if the user is relaxed, detailed event information is provided sequentially. Furthermore, if the user is anxious, event information that gives a sense of security is provided first. This allows the optimal priority of event information to be provided according to the user's emotions.

[0092] The event information provision function can suggest region-specific events by taking into account the user's geographical location information when providing event information. To take geographical location information into account, for example, GPS technology can be used. For example, the event information provision function can obtain the user's current location using GPS and suggest region-specific events. For example, if the user is in a specific region, the function can explain region-specific events. Also, if the user is in a different cultural sphere, the function can teach the user about events in that cultural sphere. For example, if the user is traveling, the function can introduce region-specific events for the region they are visiting. This makes it possible to provide region-specific event information. === Hard Collateral 1-1 === Each of the multiple elements, including the tutorial function, advice function, support function, and event information provision function, described above, is implemented, for example, by at least one of the smart device 14 and the data processing device 12. For example, the tutorial function is implemented by the control unit 46A of the smart device 14 and uses AR technology to visually provide explanations of the basic rules of mahjong, tile types, and hand combinations. The advice function is implemented, for example, by the specific processing unit 290 of the data processing device 12 and provides real-time advice on which tiles to discard and which hand combinations to aim for. The support function is implemented, for example, by the control unit 46A of the smart device 14 and teaches the etiquette and rules necessary for communicating with mahjong parlor staff and playing against other players. The event information provision function is implemented, for example, by the specific processing unit 290 of the data processing device 12 and provides information on events and campaigns aimed at beginners. === Hard Collateral 1-2 === Each of the multiple elements, including the tutorial function, advice function, support function, and event information provision function, described above, is implemented, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the tutorial function is implemented by the control unit 46A of the smart glasses 214 and uses AR technology to visually provide explanations of the basic rules of mahjong, tile types, and hand combinations. The advice function is implemented, for example, by the specific processing unit 290 of the data processing device 12 and provides real-time advice on which tiles to discard and which hand combinations to aim for. The support function is implemented, for example, by the control unit 46A of the smart glasses 214 and teaches the etiquette and rules necessary for communicating with mahjong parlor staff and playing against other players. The event information provision function is implemented, for example, by the specific processing unit 290 of the data processing device 12 and provides information on events and campaigns aimed at beginners. === Hard Collateral 1-3 === Each of the multiple elements, including the tutorial function, advice function, support function, and event information provision function, described above, is implemented, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the tutorial function is implemented by the control unit 46A of the headset terminal 314 and uses AR technology to visually provide explanations of the basic rules of mahjong, tile types, and hand combinations. The advice function is implemented, for example, by the specific processing unit 290 of the data processing device 12 and provides real-time advice on which tiles to discard and which hand combinations to aim for. The support function is implemented, for example, by the control unit 46A of the headset terminal 314 and teaches the etiquette and rules necessary for communicating with mahjong parlor staff and playing against other players. The event information provision function is implemented, for example, by the specific processing unit 290 of the data processing device 12 and provides information on events and campaigns aimed at beginners. === Hard Collateral 1-4 === Each of the multiple elements, including the tutorial function, advice function, support function, and event information provision function, described above, is implemented, for example, by at least one of the robot 414 and the data processing device 12. For example, the tutorial function is implemented by the control unit 46A of the robot 414 and uses AR technology to visually provide explanations of the basic rules of mahjong, tile types, and hand combinations. The advice function is implemented, for example, by the specific processing unit 290 of the data processing device 12 and provides real-time advice on which tiles to discard and which hand combinations to aim for. The support function is implemented, for example, by the control unit 46A of the robot 414 and teaches the etiquette and rules necessary for communicating with mahjong parlor staff and playing against other players. The event information provision function is implemented, for example, by the specific processing unit 290 of the data processing device 12 and provides information on events and campaigns aimed at beginners.

[0093] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0094] The mahjong support system may further include a play style learning unit that learns the user's play style and provides individually optimized advice. For example, the play style learning unit collects data on the user's past plays and classifies the user's play style into categories such as aggressive, defensive, and balanced. Next, the play style learning unit analyzes the trends in tiles and hands selected by the user during the game and provides advice optimized for that play style in real time. Furthermore, the play style learning unit can predict what choices the user will make in specific situations and customize advice based on the prediction. This allows the user to receive advice tailored to their play style and learn mahjong more effectively.

[0095] The mahjong support system may further include an emotion-adaptive advice unit that estimates the user's emotions and adjusts the content of advice based on the estimated emotions. For example, the emotion-adaptive advice unit analyzes the user's facial expressions and voice to estimate emotions such as tension, relaxation, and excitement. Next, the tone and content of advice are adjusted based on the estimated emotions. For example, if the user is nervous, basic advice may be provided in a gentle tone, and if the user is relaxed, detailed strategy advice may be provided. Also, if the user is excited, quick and concise advice may be provided. This makes it possible to provide optimal advice according to the user's emotions.

[0096] The mahjong support system can further include a learning plan suggestion unit that analyzes the user's past playing history and proposes an optimal learning plan. For example, the learning plan suggestion unit collects data on the user's past plays and analyzes which parts the user struggled with and which hands the user excels at. Then, based on the analysis results, the system proposes an optimal learning plan for the user. For example, if the user does not understand a particular hand, the system can provide a detailed tutorial on that hand. Also, if the user wants to master a specific strategy, the system can suggest a practice mode specialized for that strategy. This allows the user to overcome their weaknesses and learn mahjong efficiently.

[0097] The mahjong support system can further include a region-adaptive tutorial unit that teaches region-specific mahjong rules and etiquette based on the user's geographical location information. For example, the region-adaptive tutorial unit obtains the user's current location using GPS and provides region-specific mahjong rules and etiquette. For example, if the user is in the Kansai region, the region-specific rules and etiquette can be explained. Also, if the user is overseas, the region-specific mahjong rules and etiquette can be taught. This allows the user to learn appropriate mahjong playing methods according to their region.

[0098] The mahjong support system may further include a social media linking unit that analyzes the user's social media activity and provides related learning content. For example, if the user posts about mahjong on social media, the social media linking unit may provide tutorials and advice related to that content. Also, if the user is a member of a specific mahjong group, the social media linking unit may teach the rules and strategies of that group. Furthermore, if the user is watching a video about mahjong, the social media linking unit may provide learning content related to that video. This makes it possible to provide optimal learning content based on the user's social media activity.

[0099] The mahjong support system may further include an emotion-adaptive tutorial unit that estimates the user's emotions and adjusts the tutorial progression speed based on the estimated emotions. For example, the emotion-adaptive tutorial unit analyzes the user's facial expressions and voice to estimate emotions such as impatience, relaxation, and excitement. Next, the tutorial progression speed is adjusted based on the estimated emotions. For example, if the user is impatient, the tutorial progression speed is slowed down to make it easier to understand. On the other hand, if the user is relaxed, the tutorial progresses at a normal speed. This makes it possible to provide an optimal tutorial according to the user's emotions.

[0100] The mahjong support system can further include a communication history analysis unit that analyzes the user's past communication history and provides the optimal support method. For example, the communication history analysis unit collects data on the user's past communications and analyzes what support was effective. Next, based on the analysis results, the optimal support method for the user is proposed. For example, if the user prefers interactive support, interactive support is provided. Also, if the user is not good at a particular support method, that method is avoided. In this way, the optimal support can be provided based on the user's past communication history.

[0101] The mahjong support system may further include an emotion-adaptive event display unit that estimates the user's emotion and adjusts the display method of the event information based on the estimated emotion. For example, the emotion-adaptive event display unit analyzes the user's facial expressions and voice to estimate emotions such as excitement, relaxation, and anxiety. Next, the display method of the event information is adjusted based on the estimated emotion. For example, if the user is excited, a visually stimulating display method is provided, and if the user is relaxed, a calm display method is provided. Also, if the user is feeling anxious, a display method that gives a sense of security can be provided. This makes it possible to provide an optimal display method of event information according to the user's emotion.

[0102] The mahjong support system can further include a region-adaptive event suggestion unit that suggests region-specific events based on the user's geographical location information. For example, the region-adaptive event suggestion unit acquires the user's current location using GPS and provides event information specific to that region. For example, if the user is in a specific region, it can explain mahjong events specific to that region. Also, if the user is in a different cultural sphere, it can also teach events in that cultural sphere. This allows the user to obtain appropriate event information according to their region.

[0103] The mahjong support system may further include an emotion-prioritized advice unit that estimates the user's emotions and determines the priority of advice based on the estimated emotions. For example, the emotion-prioritized advice unit analyzes the user's facial expressions and voice to estimate emotions such as impatience, relaxation, and anxiety. Next, the priority of advice is determined based on the estimated emotions. For example, if the user is impatient, the most important advice may be provided first, and if the user is relaxed, more detailed advice may be provided sequentially. Also, if the user is feeling anxious, advice that gives a sense of security may be provided first. This makes it possible to provide the optimal priority of advice according to the user's emotions.

[0104] The processing flow of the second embodiment will be briefly explained below.

[0105] Step 1: The tutorial function uses AR to provide explanations of the rules of mahjong, the types of tiles, and the different hands. When the user launches the app, AR technology is used to visually explain the basic rules of mahjong and explain the different types of tiles and the different hands. In addition, the app provides interactive features that allow users to learn by actually manipulating the tiles. For example, when the user selects a tile, detailed information about that tile is displayed. Step 2: The advice function provides real-time advice on which tiles to discard and which hand to aim for. When a user selects a tile during the game, the next tile to discard and the hand to aim for are displayed in real time. It also provides customized advice based on the user's playing style. For example, if a user prefers an aggressive playing style, it will suggest an aggressive strategy. Step 3: The support function teaches the necessary etiquette and rules when communicating with mahjong parlor staff and playing against other players. It teaches the user how to greet and behave when entering a mahjong parlor, and displays the necessary rules and etiquette in real time during a match. For example, if a user has trouble during a match, the support function will provide appropriate advice.

[0106] 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.

[0107] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). 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 (e.g., still image data or video data). 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 one or more data formats of voice data, text data, image data, etc. 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 may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0108] 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.

[0109] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0110] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0111] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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).

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0120] 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. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0121] 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.

[0122] 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.

[0123] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0124] 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.

[0125] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0126] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0127] 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.

[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 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.

[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 (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).

[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] 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.

[0134] 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.

[0135] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0136] 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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0137] 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.

[0138] 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.

[0139] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0140] 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.

[0141] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0142] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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).

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0153] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. 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 the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0154] 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.

[0155] 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.

[0156] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0157] 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.

[0158] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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).

[0163] 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.

[0164] 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."

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] The hardware resource that executes the specific processing 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 processing may be a single processor.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] [Explanation of symbols]

[0178] 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. Tutorial function using AR, an advice function that provides real-time advice based on what has been learned through the tutorial function; and a support function that provides communication support based on the information obtained by the advice function. A system characterized by:

2. Has the ability to be expanded to other table games 2. The system of claim 1.

3. Equipped with event information provision function 2. The system of claim 1.

4. The tutorial function Using AR to provide explanations of mahjong rules, tile types, and hand combinations 2. The system of claim 1.

5. The advice function: Providing real-time advice on which tiles to discard and which hand to aim for 2. The system of claim 1.

6. The support function is Communicating with staff at mahjong parlors and teaching etiquette and rules while playing against other players 2. The system of claim 1.

7. The tutorial function Estimate the user's emotions and adjust the tutorial progress speed based on the estimated user emotions.

2. The system of claim 1.

8. The tutorial function Assess user comprehension in real time during the tutorial and customize the content accordingly 2. The system of claim 1.

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