System

Abstract

An object of a system according to an embodiment is to perform a contract procedure while naturally conversing with a character generated by a user.SOLUTION: A system includes a character generation part, a conversation part, and a contract procedure part. The character generation unit allows the user to generate a character using the generation AI. The conversation unit allows the character generated by the character generation unit and the user to have a conversation in a natural language. The contract procedure unit performs a contract procedure of the smartphone through the character.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technologies have the drawback of being inconvenient, as they do not allow users to carry out contract procedures while having natural conversations with characters they create.

[0005] The system according to the embodiment aims to allow users to carry out contract procedures while having natural conversations with characters they have created. [Means for solving the problem]

[0006] The system according to the embodiment includes a character generation unit, a conversation unit, and a contract procedure unit. The character generation unit allows a user to generate a character using a generation AI. The conversation unit allows a user to converse in natural language with the character generated by the character generation unit. The contract procedure unit performs smartphone contract procedures through the character. [Effects of the Invention]

[0007] The system according to the embodiment allows a user to carry out contract procedures while having natural conversations with a character created by the user. [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) The online shopping system according to the embodiment of the present invention is a system in which a user can converse with a character that the user has created and can then use the character to purchase a smartphone. This allows the user to complete the smartphone contract procedure while conversing with the character that the user has created.

[0029] An online shopping system according to an embodiment includes a character generation unit, a conversation unit, and a contract procedure unit. The character generation unit allows a user to generate a character using a generation AI. For example, if a user inputs a prompt such as "I want to create a cheerful and energetic character" into the generation AI, the generation AI generates a character based on the prompt. The character generation unit can also customize the character's appearance and personality according to the user's preferences. For example, the generation AI can generate the character's appearance and personality using deep learning technology. The conversation unit allows the user to converse in natural language with the character generated by the character generation unit. For example, if a user asks, "What products are popular today?", the generation AI generates an appropriate answer to the question and conveys it to the user through the character. The conversation unit can also conduct real-time conversations using chatbot technology. For example, the generation AI can understand the user's question using voice recognition technology and generate an appropriate answer. The contract procedure unit handles smartphone contract procedures through the character. For example, if a user tells the character, "I want to sign up for a new smartphone contract," the generation AI proceeds with the contract procedures based on the user's request. The contract procedure unit also guides the user through the process of selecting the smartphone model and plan they desire and entering the necessary information. For example, the generation AI automatically generates a contract based on the user's input and asks the user for confirmation. This allows the online shop system according to the embodiment to complete the smartphone contract procedure while conversing with a character the user has created.

[0030] The character generation unit can suggest the optimal character based on the user's past purchase history and browsing history. For example, the character generation unit analyzes the user's past purchase history, and the generation AI suggests the optimal character based on that data. For example, the character generation unit generates a character that suits the user's preferences based on trends in past purchased products and services. The character generation unit also suggests the optimal character based on the user's browsing history. For example, it analyzes the themes of websites and content frequently viewed by the user and customizes the character's appearance and personality based on that. The character generation unit also integrates the purchase history and browsing history, and the generation AI suggests the character that best suits the user's preferences. For example, it finds commonalities between past purchased products and viewed content and generates a character that reflects that. This makes it possible to suggest the optimal character based on the user's past purchase history and browsing history.

[0031] The character generation unit can analyze the user's voice tone and facial expression and adjust the character's personality and appearance based on that. For example, the character generation unit analyzes the user's voice tone, and the generation AI adjusts the character's personality based on that data. For example, for a user with a bright voice tone, it generates a character with a lively and cheerful personality. The character generation unit also analyzes the user's facial expression, and the generation AI adjusts the character's appearance based on that data. For example, for a user who smiles a lot, it generates a character that is characterized by smiling. The character generation unit also analyzes the voice tone and facial expression together, and the generation AI generates a character that best suits the user's personality and preferences. For example, for a user with a calm voice tone and smile, it generates a kind and friendly character. This makes it possible to adjust the character's personality and appearance based on the user's voice tone and facial expression.

[0032] The character generation unit can add a function that refers to characters from movies or games that the user likes. For example, the character generation unit inputs characters from movies or games that the user likes, and the generation AI uses that input as reference to generate a new character. For example, it generates a character that incorporates the characteristics of a character from a movie that the user likes. The character generation unit also references a database of movie or game characters to generate a character that suits the user's preferences. For example, it generates a new character based on the appearance and personality of a character that the user likes. The character generation unit also inputs an image or name of a character that the user likes, and the generation AI generates a new character based on that. For example, it generates an original character that incorporates the characteristics of a character that the user likes. This allows for the addition of a function that refers to characters from movies or games that the user likes.

[0033] The character generation unit may incorporate a function that allows multiple users to collaboratively generate and share characters. The character generation unit, for example, provides an interface for multiple users to collaboratively generate characters. For example, each user customizes a part of the character and collaboratively completes the final character. The character generation unit also incorporates a function that allows multiple users to share the generated characters. For example, the generated characters can be shared with friends and family for collaborative use. The character generation unit also provides a function that allows multiple users to collaboratively generate characters and share the characters in an online community. For example, the generated characters can be made public within the community and interacted with other users. This allows multiple users to collaboratively generate and share characters.

[0034] The conversation unit allows the generation AI to learn the user's interests and concerns based on the content of the conversation and reflect them in future conversations. For example, the conversation unit analyzes the content of the conversation and the generation AI learns the user's interests and concerns. For example, it records the topics that the user frequently talks about and brings up those topics in future conversations. The conversation unit also allows the generation AI to learn the user's interests and concerns based on the user's conversation history and reflect them in future conversations. For example, it provides more detailed information on the user's favorite topics and questions. The conversation unit also analyzes the content of the conversation in real time and the generation AI instantly learns the user's interests and concerns. For example, if the user expresses a new interest, it reflects that information in the next conversation. In this way, the user's interests and concerns can be learned and reflected in future conversations.

[0035] The conversation unit can analyze the tone and speed of the user's voice during conversation and react accordingly. The conversation unit, for example, analyzes the tone of the user's voice and causes the character to react accordingly. For example, if the user is excited, the character also responds in an excited tone. The conversation unit also analyzes the speed of the user's voice and causes the character to react accordingly. For example, if the user is in a hurry, the character also responds quickly. The conversation unit also analyzes the tone and speed of the voice together and causes the character to react according to the user's emotional state. For example, if the user is calm, the character also responds in a calm tone. This makes it possible to show a reaction according to the tone and speed of the user's voice.

[0036] The conversation unit can add a community function that allows users to interact with other users through conversations with characters. The conversation unit provides a community function that allows users to interact with other users through conversations with characters, for example. For example, users with common interests converse with each other through characters. The conversation unit also adds a function that allows characters to promote interaction with other users. For example, characters suggest conversations with other users to users. The conversation unit also provides a function that allows users to participate in a community through conversations with characters. For example, characters introduce community events and discussions to users. This allows users to interact with other users through conversations with characters.

[0037] The conversation unit can introduce a function that automatically translates the content of a conversation and allows users who speak different languages ​​to communicate with each other through a character. The conversation unit, for example, provides a function that automatically translates the content of a conversation and allows users who speak different languages ​​to communicate with each other through a character. For example, an English-speaking user and a Japanese-speaking user converse through a character. The conversation unit also uses an automatic translation function to support conversations between users who speak different languages ​​with a character. For example, the character translates the content of a conversation in real time and conveys it to the user. The conversation unit also introduces a function that allows users who speak different languages ​​to communicate with each other through a character. For example, the character provides multilingual conversations to promote interaction between users. This allows users who speak different languages ​​to communicate with each other through a character.

[0038] During the contract procedure, the generation AI can refer to the user's past contract history and propose the optimal plan. For example, the contract procedure unit analyzes the user's past contract history and the generation AI proposes the optimal plan. For example, the generation AI proposes the optimal smartphone plan for the user based on past contract details and usage status. During the contract procedure, the generation AI can refer to the user's past contract history and automatically select the optimal plan. For example, the generation AI can automatically select the plan that is most suitable for the user based on past data. The contract procedure unit can also suggest the optimal plan based on the user's past contract history and allow the user to select that plan. For example, the generation AI can present the optimal plan to the user by referring to past contract details. This makes it possible to suggest the optimal plan by referring to the user's past contract history.

[0039] The contract procedure unit can analyze the user's tone of voice and facial expression during the contract procedure and provide support accordingly. The contract procedure unit, for example, analyzes the user's tone of voice, and a character provides support accordingly. For example, if the user speaks in an anxious tone, the character will say reassuring words. The contract procedure unit also analyzes the user's facial expression, and the character provides support accordingly. For example, if the user looks troubled, the character will provide specific advice. The contract procedure unit also analyzes the tone of voice and facial expression together, and the character provides support according to the user's emotional state. For example, if the user is excited, the character will respond calmly. This makes it possible to provide support according to the user's tone of voice and facial expression.

[0040] The contract procedure unit can add a function in which a character provides the user with a visual guide of the contract contents during the contract procedure. For example, the contract procedure unit may provide the user with a visual guide of the contract contents during the contract procedure. For example, the contract contents may be visually explained using diagrams and icons. The contract procedure unit may also provide a visual guide of each step of the contract procedure, making it easier for the user to understand the procedure. For example, the progress of the procedure may be displayed using graphs and charts. The contract procedure unit may also provide a visual guide of the contract contents, allowing the user to proceed smoothly with the procedure. For example, the important points of the contract contents may be highlighted. This allows the character to provide the user with a visual guide of the contract contents during the contract procedure.

[0041] The contract procedure section can introduce a function that allows the user to refer to reviews and ratings from other users during the contract procedure. The contract procedure section, for example, provides a function that allows the user to refer to reviews and ratings from other users during the contract procedure. For example, it displays reviews of the smartphone that the user is about to sign up for. The contract procedure section also provides information that is useful during the contract procedure based on the ratings of other users. For example, it displays ratings from users who have signed up for the same plan. The contract procedure section also displays reviews and ratings from other users in real time during the contract procedure so that the user can refer to them. For example, it automatically updates and displays the latest reviews and ratings. This allows the user to refer to reviews and ratings from other users during the contract procedure.

[0042] In the contract procedure section, when the contract details are confirmed, the generation AI can compare them with the user's previous contract details and highlight any changes. For example, when the contract details are confirmed, the generation AI can compare them with the user's previous contract details and highlight any changes. For example, the differences between the previous contract details and the current contract details are displayed in different colors. In addition, in the contract procedure section, the generation AI automatically detects changes based on the user's previous contract details and notifies the user. For example, changes to the fee plan or service details are highlighted. In addition, when the contract details are confirmed, the generation AI can compare them with the previous contract details and highlight any important changes. For example, changes to the contract period or benefits are prominently displayed. This allows the contract details to be compared with the previous contract details and changes to be highlighted when confirming the contract details.

[0043] The contract procedure unit can analyze the user's tone of voice and facial expression when confirming the contract contents, and provide a confirmation method that corresponds to the tone of voice and facial expression. The contract procedure unit, for example, analyzes the user's tone of voice, and a character provides a confirmation method that corresponds to the tone of voice. For example, if the user speaks in an anxious tone, the character provides a detailed explanation. The contract procedure unit can also analyze the user's facial expression, and the character provides a confirmation method that corresponds to the facial expression. For example, if the user looks troubled, the character provides specific advice. The contract procedure unit can also analyze the tone of voice and facial expression together, and the character provides a confirmation method that corresponds to the user's emotional state. For example, if the user is excited, the character responds calmly. This makes it possible to provide a confirmation method that corresponds to the user's tone of voice and facial expression when confirming the contract contents.

[0044] The contract procedure unit can add a function in which a character provides a visual guide of the contract contents to the user when the contract contents are being confirmed. For example, the contract procedure unit may provide a visual guide of the contract contents to the user when the contract contents are being confirmed. For example, the contract contents may be visually explained using diagrams and icons. The contract procedure unit may also provide a visual guide of the contract contents to the user, making it easier for the user to understand the contents. For example, the important points of the contract contents may be highlighted. The contract procedure unit may also provide a visual guide of the contract contents to enable the user to smoothly understand the contents. For example, changes to the contract contents may be displayed in different colors. This allows the character to provide a visual guide of the contract contents to the user when the contract contents are being confirmed.

[0045] The contract procedure section can introduce a function that allows the user to refer to reviews and ratings from other users when confirming the contract details. The contract procedure section, for example, provides a function that allows the user to refer to reviews and ratings from other users when confirming the contract details. For example, it displays reviews of the smartphone that the user is about to sign up for. The contract procedure section also provides information that is useful when confirming the contract details based on the ratings of other users. For example, it displays ratings from users who have signed up for the same plan. The contract procedure section also displays reviews and ratings from other users in real time when confirming the contract details, allowing the user to refer to them. For example, it automatically updates and displays the latest reviews and ratings. This allows the user to refer to reviews and ratings from other users when confirming the contract details.

[0046] The contract procedure unit allows the generation AI to refer to the user's past support history and provide the most appropriate support when providing post-contract support. The contract procedure unit, for example, analyzes the user's past support history and the generation AI provides the most appropriate support. For example, the unit provides the most appropriate support to the user based on past inquiries and solutions. Furthermore, the contract procedure unit allows the generation AI to refer to the user's past support history and automatically select the most appropriate support when providing post-contract support. For example, the unit automatically selects the support that is most appropriate for the user based on past data. Furthermore, the contract procedure unit allows the generation AI to provide the most appropriate support based on the user's past support history and enable the user to receive that support. For example, the unit refers to the content of past support and presents the most appropriate support to the user. This allows the generation AI to refer to the user's past support history when providing post-contract support and provide the most appropriate support.

[0047] The contract procedure unit can analyze the user's tone of voice and facial expression during post-contract support and provide support accordingly. The contract procedure unit, for example, analyzes the user's tone of voice, and a character provides support accordingly. For example, if the user speaks in an anxious tone, the character will say reassuring words. The contract procedure unit also analyzes the user's facial expression, and the character provides support accordingly. For example, if the user looks troubled, the character will provide specific advice. The contract procedure unit also analyzes the voice tone and facial expression together, and the character provides support according to the user's emotional state. For example, if the user is excited, the character will respond calmly. This makes it possible to provide support according to the user's voice tone and facial expression during post-contract support.

[0048] The contract procedure section can add a function in which a character provides a visual guide of the support content to the user when providing post-contract support. For example, the contract procedure section may provide a visual guide of the support content to the user when providing post-contract support. For example, the support content may be visually explained using diagrams and icons. The contract procedure section may also provide a visual guide of the support content to make it easier for the user to understand. For example, the important points of the support content may be highlighted. The contract procedure section may also provide a visual guide of the support content to enable the user to smoothly understand the content. For example, changes to the support content may be displayed in different colors. This allows the character to provide a visual guide of the support content to the user when providing post-contract support.

[0049] The contract procedure section can introduce a function that allows other users' reviews and ratings to be referenced when providing post-contract support. The contract procedure section, for example, provides a function that allows other users' reviews and ratings to be referenced when providing post-contract support. For example, it displays reviews about the support content. The contract procedure section also provides information that is useful when providing post-contract support based on the ratings of other users. For example, it displays ratings from users who have received the same support. The contract procedure section also displays other users' reviews and ratings in real time when providing post-contract support, so that the user can refer to them. For example, it automatically updates and displays the latest reviews and ratings. This allows other users' reviews and ratings to be referenced when providing post-contract support.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The character generation unit can set the character's special skills and hobbies based on the user's hobbies and interests. For example, if the user likes music, the character can be given the special skill of playing an instrument. If the user is interested in sports, the character can be given a sports hobby. Furthermore, if the user is good at cooking, the character can be given cooking skills. In this way, a character can be generated that matches the user's hobbies and interests.

[0052] The character generation unit can suggest the most suitable character based on the user's past purchase history and browsing history. For example, it can generate a character that matches the user's preferences based on the user's past purchase trends of products and services. It can also analyze the themes of websites and content frequently visited by the user and customize the character's appearance and personality based on that. Furthermore, it can integrate the purchase history and browsing history to suggest a character that best suits the user's preferences. This makes it possible to suggest the most suitable character based on the user's past purchase history and browsing history.

[0053] The character generation unit can analyze the user's voice tone and facial expression and adjust the character's personality and appearance based on that. For example, for a user with a bright voice tone, a character with a lively and cheerful personality can be generated. Also, for a user who smiles a lot, a character characterized by a smile can be generated. Furthermore, for a user with a gentle voice tone and smile, a kind and friendly character can be generated. In this way, the character's personality and appearance can be adjusted based on the user's voice tone and facial expression.

[0054] The character generation unit can add a function that refers to characters from movies or games that the user likes. For example, it can generate a character that incorporates the characteristics of characters from movies that the user likes. It can also refer to a database of movie or game characters to generate a character that suits the user's preferences. Furthermore, it can also generate a new character based on an image or name of a character that the user likes. This allows the addition of a function that refers to characters from movies or games that the user likes.

[0055] The character generation unit may incorporate a function that allows multiple users to collaboratively generate and share characters. For example, each user may customize parts of the character and then collaborate to create the final character. The generated character may also be shared with friends and family for collaborative use. Furthermore, the generated character may be made public in an online community and interacted with other users. This allows multiple users to collaboratively generate and share characters.

[0056] The conversation part allows the generation AI to learn the user's interests and concerns based on the content of the conversation and reflect them in future conversations. For example, it can record the topics that the user frequently talks about and bring those topics up in future conversations. The generation AI can also learn the user's interests and concerns based on the user's conversation history and reflect them in future conversations. Furthermore, the generation AI can analyze the content of the conversation in real time and instantly learn the user's interests and concerns. This allows the generation AI to learn the user's interests and concerns and reflect them in future conversations.

[0057] The conversation unit can analyze the tone and speed of the user's voice during conversation and respond accordingly. For example, if the user is excited, the character can respond in an excited tone. If the user is in a hurry, the character can respond quickly. Furthermore, if the user is calm, the character can respond in a calm tone. This makes it possible to respond according to the tone and speed of the user's voice.

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

[0059] Step 1: The character generation unit uses the generation AI to generate a character. For example, if the user inputs a prompt such as "I want to create a bright and energetic character" into the generation AI, the generation AI will generate a character based on that prompt. The character generation unit can also customize the appearance and personality according to the user's preferences. For example, the generation AI can generate the character's appearance and personality using deep learning technology. Step 2: In the conversation unit, the user converses in natural language with the character generated by the character generation unit. For example, if the user asks, "What products are popular today?", the generation AI generates an appropriate answer to the question and conveys it to the user through the character. The conversation unit can also use chatbot technology to conduct real-time conversations. For example, the generation AI can use voice recognition technology to understand the user's question and generate an appropriate answer. Step 3: The contract procedure section handles the smartphone contract procedure through the character. For example, if the user tells the character that they would like to sign up for a new smartphone, the generation AI will proceed with the contract procedure based on that request. The contract procedure section also guides the user through the process of selecting the smartphone model and plan they desire and entering the necessary information. For example, the generation AI automatically generates a contract based on the user's input and asks the user for confirmation.

[0060] (Example 2) The online shopping system according to the embodiment of the present invention is a system in which a user can converse with a character that the user has created and can then use the character to purchase a smartphone. This allows the user to complete the smartphone contract procedure while conversing with the character that the user has created.

[0061] An online shopping system according to an embodiment includes a character generation unit, a conversation unit, and a contract procedure unit. The character generation unit allows a user to generate a character using a generation AI. For example, if a user inputs a prompt such as "I want to create a cheerful and energetic character" into the generation AI, the generation AI generates a character based on the prompt. The character generation unit can also customize the character's appearance and personality according to the user's preferences. For example, the generation AI can generate the character's appearance and personality using deep learning technology. The conversation unit allows the user to converse in natural language with the character generated by the character generation unit. For example, if a user asks, "What products are popular today?", the generation AI generates an appropriate answer to the question and conveys it to the user through the character. The conversation unit can also conduct real-time conversations using chatbot technology. For example, the generation AI can understand the user's question using voice recognition technology and generate an appropriate answer. The contract procedure unit handles smartphone contract procedures through the character. For example, if a user tells the character, "I want to sign up for a new smartphone contract," the generation AI proceeds with the contract procedures based on the user's request. The contract procedure unit also guides the user through the process of selecting the smartphone model and plan they desire and entering the necessary information. For example, the generation AI automatically generates a contract based on the user's input and asks the user for confirmation. This allows the online shop system according to the embodiment to complete the smartphone contract procedure while conversing with a character the user has created.

[0062] The character generation unit can suggest the optimal character based on the user's past purchase history and browsing history. For example, the character generation unit analyzes the user's past purchase history, and the generation AI suggests the optimal character based on that data. For example, the character generation unit generates a character that suits the user's preferences based on trends in past purchased products and services. The character generation unit also suggests the optimal character based on the user's browsing history. For example, it analyzes the themes of websites and content frequently viewed by the user and customizes the character's appearance and personality based on that. The character generation unit also integrates the purchase history and browsing history, and the generation AI suggests the character that best suits the user's preferences. For example, it finds commonalities between past purchased products and viewed content and generates a character that reflects that. This makes it possible to suggest the optimal character based on the user's past purchase history and browsing history.

[0063] The character generation unit can analyze the user's voice tone and facial expression and adjust the character's personality and appearance based on that. For example, the character generation unit analyzes the user's voice tone, and the generation AI adjusts the character's personality based on that data. For example, for a user with a bright voice tone, it generates a character with a lively and cheerful personality. The character generation unit also analyzes the user's facial expression, and the generation AI adjusts the character's appearance based on that data. For example, for a user who smiles a lot, it generates a character that is characterized by smiling. The character generation unit also analyzes the voice tone and facial expression together, and the generation AI generates a character that best suits the user's personality and preferences. For example, for a user with a calm voice tone and smile, it generates a kind and friendly character. This makes it possible to adjust the character's personality and appearance based on the user's voice tone and facial expression.

[0064] The character generation unit uses the emotion estimation function to generate a character that corresponds to the user's current emotional state, thereby improving the user's mood. The character generation unit, for example, uses the emotion estimation function to analyze the user's current emotional state and generate a character based on that. For example, if the user is feeling stressed, the character generation unit generates a character that helps the user relax. The character generation unit also adjusts the character's personality and appearance using the generation AI according to the user's emotional state. For example, if the user is sad, the character generation unit generates a character that provides encouragement and comfort. The character generation unit also uses the emotion estimation function to generate a character that improves the user's mood. For example, if the user is tired, the character generation unit generates a character that cheers the user up. In this way, a character that corresponds to the user's current emotional state can be generated, thereby improving the user's mood.

[0065] The character generation unit can add a function that refers to characters from movies or games that the user likes. For example, the character generation unit inputs characters from movies or games that the user likes, and the generation AI uses that input as reference to generate a new character. For example, it generates a character that incorporates the characteristics of a character from a movie that the user likes. The character generation unit also references a database of movie or game characters to generate a character that suits the user's preferences. For example, it generates a new character based on the appearance and personality of a character that the user likes. The character generation unit also inputs an image or name of a character that the user likes, and the generation AI generates a new character based on that. For example, it generates an original character that incorporates the characteristics of a character that the user likes. This allows for the addition of a function that refers to characters from movies or games that the user likes.

[0066] The character generation unit may incorporate a function that allows multiple users to collaboratively generate and share characters. The character generation unit, for example, provides an interface for multiple users to collaboratively generate characters. For example, each user customizes a part of the character and collaboratively completes the final character. The character generation unit also incorporates a function that allows multiple users to share the generated characters. For example, the generated characters can be shared with friends and family for collaborative use. The character generation unit also provides a function that allows multiple users to collaboratively generate characters and share the characters in an online community. For example, the generated characters can be made public within the community and interacted with other users. This allows multiple users to collaboratively generate and share characters.

[0067] The character generation unit can use the emotion estimation function to collect other users' emotional reactions to a character generated by a user and provide feedback. The character generation unit, for example, uses the emotion estimation function to analyze what emotions other users have toward the generated character. For example, it collects positive and negative reactions to the character. The character generation unit also provides feedback to the generated character based on the emotional reactions of other users. For example, it suggests improvements to the character's appearance or personality. The character generation unit also evaluates the generated character based on the emotion estimation data and provides the result as feedback to the user. For example, it displays the character's popularity or sympathy level as a numerical value. This allows the character generation unit to collect other users' emotional reactions to the character generated by a user and provide feedback.

[0068] The conversation unit allows the generation AI to learn the user's interests and concerns based on the content of the conversation and reflect them in future conversations. For example, the conversation unit analyzes the content of the conversation and the generation AI learns the user's interests and concerns. For example, it records the topics that the user frequently talks about and brings up those topics in future conversations. The conversation unit also allows the generation AI to learn the user's interests and concerns based on the user's conversation history and reflect them in future conversations. For example, it provides more detailed information on the user's favorite topics and questions. The conversation unit also analyzes the content of the conversation in real time and the generation AI instantly learns the user's interests and concerns. For example, if the user expresses a new interest, it reflects that information in the next conversation. In this way, the user's interests and concerns can be learned and reflected in future conversations.

[0069] The conversation unit can analyze the tone and speed of the user's voice during conversation and react accordingly. The conversation unit, for example, analyzes the tone of the user's voice and causes the character to react accordingly. For example, if the user is excited, the character also responds in an excited tone. The conversation unit also analyzes the speed of the user's voice and causes the character to react accordingly. For example, if the user is in a hurry, the character also responds quickly. The conversation unit also analyzes the tone and speed of the voice together and causes the character to react according to the user's emotional state. For example, if the user is calm, the character also responds in a calm tone. This makes it possible to show a reaction according to the tone and speed of the user's voice.

[0070] The conversation unit uses the emotion estimation function to generate conversation content according to the user's emotional state, thereby improving user satisfaction. The conversation unit, for example, uses the emotion estimation function to analyze the user's emotional state and generate conversation content based on that. For example, if the user is tired, it provides conversation content that will relax the user. In addition, the conversation unit uses the generation AI to adjust the conversation content according to the user's emotional state. For example, if the user is sad, it provides words of encouragement and comfort. In addition, the conversation unit uses the emotion estimation function to generate conversation content to improve user satisfaction. For example, if the user is happy, it provides conversation content that shares that joy. In this way, conversation content according to the user's emotional state can be generated, improving user satisfaction.

[0071] The conversation unit can add a community function that allows users to interact with other users through conversations with characters. The conversation unit provides a community function that allows users to interact with other users through conversations with characters, for example. For example, users with common interests converse with each other through characters. The conversation unit also adds a function that allows characters to promote interaction with other users. For example, characters suggest conversations with other users to users. The conversation unit also provides a function that allows users to participate in a community through conversations with characters. For example, characters introduce community events and discussions to users. This allows users to interact with other users through conversations with characters.

[0072] The conversation unit can introduce a function that automatically translates the content of a conversation and allows users who speak different languages ​​to communicate with each other through a character. The conversation unit, for example, provides a function that automatically translates the content of a conversation and allows users who speak different languages ​​to communicate with each other through a character. For example, an English-speaking user and a Japanese-speaking user converse through a character. The conversation unit also uses an automatic translation function to support conversations between users who speak different languages ​​with a character. For example, the character translates the content of a conversation in real time and conveys it to the user. The conversation unit also introduces a function that allows users who speak different languages ​​to communicate with each other through a character. For example, the character provides multilingual conversations to promote interaction between users. This allows users who speak different languages ​​to communicate with each other through a character.

[0073] The conversation unit can provide a function that uses the emotion estimation function to record emotions felt by the user during a conversation and allow the user to look back on them later. The conversation unit, for example, uses the emotion estimation function to record emotions felt by the user during a conversation. For example, the joy or sadness felt by the user during a conversation is saved as data. The conversation unit also provides a function that allows the user to look back on the emotion data recorded during a conversation later. For example, it displays a list of past conversations and the emotions felt at the time. The conversation unit also uses the emotion estimation function to record emotion data during a conversation and allow the user to perform self-analysis based on the data. For example, it displays emotional fluctuations in a graph. This allows the user to record the emotions felt during a conversation and look back on them later.

[0074] During the contract procedure, the generation AI can refer to the user's past contract history and propose the optimal plan. For example, the contract procedure unit analyzes the user's past contract history and the generation AI proposes the optimal plan. For example, the generation AI proposes the optimal smartphone plan for the user based on past contract details and usage status. During the contract procedure, the generation AI can refer to the user's past contract history and automatically select the optimal plan. For example, the generation AI can automatically select the plan that is most suitable for the user based on past data. The contract procedure unit can also suggest the optimal plan based on the user's past contract history and allow the user to select that plan. For example, the generation AI can present the optimal plan to the user by referring to past contract details. This makes it possible to suggest the optimal plan by referring to the user's past contract history.

[0075] The contract procedure unit can analyze the user's tone of voice and facial expression during the contract procedure and provide support accordingly. The contract procedure unit, for example, analyzes the user's tone of voice, and a character provides support accordingly. For example, if the user speaks in an anxious tone, the character will say reassuring words. The contract procedure unit also analyzes the user's facial expression, and the character provides support accordingly. For example, if the user looks troubled, the character will provide specific advice. The contract procedure unit also analyzes the tone of voice and facial expression together, and the character provides support according to the user's emotional state. For example, if the user is excited, the character will respond calmly. This makes it possible to provide support according to the user's tone of voice and facial expression.

[0076] The contract procedure unit can use the emotion estimation function to generate dialogue for reducing the user's stress level during the contract procedure. The contract procedure unit, for example, uses the emotion estimation function to analyze the user's stress level during the contract procedure and generates dialogue content based on that. For example, if the user is feeling stressed, it provides dialogue content that helps them relax. In addition, the contract procedure unit has the generation AI adjust the dialogue content according to the user's stress level. For example, if the user is nervous, a character will say words to help the user relax. In addition, the contract procedure unit uses the emotion estimation function to generate dialogue for reducing the user's stress level. For example, if the user is feeling anxious, a character will provide dialogue content that reassures the user. In this way, it is possible to generate dialogue for reducing the user's stress level during the contract procedure.

[0077] The contract procedure unit can add a function in which a character provides the user with a visual guide of the contract contents during the contract procedure. For example, the contract procedure unit may provide the user with a visual guide of the contract contents during the contract procedure. For example, the contract contents may be visually explained using diagrams and icons. The contract procedure unit may also provide a visual guide of each step of the contract procedure, making it easier for the user to understand the procedure. For example, the progress of the procedure may be displayed using graphs and charts. The contract procedure unit may also provide a visual guide of the contract contents, allowing the user to proceed smoothly with the procedure. For example, the important points of the contract contents may be highlighted. This allows the character to provide the user with a visual guide of the contract contents during the contract procedure.

[0078] The contract procedure section can introduce a function that allows the user to refer to reviews and ratings from other users during the contract procedure. The contract procedure section, for example, provides a function that allows the user to refer to reviews and ratings from other users during the contract procedure. For example, it displays reviews of the smartphone that the user is about to sign up for. The contract procedure section also provides information that is useful during the contract procedure based on the ratings of other users. For example, it displays ratings from users who have signed up for the same plan. The contract procedure section also displays reviews and ratings from other users in real time during the contract procedure so that the user can refer to them. For example, it automatically updates and displays the latest reviews and ratings. This allows the user to refer to reviews and ratings from other users during the contract procedure.

[0079] The contract procedure unit can use the emotion estimation function to collect the user's emotional reactions during the contract procedure and use the collected data to improve the procedure. The contract procedure unit, for example, uses the emotion estimation function to collect the user's emotional reactions during the contract procedure. For example, the anxiety and stress felt by the user during the procedure is saved as data. The contract procedure unit also identifies areas for improvement in the procedure based on the emotion data collected during the contract procedure. For example, it identifies steps that are likely to cause stress to the user and improves those parts. The contract procedure unit also uses the emotion estimation data to help improve the contract procedure. For example, it analyzes the user's emotional reactions and optimizes the flow of the procedure. In this way, the user's emotional reactions during the contract procedure can be collected and used to improve the procedure.

[0080] In the contract procedure section, when the contract details are confirmed, the generation AI can compare them with the user's previous contract details and highlight any changes. For example, when the contract details are confirmed, the generation AI can compare them with the user's previous contract details and highlight any changes. For example, the differences between the previous contract details and the current contract details are displayed in different colors. In addition, in the contract procedure section, the generation AI automatically detects changes based on the user's previous contract details and notifies the user. For example, changes to the fee plan or service details are highlighted. In addition, when the contract details are confirmed, the generation AI can compare them with the previous contract details and highlight any important changes. For example, changes to the contract period or benefits are prominently displayed. This allows the contract details to be compared with the previous contract details and changes to be highlighted when confirming the contract details.

[0081] The contract procedure unit can analyze the user's tone of voice and facial expression when confirming the contract contents, and provide a confirmation method that corresponds to the tone of voice and facial expression. The contract procedure unit, for example, analyzes the user's tone of voice, and a character provides a confirmation method that corresponds to the tone of voice. For example, if the user speaks in an anxious tone, the character provides a detailed explanation. The contract procedure unit can also analyze the user's facial expression, and the character provides a confirmation method that corresponds to the facial expression. For example, if the user looks troubled, the character provides specific advice. The contract procedure unit can also analyze the tone of voice and facial expression together, and the character provides a confirmation method that corresponds to the user's emotional state. For example, if the user is excited, the character responds calmly. This makes it possible to provide a confirmation method that corresponds to the user's tone of voice and facial expression when confirming the contract contents.

[0082] The contract procedure unit can use the emotion estimation function to generate dialogue to reduce the user's anxiety when confirming the contract details. The contract procedure unit, for example, uses the emotion estimation function to analyze the user's anxiety when confirming the contract details and generates dialogue content based on that. For example, if the user is feeling anxious, it provides dialogue content that reassures the user. Furthermore, in the contract procedure unit, the generation AI adjusts the dialogue content according to the user's anxiety. For example, if the user is nervous, a character will say words to help the user relax. Furthermore, the contract procedure unit uses the emotion estimation function to generate dialogue to reduce the user's anxiety. For example, if the user is feeling anxious, a character will provide dialogue content that reassures the user. In this way, it is possible to generate dialogue to reduce the user's anxiety when confirming the contract details.

[0083] The contract procedure unit can add a function in which a character provides a visual guide of the contract contents to the user when the contract contents are being confirmed. For example, the contract procedure unit may provide a visual guide of the contract contents to the user when the contract contents are being confirmed. For example, the contract contents may be visually explained using diagrams and icons. The contract procedure unit may also provide a visual guide of the contract contents to the user, making it easier for the user to understand the contents. For example, the important points of the contract contents may be highlighted. The contract procedure unit may also provide a visual guide of the contract contents to enable the user to smoothly understand the contents. For example, changes to the contract contents may be displayed in different colors. This allows the character to provide a visual guide of the contract contents to the user when the contract contents are being confirmed.

[0084] The contract procedure section can introduce a function that allows the user to refer to reviews and ratings from other users when confirming the contract details. The contract procedure section, for example, provides a function that allows the user to refer to reviews and ratings from other users when confirming the contract details. For example, it displays reviews of the smartphone that the user is about to sign up for. The contract procedure section also provides information that is useful when confirming the contract details based on the ratings of other users. For example, it displays ratings from users who have signed up for the same plan. The contract procedure section also displays reviews and ratings from other users in real time when confirming the contract details, allowing the user to refer to them. For example, it automatically updates and displays the latest reviews and ratings. This allows the user to refer to reviews and ratings from other users when confirming the contract details.

[0085] The contract procedure unit uses the emotion estimation function to collect the user's emotional reactions when confirming the contract contents, and can use this information to improve the procedure. The contract procedure unit, for example, uses the emotion estimation function to collect the user's emotional reactions when confirming the contract contents. For example, the anxiety and stress felt by the user when confirming the contract contents is saved as data. The contract procedure unit also identifies areas for improvement in the procedure based on the emotion data collected when confirming the contract contents. For example, it finds areas where the user is likely to feel stressed and improves those areas. The contract procedure unit also uses the emotion estimation data to help improve the contract content confirmation procedure. For example, it analyzes the user's emotional reactions and optimizes the flow of the confirmation procedure. In this way, the user's emotional reactions when confirming the contract contents can be collected and used to improve the procedure.

[0086] The contract procedure unit allows the generation AI to refer to the user's past support history and provide the most appropriate support when providing post-contract support. The contract procedure unit, for example, analyzes the user's past support history and the generation AI provides the most appropriate support. For example, the unit provides the most appropriate support to the user based on past inquiries and solutions. Furthermore, the contract procedure unit allows the generation AI to refer to the user's past support history and automatically select the most appropriate support when providing post-contract support. For example, the unit automatically selects the support that is most appropriate for the user based on past data. Furthermore, the contract procedure unit allows the generation AI to provide the most appropriate support based on the user's past support history and enable the user to receive that support. For example, the unit refers to the content of past support and presents the most appropriate support to the user. This allows the generation AI to refer to the user's past support history when providing post-contract support and provide the most appropriate support.

[0087] The contract procedure unit can analyze the user's tone of voice and facial expression during post-contract support and provide support accordingly. The contract procedure unit, for example, analyzes the user's tone of voice, and a character provides support accordingly. For example, if the user speaks in an anxious tone, the character will say reassuring words. The contract procedure unit also analyzes the user's facial expression, and the character provides support accordingly. For example, if the user looks troubled, the character will provide specific advice. The contract procedure unit also analyzes the voice tone and facial expression together, and the character provides support according to the user's emotional state. For example, if the user is excited, the character will respond calmly. This makes it possible to provide support according to the user's voice tone and facial expression during post-contract support.

[0088] The contract procedure unit can use the emotion estimation function to generate dialogue to improve user satisfaction during post-contract support. The contract procedure unit, for example, uses the emotion estimation function to analyze the user's emotional state during post-contract support and generate dialogue content based on that. For example, if the user is feeling anxious, it provides dialogue content that reassures the user. In addition, the contract procedure unit has the generation AI adjust the dialogue content according to the user's emotional state. For example, if the user is nervous, a character will say words to help the user relax. In addition, the contract procedure unit uses the emotion estimation function to generate dialogue to improve user satisfaction. For example, if the user is happy, it provides dialogue content that shares that joy. In this way, it is possible to generate dialogue to improve user satisfaction during post-contract support.

[0089] The contract procedure section can add a function in which a character provides a visual guide of the support content to the user when providing post-contract support. For example, the contract procedure section may provide a visual guide of the support content to the user when providing post-contract support. For example, the support content may be visually explained using diagrams and icons. The contract procedure section may also provide a visual guide of the support content to make it easier for the user to understand. For example, the important points of the support content may be highlighted. The contract procedure section may also provide a visual guide of the support content to enable the user to smoothly understand the content. For example, changes to the support content may be displayed in different colors. This allows the character to provide a visual guide of the support content to the user when providing post-contract support.

[0090] The contract procedure section can introduce a function that allows other users' reviews and ratings to be referenced when providing post-contract support. The contract procedure section, for example, provides a function that allows other users' reviews and ratings to be referenced when providing post-contract support. For example, it displays reviews about the support content. The contract procedure section also provides information that is useful when providing post-contract support based on the ratings of other users. For example, it displays ratings from users who have received the same support. The contract procedure section also displays other users' reviews and ratings in real time when providing post-contract support, so that the user can refer to them. For example, it automatically updates and displays the latest reviews and ratings. This allows other users' reviews and ratings to be referenced when providing post-contract support.

[0091] The contract procedure unit can use the emotion estimation function to collect the user's emotional reactions during post-contract support and use the collected data to improve support. The contract procedure unit, for example, uses the emotion estimation function to collect the user's emotional reactions during post-contract support. For example, the anxiety and stress felt by the user during support is saved as data. The contract procedure unit also identifies areas of support that need improvement based on the emotion data collected during post-contract support. For example, it finds areas where the user is likely to feel stressed and improves those areas. The contract procedure unit also uses the emotion estimation data to help improve post-contract support. For example, it analyzes the user's emotional reactions and optimizes the support flow. This allows the user's emotional reactions during post-contract support to be collected and used to improve support.

[0092] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0093] The character generation unit can set the character's special skills and hobbies based on the user's hobbies and interests. For example, if the user likes music, the character can be given the special skill of playing an instrument. If the user is interested in sports, the character can be given a sports hobby. Furthermore, if the user is good at cooking, the character can be given cooking skills. In this way, a character can be generated that matches the user's hobbies and interests.

[0094] The character generation unit can suggest the most suitable character based on the user's past purchase history and browsing history. For example, it can generate a character that matches the user's preferences based on the user's past purchase trends of products and services. It can also analyze the themes of websites and content frequently visited by the user and customize the character's appearance and personality based on that. Furthermore, it can integrate the purchase history and browsing history to suggest a character that best suits the user's preferences. This makes it possible to suggest the most suitable character based on the user's past purchase history and browsing history.

[0095] The character generation unit can analyze the user's voice tone and facial expression and adjust the character's personality and appearance based on that. For example, for a user with a bright voice tone, a character with a lively and cheerful personality can be generated. Also, for a user who smiles a lot, a character characterized by a smile can be generated. Furthermore, for a user with a gentle voice tone and smile, a kind and friendly character can be generated. In this way, the character's personality and appearance can be adjusted based on the user's voice tone and facial expression.

[0096] The character generation unit uses the emotion estimation function to generate a character according to the user's current emotional state, thereby improving the user's mood. For example, if the user is feeling stressed, a character that relaxes the user can be generated. If the user is sad, a character that provides encouragement and comfort can be generated. Furthermore, if the user is tired, a character that cheers the user up can be generated. In this way, a character according to the user's current emotional state can be generated, thereby improving the user's mood.

[0097] The character generation unit can add a function that refers to characters from movies or games that the user likes. For example, it can generate a character that incorporates the characteristics of characters from movies that the user likes. It can also refer to a database of movie or game characters to generate a character that suits the user's preferences. Furthermore, it can also generate a new character based on an image or name of a character that the user likes. This allows the addition of a function that refers to characters from movies or games that the user likes.

[0098] The character generation unit may incorporate a function that allows multiple users to collaboratively generate and share characters. For example, each user may customize parts of the character and then collaborate to create the final character. The generated character may also be shared with friends and family for collaborative use. Furthermore, the generated character may be made public in an online community and interacted with other users. This allows multiple users to collaboratively generate and share characters.

[0099] The character generation unit can use the emotion estimation function to collect other users' emotional reactions to a character generated by the user and provide feedback. For example, it can analyze how other users feel about the generated character. It can also suggest improvements to the generated character based on the emotional reactions of other users. It can also evaluate the generated character based on the emotion estimation data and provide feedback to the user. This allows it to collect other users' emotional reactions to a character generated by the user and provide feedback.

[0100] The conversation part allows the generation AI to learn the user's interests and concerns based on the content of the conversation and reflect them in future conversations. For example, it can record the topics that the user frequently talks about and bring those topics up in future conversations. The generation AI can also learn the user's interests and concerns based on the user's conversation history and reflect them in future conversations. Furthermore, the generation AI can analyze the content of the conversation in real time and instantly learn the user's interests and concerns. This allows the generation AI to learn the user's interests and concerns and reflect them in future conversations.

[0101] The conversation unit can analyze the tone and speed of the user's voice during conversation and respond accordingly. For example, if the user is excited, the character can respond in an excited tone. If the user is in a hurry, the character can respond quickly. Furthermore, if the user is calm, the character can respond in a calm tone. This makes it possible to respond according to the tone and speed of the user's voice.

[0102] The conversation unit uses the emotion estimation function to generate conversation content according to the user's emotional state, thereby improving user satisfaction. For example, if the user is tired, conversation content that will relax the user can be provided. If the user is sad, words of encouragement and comfort can be provided. Furthermore, if the user is happy, conversation content that shares that joy can be provided. In this way, conversation content according to the user's emotional state can be generated, improving user satisfaction.

[0103] The processing flow of the second embodiment will be briefly explained below.

[0104] Step 1: The character generation unit uses the generation AI to generate a character. For example, if the user inputs a prompt such as "I want to create a bright and energetic character" into the generation AI, the generation AI will generate a character based on that prompt. The character generation unit can also customize the appearance and personality according to the user's preferences. For example, the generation AI can generate the character's appearance and personality using deep learning technology. Step 2: In the conversation unit, the user converses in natural language with the character generated by the character generation unit. For example, if the user asks, "What products are popular today?", the generation AI generates an appropriate answer to the question and conveys it to the user through the character. The conversation unit can also use chatbot technology to conduct real-time conversations. For example, the generation AI can use voice recognition technology to understand the user's question and generate an appropriate answer. Step 3: The contract procedure section handles the smartphone contract procedure through the character. For example, if the user tells the character that they would like to sign up for a new smartphone, the generation AI will proceed with the contract procedure based on that request. The contract procedure section also guides the user through the process of selecting the smartphone model and plan they desire and entering the necessary information. For example, the generation AI automatically generates a contract based on the user's input and asks the user for confirmation.

[0105] 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.

[0106] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0107] 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.

[0108] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0109] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0122] 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.

[0123] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0124] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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).

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the 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 specific processing unit 290 using these models.

[0134] 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.

[0135] 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.

[0136] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0137] 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.

[0138] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0139] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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).

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] In the robot 414, 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 robot 414 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.

[0150] 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.

[0151] 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.

[0152] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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).

[0158] 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.

[0159] 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."

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0172] 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. a character generation unit in which a user generates a character using a generation AI; a conversation unit in which a user converses in natural language with the character generated by the character generation unit; a contract procedure unit that performs contract procedures for a smartphone through the character; A system characterized by:

2. The character generation unit Suggesting the most suitable character based on the user's past purchase history and browsing history 2. The system of claim 1.

3. The character generation unit Analyzing the user's tone of voice and facial expressions and adjusting the character's personality and appearance based on that.

2. The system of claim 1.

4. The character generation unit Generate a character according to the user's current emotional state to improve the user's mood 2. The system of claim 1.

5. The character generation unit Add a feature that allows users to refer to their favorite movie or game characters 2. The system of claim 1.

Images