System

Abstract

An object of a system according to an embodiment is to generate humor or laughter based on a user's input.SOLUTION: A system includes a prompt analysis unit, a humor generation unit, and a provision unit. The prompt analysis unit analyzes a prompt input by a user. The humor generation section generates humor based on the prompt analyzed by the prompt analysis section. The provision section provides the humor generated by the humor generation section.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 techniques do not adequately generate humor or laughter based on user input, and there is room for improvement.

[0005] The system according to the embodiment aims to generate humor and laughter based on user input. [Means for solving the problem]

[0006] The system according to the embodiment includes a prompt analysis unit, a humor generation unit, and a providing unit. The prompt analysis unit analyzes a prompt input by a user. The humor generation unit generates humor based on the prompt analyzed by the prompt analysis unit. The providing unit provides the humor generated by the humor generation unit. [Effects of the Invention]

[0007] The system according to the embodiment can generate humor and laughter based on user input. [Brief explanation of the drawings]

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

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

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

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

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

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

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

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

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

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

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

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

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

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

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

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

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

[0028] (Example 1) The AI ​​Comedy Machine according to an embodiment of the present invention is a system that generates humor and laughter using generative AI. This system allows salespeople and presenters to incorporate laughter and humor into their icebreaker talks and presentations, effectively attracting attention and empathy. It can also provide laughter to relieve stress and fatigue and promote positive feelings for people who want to make their daily lives more enjoyable. In this way, the AI ​​Comedy Machine can support the talks of salespeople and presenters and bring laughter to everyday life.

[0029] The AI ​​comedy machine according to the embodiment includes a prompt analysis unit, a humor generation unit, and a provision unit. The prompt analysis unit analyzes prompts input by a user. For example, the prompt analysis unit understands the intent and context of the prompt using natural language processing technology. The prompt analysis unit can also extract important information from the prompt using keyword extraction technology. For example, the prompt analysis unit analyzes a user-input prompt such as "Please tell me some jokes that can be used in sales talks" and extracts information for generating jokes suitable for sales talks. The humor generation unit generates humor based on the prompt analyzed by the prompt analysis unit. For example, the humor generation unit generates jokes using a text generation AI (e.g., GPT-3). The humor generation unit can also generate humor that includes not only text but also audio and video using a multimodal generation AI. For example, the humor generation unit generates icebreaker jokes that can be used in sales talks based on the user's prompt. The provision unit provides the humor generated by the humor generation unit. For example, the provision unit displays the generated jokes in text format. The provision unit can also play the generated jokes as audio using speech synthesis technology. Furthermore, the providing unit can provide the generated joke as an animation or video. For example, the providing unit displays the generated joke on a smartphone or tablet screen and plays it as audio. This allows the AI ​​comedy machine according to the embodiment to generate and provide humor based on a user's prompts. For example, when a salesperson introduces a new product, they can use a joke provided by the generation AI to break the ice and attract the audience's attention. Also, when a user is feeling stressed, the generation AI can provide a relaxing joke to encourage a positive mood.

[0030] The prompt analysis unit can analyze prompts and understand their intentions and backgrounds. For example, the prompt analysis unit uses natural language processing technology to analyze a user's input prompt and understand its intentions and backgrounds. For example, the prompt analysis unit analyzes a prompt such as "Please tell me some jokes that can be used in sales talks" and generates jokes that are suitable for sales talks. The prompt analysis unit also allows the generation AI to generate appropriate humor based on the content of the prompt. For example, in response to a prompt such as "Please tell me some jokes that can be used in conversations with friends," a casual joke is generated. The prompt analysis unit also analyzes a user's input prompt, and the generation AI generates appropriate humor based on the background information. For example, in response to a prompt such as "Please tell me some jokes that can help me relax when I'm feeling stressed," a relaxing joke is generated. This allows the generation AI to generate more appropriate humor by understanding the intentions and backgrounds of the user's prompts.

[0031] The humor generation unit can generate humor in at least one different genre among black humor, satire, and parody. For example, the humor generation unit trains the generation AI on a dataset for generating humor in different genres, such as black humor, satire, and parody. For example, representative jokes from each genre are collected and trained by the generation AI. The humor generation unit also provides humor genres that the user can select, and the generation AI generates appropriate jokes based on the selection. For example, if the user selects black humor, the generation AI generates jokes specific to that genre. To generate humor in different genres, the humor generation unit also combines multiple humor styles to create new jokes. For example, the generation AI generates jokes that combine satire and parody. This allows the generation AI to generate humor in different genres and meet the diverse needs of users.

[0032] The providing unit can provide humor in any of the following formats: text, audio, or video. For example, the providing unit provides jokes generated by the generation AI as audio using speech synthesis technology. For example, a function is added to play generated jokes in a natural voice. The providing unit also provides jokes generated by the generation AI as animations or videos. For example, an animation matching the content of the joke is automatically generated to provide visual entertainment to the user. The providing unit also provides humor in a multimedia format that combines text, audio, and video. For example, the text of the joke is displayed while simultaneously playing audio and streaming video. This allows the generated humor to be provided in a variety of formats, making it possible to provide humor that suits the user's usage scenario.

[0033] The humor generation unit can generate humor appropriate for different cultures and languages. For example, the humor generation unit learns a dataset for the generation AI to generate jokes appropriate for different languages ​​and cultures. For example, it collects representative jokes from each country and trains the generation AI. The humor generation unit also provides languages ​​and cultures that the user can select, and the generation AI generates appropriate jokes based on that selection. For example, if the user selects English, the generation AI generates English-language jokes. To accommodate different cultures and languages, the humor generation unit uses a multilingual humor generation algorithm for the generation AI. For example, the same joke is generated in multiple languages, taking cultural nuances into account. This allows the generation AI to generate humor appropriate for different cultures and languages, thereby catering to an international audience.

[0034] The prompt analysis unit can adjust the tone and style of the humor to be generated according to the content of the prompt. For example, the prompt analysis unit causes the generation AI to adjust the tone and style of the humor based on the user's input prompt. For example, in response to the prompt, "Please tell me some light-hearted jokes," the generation AI generates light-hearted jokes. The prompt analysis unit also causes the generation AI to change the style of the humor according to the content of the prompt. For example, in response to the prompt, "Please tell me some black jokes," the generation AI generates black jokes. In addition, the prompt analysis unit also causes the generation AI to analyze the content of the prompt and generate appropriate humor to meet the user's expectations. For example, in response to the prompt, "Please tell me some satirical jokes," the generation AI generates satirical jokes. In this way, the user's expectations can be met by adjusting the tone and style of the humor according to the content of the prompt.

[0035] The prompt analysis unit automatically suggests related questions in response to prompts entered by the user, thereby supporting more specific humor generation. For example, the prompt analysis unit allows the generation AI to automatically suggest related questions in response to a prompt entered by the user. For example, in response to the prompt, "Please tell me some jokes that can be used in sales talks," the prompt analysis unit asks, "What kind of products do you plan to introduce?" The prompt analysis unit also allows the generation AI to suggest questions to support more specific humor generation based on the user's prompt. For example, in response to the prompt, "Please tell me some jokes that can be used in conversations with friends," the prompt analysis unit asks, "What topics do you talk about?" The prompt analysis unit also allows the generation AI to suggest related questions in response to prompts entered by the user, thereby supporting more specific humor generation. For example, in response to the prompt, "Please tell me some jokes that can be used to relax when I'm feeling stressed," the prompt analysis unit asks, "In what situations do you feel stressed?" This allows the generation AI to automatically suggest related questions in response to prompts entered by the user, thereby supporting more specific humor generation.

[0036] The prompt analysis unit provides humor categories that the user can select when entering a prompt, thereby increasing the variety of humor to be generated. For example, the prompt analysis unit provides humor categories that the generation AI can select when the user enters a prompt. For example, it displays categories such as "black jokes," "sarcastic jokes," and "parodies." The prompt analysis unit also provides humor categories that the user can select when entering a prompt, and the generation AI generates appropriate jokes based on the selection. For example, if the user selects "light jokes," the generation AI generates jokes with a light tone. The prompt analysis unit also provides humor categories that the generation AI can select when entering a prompt, thereby increasing the variety of humor to be generated. For example, if the user selects "jokes that can be used in conversations with friends," the generation AI generates casual jokes. In this way, by providing humor categories that the user can select when entering a prompt, the variety of humor to be generated can be increased.

[0037] The provision unit can insert humor at the optimal timing depending on the content of a sales talk or presentation. For example, the provision unit analyzes the script of a sales talk or presentation, and the generation AI inserts humor at the optimal timing. For example, inserting an ice-breaker joke before a product introduction. The provision unit also analyzes the slides and materials of the presentation, and the generation AI inserts humor at the appropriate timing. For example, inserting a light-hearted joke before an important point. The provision unit also monitors the progress of the sales talk or presentation in real time, and the generation AI provides humor at the optimal timing. For example, inserting a joke while watching the audience's reaction. This makes it possible to attract the audience's attention by inserting humor at the optimal timing depending on the content of the sales talk or presentation.

[0038] The providing unit can provide a function that automatically incorporates generated humor into presentation slides and materials. For example, the providing unit integrates the generative AI into a presentation slide creation tool to provide a function that automatically incorporates humor into slides. For example, it automatically generates jokes that match the content of the slides. The providing unit also provides a function that automatically inserts humor generated by the generative AI into presentation materials. For example, it inserts jokes appropriate for each section of the materials. The providing unit also analyzes presentation slides and materials and develops a system in which the generative AI automatically incorporates appropriate humor. For example, it inserts an ice-breaker joke before an important point. This allows the quality of presentations to be improved by automatically incorporating generated humor into presentation slides and materials.

[0039] The providing unit can automatically synchronize the humor generated by the generation AI with devices used by salespeople and presenters. The providing unit automatically synchronizes the humor generated by the generation AI with, for example, smartphones and tablets used by salespeople and presenters. For example, jokes are displayed in real time during a presentation. The providing unit also develops a system that automatically synchronizes the humor generated by the generation AI with devices used by salespeople and presenters. For example, it inserts jokes in conjunction with a slide creation tool. The providing unit also provides a function that automatically synchronizes the humor generated by the generation AI with devices used by salespeople and presenters. For example, it displays jokes as the presentation progresses. This allows the efficiency of presentation preparation to be improved by automatically synchronizing the humor generated with devices used by salespeople and presenters.

[0040] The humor generation unit can generate humor appropriate for different industries and business situations. For example, the humor generation unit learns a dataset that the generation AI uses to generate humor appropriate for different industries and business situations. For example, it collects representative jokes from each industry and trains the generation AI. The humor generation unit also provides industries and business situations that the user can select, and the generation AI generates appropriate jokes based on that selection. For example, if the user selects the IT industry, it generates jokes specialized for the IT industry. In addition, to accommodate different industries and business situations, the humor generation unit allows the generation AI to combine various humor styles to create new jokes. For example, it generates humor that combines jokes from the medical and education industries. This allows the generation AI to generate humor appropriate for different industries and business situations, making it usable for a wide range of applications.

[0041] The providing unit can provide humor at the optimal timing according to the user's daily schedule and activities. The providing unit, for example, analyzes the user's daily schedule, and the generation AI provides humor at the optimal timing. For example, it provides a joke that will refresh the user during their morning commute. The providing unit also provides humor at the appropriate timing based on the user's activity data. For example, it provides a joke that will help the user relax between work. The providing unit also continuously monitors the user's daily schedule and activities, and the generation AI provides humor at the optimal timing. For example, it provides a joke that will help the user relax when they are feeling stressed. In this way, providing humor at the optimal timing according to the user's daily schedule and activities makes daily life more enjoyable.

[0042] The providing unit can analyze the user's past laughter history and provide individually customized humor. The providing unit, for example, analyzes the user's past laughter history, and the generation AI provides individually customized humor. For example, the providing unit learns the patterns of jokes that the user has liked in the past. The providing unit also allows the generation AI to provide appropriate humor based on the user's laughter history. For example, the generation AI generates new jokes based on the style of jokes that the user has laughed at in the past. The providing unit also continuously monitors the user's past laughter history, and the generation AI provides individually customized humor. For example, if the user likes jokes of a specific genre, the generation AI provides jokes specialized for that genre. In this way, by analyzing the user's past laughter history and providing individually customized humor, it is possible to provide humor that is more familiar to the user.

[0043] The providing unit can work in conjunction with smart home devices to provide humor within the home. The providing unit works in conjunction with, for example, a smart speaker or smart display, and the generation AI provides humor within the home. For example, it plays a joke as an alarm in the morning. The providing unit also works in conjunction with smart home devices, and the generation AI provides humor according to the situation within the home. For example, it provides a joke that will help the family relax when they get together. The providing unit also develops a system that enables the generation AI to provide humor within the home through smart home devices. For example, it plays a joke when a smart light is turned on. In this way, by working in conjunction with smart home devices to provide humor within the home, it is possible to brighten the atmosphere within the home.

[0044] The humor generation unit can generate humor that matches the user's hobbies and interests. For example, the humor generation unit analyzes the user's hobbies and interests, and the generation AI generates humor that matches them. For example, if the user likes sports, the generation AI provides jokes related to sports. The humor generation unit also provides appropriate humor based on the user's hobbies and interests. For example, if the user likes movies, the generation AI provides jokes related to movies. The humor generation unit also continuously monitors the user's hobbies and interests, and the generation AI provides humor that matches them. For example, if the user takes up a new hobby, the generation AI provides jokes related to that hobby. This allows for humor that matches the user's hobbies and interests to be generated, making everyday life more enjoyable.

[0045] The humor generation unit can analyze a user's preferences and past usage history to provide individually customized humor. The humor generation unit, for example, analyzes a user's past usage history, and the generation AI provides individually customized humor. For example, the humor generation unit learns the patterns of jokes that the user has liked in the past. The humor generation unit also provides appropriate humor based on the user's preferences, and the generation AI provides jokes specific to that genre. The humor generation unit also continuously monitors the user's past usage history, and the generation AI provides individually customized humor. For example, if a user likes jokes of a specific genre, the generation AI provides jokes specific to that genre. In this way, by analyzing a user's preferences and past usage history and providing individually customized humor, it is possible to provide humor that is more familiar to the user.

[0046] The humor generation unit can continuously improve the quality of the humor generated based on user feedback. For example, the humor generation unit collects user ratings (e.g., star ratings and comments) on jokes, and the generation AI improves the next joke generation based on that feedback. For example, it avoids patterns in jokes that have received low ratings. The humor generation unit also analyzes user feedback and continuously improves the quality of the humor generated by the generation AI. For example, it learns the style of jokes that users prefer and generates new jokes based on that. The humor generation unit also develops a system that continuously improves the quality of the humor generated by the generation AI based on user feedback. For example, it analyzes user ratings in real time and reflects them in the generation of the next joke. In this way, the quality of the humor generated based on user feedback can be continuously improved, thereby providing higher quality humor.

[0047] The providing unit can provide a function that allows a user to share customized humor with other users. The providing unit provides, for example, a function that allows a user to share customized jokes with other users. For example, jokes created by the user are shared on a social networking site or a messaging app. The providing unit also develops a platform for sharing customized humor. For example, a user posts their own jokes, and other users rate and comment on them. The providing unit also provides a function that allows a user to share customized humor with other users. For example, a joke created by a user is shared, allowing other users to use it. In this way, by providing a function that allows a user to share customized humor with other users, it is possible to spread the enjoyment of humor.

[0048] The providing unit can make the customized humor available on different devices and platforms. For example, the providing unit develops a system that allows users to use customized humor on different devices and platforms. For example, the system allows the same jokes to be used on smartphones, tablets, PCs, etc. The providing unit also stores the customized humor on the cloud and makes it accessible on different devices and platforms. For example, the system allows users to access their own jokes from any device. The providing unit also provides an API that allows the customized humor to be used on different devices and platforms. For example, the system allows other applications and services to use the customized jokes. This improves user convenience by allowing the customized humor to be used on different devices and platforms.

[0049] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0050] The AI ​​Comedy Machine can also analyze a user's past laughing history and provide individually customized humor. For example, it can learn the patterns of jokes that the user liked in the past and generate new jokes based on that. Also, if a user likes jokes of a specific genre, it can provide jokes specialized for that genre. In this way, by analyzing a user's past laughing history and providing individually customized humor, it can provide humor that is more familiar to the user.

[0051] The AI ​​comedy machine can also be equipped with the ability to generate humor appropriate for different cultures and languages. For example, it can collect representative jokes from various countries and train the generation AI to learn them. It can also provide users with a choice of language and culture, generating appropriate jokes based on that selection. It can also generate the same joke in multiple languages, taking cultural nuances into account. This allows it to cater to an international audience by generating humor appropriate for different cultures and languages.

[0052] The AI ​​Comedy Machine can also be equipped with the ability to generate humor tailored to the user's hobbies and interests. For example, if the user likes sports, it can provide jokes related to sports. If the user likes movies, it can provide jokes related to movies. It can also continuously monitor the user's hobbies and interests and provide jokes related to new hobbies. This can make everyday life more enjoyable by generating humor tailored to the user's hobbies and interests.

[0053] The AI ​​Comedy Machine can also have a function that allows users to share their customized humor with other users. For example, users can share jokes they create on social media or messaging apps. A platform for sharing customized humor can also be developed, allowing users to post their own jokes and other users to rate and comment on them. Furthermore, it is possible for users to share their jokes and make them available to other users. This allows users to share their customized humor with other users, thereby broadening the enjoyment of humor.

[0054] The AI ​​comedy machine can also be equipped with the ability to generate humor tailored to different industries and business situations. For example, it can collect representative jokes from each industry and train the generation AI to learn from them. It can also provide users with industries and business situations to choose from, generating appropriate jokes based on their selection. Furthermore, to accommodate different industries and business situations, the generation AI can combine various humor styles to create new jokes. This allows it to be used for a wide range of purposes by generating humor tailored to different industries and business situations.

[0055] The AI ​​Comedy Machine can also be equipped with the ability to link with smart home devices and provide humor within the home. For example, by linking with a smart speaker or smart display, the generation AI can provide humor within the home. It can also provide humor according to the situation within the home. For example, it can provide relaxing jokes when the family gets together. Furthermore, it is possible to develop a system that allows the generation AI to provide humor within the home through smart home devices. This allows it to link with smart home devices and provide humor within the home, brightening the atmosphere within the home.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The prompt analysis unit analyzes the prompt entered by the user. For example, the prompt analysis unit uses natural language processing technology to understand the intent and background of the prompt, and uses keyword extraction technology to extract important information from the prompt. Specifically, it analyzes the prompt entered by the user, "Please tell me some jokes that can be used in sales talks," and extracts information needed to generate jokes suitable for sales talks. Step 2: The humor generator generates humor based on the prompt analyzed by the prompt analyzer. For example, the humor generator can generate jokes using text generation AI (e.g., GPT-3) and can also generate humor that includes not only text but also audio and video using multimodal generation AI. Specifically, it generates icebreaker jokes that can be used in sales talks. Step 3: The providing unit provides the humor generated by the humor generating unit. For example, the providing unit may display the generated joke in text format, play it as audio using speech synthesis technology, or provide it as animation or video. Specifically, the generated joke is displayed on the screen of a smartphone or tablet and played as audio.

[0058] (Example 2) The AI ​​Comedy Machine according to an embodiment of the present invention is a system that generates humor and laughter using generative AI. This system allows salespeople and presenters to incorporate laughter and humor into their icebreaker talks and presentations, effectively attracting attention and empathy. It can also provide laughter to relieve stress and fatigue and promote positive feelings for people who want to make their daily lives more enjoyable. In this way, the AI ​​Comedy Machine can support the talks of salespeople and presenters and bring laughter to everyday life.

[0059] The AI ​​comedy machine according to the embodiment includes a prompt analysis unit, a humor generation unit, and a provision unit. The prompt analysis unit analyzes prompts input by a user. For example, the prompt analysis unit understands the intent and context of the prompt using natural language processing technology. The prompt analysis unit can also extract important information from the prompt using keyword extraction technology. For example, the prompt analysis unit analyzes a user-input prompt such as "Please tell me some jokes that can be used in sales talks" and extracts information for generating jokes suitable for sales talks. The humor generation unit generates humor based on the prompt analyzed by the prompt analysis unit. For example, the humor generation unit generates jokes using a text generation AI (e.g., GPT-3). The humor generation unit can also generate humor that includes not only text but also audio and video using a multimodal generation AI. For example, the humor generation unit generates icebreaker jokes that can be used in sales talks based on the user's prompt. The provision unit provides the humor generated by the humor generation unit. For example, the provision unit displays the generated jokes in text format. The provision unit can also play the generated jokes as audio using speech synthesis technology. Furthermore, the providing unit can provide the generated joke as an animation or video. For example, the providing unit displays the generated joke on a smartphone or tablet screen and plays it as audio. This allows the AI ​​comedy machine according to the embodiment to generate and provide humor based on a user's prompts. For example, when a salesperson introduces a new product, they can use a joke provided by the generation AI to break the ice and attract the audience's attention. Also, when a user is feeling stressed, the generation AI can provide a relaxing joke to encourage a positive mood.

[0060] The prompt analysis unit can analyze prompts and understand their intentions and backgrounds. For example, the prompt analysis unit uses natural language processing technology to analyze a user's input prompt and understand its intentions and backgrounds. For example, the prompt analysis unit analyzes a prompt such as "Please tell me some jokes that can be used in sales talks" and generates jokes that are suitable for sales talks. The prompt analysis unit also allows the generation AI to generate appropriate humor based on the content of the prompt. For example, in response to a prompt such as "Please tell me some jokes that can be used in conversations with friends," a casual joke is generated. The prompt analysis unit also analyzes a user's input prompt, and the generation AI generates appropriate humor based on the background information. For example, in response to a prompt such as "Please tell me some jokes that can help me relax when I'm feeling stressed," a relaxing joke is generated. This allows the generation AI to generate more appropriate humor by understanding the intentions and backgrounds of the user's prompts.

[0061] The humor generation unit can incorporate real-time user reactions as feedback and reflect them in the next joke generation. For example, the humor generation unit analyzes the user's laughter and facial expressions in real time in response to a joke generated by the generation AI and incorporates that data as feedback. For example, the humor generation unit collects user reactions using a camera or microphone and reflects them in the next joke generation. The humor generation unit also collects user ratings of jokes (e.g., star ratings and comments) and uses that feedback to improve the next joke generation by the generation AI. For example, it avoids patterns in jokes that receive low ratings. The humor generation unit also analyzes the user's real-time reactions and adjusts the tone and content of the joke based on those reactions. For example, if the user does not laugh, the generation AI changes the tone of the next joke. In this way, the next humor generation can be improved by incorporating the user's real-time reactions as feedback.

[0062] The humor generation unit can generate humor in at least one different genre among black humor, satire, and parody. For example, the humor generation unit trains the generation AI on a dataset for generating humor in different genres, such as black humor, satire, and parody. For example, representative jokes from each genre are collected and trained by the generation AI. The humor generation unit also provides humor genres that the user can select, and the generation AI generates appropriate jokes based on the selection. For example, if the user selects black humor, the generation AI generates jokes specific to that genre. To generate humor in different genres, the humor generation unit also combines multiple humor styles to create new jokes. For example, the generation AI generates jokes that combine satire and parody. This allows the generation AI to generate humor in different genres and meet the diverse needs of users.

[0063] The humor generation unit can use the emotion estimation function to generate humor that corresponds to the user's emotional state. For example, the humor generation unit uses the emotion estimation function to analyze the user's facial expressions and voice to estimate their current emotional state. For example, the humor generation unit analyzes the user's emotions in real time using a camera or microphone. The humor generation unit also uses a generation AI to generate appropriate humor according to the user's emotional state. For example, if the user is sad, the humor generation unit generates a joke that will brighten the mood. The humor generation unit also uses the emotion estimation data to continuously monitor the user's emotional state and provide humor at an appropriate time. For example, the humor generation unit provides a joke that will help the user relax when they are feeling stressed. This allows the user's mood to be improved by generating humor that corresponds to the user's emotional state.

[0064] The providing unit can provide humor in any of the following formats: text, audio, or video. For example, the providing unit provides jokes generated by the generation AI as audio using speech synthesis technology. For example, a function is added to play generated jokes in a natural voice. The providing unit also provides jokes generated by the generation AI as animations or videos. For example, an animation matching the content of the joke is automatically generated to provide visual entertainment to the user. The providing unit also provides humor in a multimedia format that combines text, audio, and video. For example, the text of the joke is displayed while simultaneously playing audio and streaming video. This allows the generated humor to be provided in a variety of formats, making it possible to provide humor that suits the user's usage scenario.

[0065] The humor generation unit can generate humor appropriate for different cultures and languages. For example, the humor generation unit learns a dataset for the generation AI to generate jokes appropriate for different languages ​​and cultures. For example, it collects representative jokes from each country and trains the generation AI. The humor generation unit also provides languages ​​and cultures that the user can select, and the generation AI generates appropriate jokes based on that selection. For example, if the user selects English, the generation AI generates English-language jokes. To accommodate different cultures and languages, the humor generation unit uses a multilingual humor generation algorithm for the generation AI. For example, the same joke is generated in multiple languages, taking cultural nuances into account. This allows the generation AI to generate humor appropriate for different cultures and languages, thereby catering to an international audience.

[0066] The humor generation unit can use the emotion estimation function to provide humor that corresponds to the user's emotional state in real time. For example, the humor generation unit uses the emotion estimation function to analyze the user's current situation and emotional state in real time. For example, if the user is nervous, it provides a joke that will help them relax. In addition, the humor generation unit allows the generation AI to generate appropriate humor depending on the user's situation. For example, if the user is in a meeting, it provides a light ice-breaker joke. In addition, the humor generation unit allows the generation AI to continuously monitor the user's situation based on the emotion estimation data and provide humor at an appropriate time. For example, it provides a joke that will help the user relax when they are feeling stressed. In this way, humor that corresponds to the user's emotional state can be provided in real time, providing laughter that suits the situation.

[0067] The prompt analysis unit can adjust the tone and style of the humor to be generated according to the content of the prompt. For example, the prompt analysis unit causes the generation AI to adjust the tone and style of the humor based on the user's input prompt. For example, in response to the prompt, "Please tell me some light-hearted jokes," the generation AI generates light-hearted jokes. The prompt analysis unit also causes the generation AI to change the style of the humor according to the content of the prompt. For example, in response to the prompt, "Please tell me some black jokes," the generation AI generates black jokes. In addition, the prompt analysis unit also causes the generation AI to analyze the content of the prompt and generate appropriate humor to meet the user's expectations. For example, in response to the prompt, "Please tell me some satirical jokes," the generation AI generates satirical jokes. In this way, the user's expectations can be met by adjusting the tone and style of the humor according to the content of the prompt.

[0068] The prompt analysis unit uses the emotion estimation function to analyze the user's emotion when entering a prompt and can generate humor that matches that emotion. The prompt analysis unit, for example, uses the emotion estimation function to analyze the user's emotion when entering a prompt. For example, if the user is feeling stressed, it generates a joke that will help the user relax. The prompt analysis unit also allows the generation AI to generate appropriate humor according to the user's emotional state. For example, if the user is sad, it generates a joke that will brighten the mood. The prompt analysis unit also allows the generation AI to continuously monitor the user's emotional state based on the emotion estimation data and provide humor at an appropriate time. For example, it provides a joke that will help the user relax when they are nervous. In this way, the user's emotion when entering a prompt is analyzed and humor that matches that emotion is generated, making it possible to provide humor that matches the user's emotion.

[0069] The prompt analysis unit automatically suggests related questions in response to prompts entered by the user, thereby supporting more specific humor generation. For example, the prompt analysis unit allows the generation AI to automatically suggest related questions in response to a prompt entered by the user. For example, in response to the prompt, "Please tell me some jokes that can be used in sales talks," the prompt analysis unit asks, "What kind of products do you plan to introduce?" The prompt analysis unit also allows the generation AI to suggest questions to support more specific humor generation based on the user's prompt. For example, in response to the prompt, "Please tell me some jokes that can be used in conversations with friends," the prompt analysis unit asks, "What topics do you talk about?" The prompt analysis unit also allows the generation AI to suggest related questions in response to prompts entered by the user, thereby supporting more specific humor generation. For example, in response to the prompt, "Please tell me some jokes that can be used to relax when I'm feeling stressed," the prompt analysis unit asks, "In what situations do you feel stressed?" This allows the generation AI to automatically suggest related questions in response to prompts entered by the user, thereby supporting more specific humor generation.

[0070] The prompt analysis unit provides humor categories that the user can select when entering a prompt, thereby increasing the variety of humor to be generated. For example, the prompt analysis unit provides humor categories that the generation AI can select when the user enters a prompt. For example, it displays categories such as "black jokes," "sarcastic jokes," and "parodies." The prompt analysis unit also provides humor categories that the user can select when entering a prompt, and the generation AI generates appropriate jokes based on the selection. For example, if the user selects "light jokes," the generation AI generates jokes with a light tone. The prompt analysis unit also provides humor categories that the generation AI can select when entering a prompt, thereby increasing the variety of humor to be generated. For example, if the user selects "jokes that can be used in conversations with friends," the generation AI generates casual jokes. In this way, by providing humor categories that the user can select when entering a prompt, the variety of humor to be generated can be increased.

[0071] The prompt analysis unit uses the emotion estimation function to analyze the user's emotion when entering a prompt in real time and can suggest humor that matches that emotion. The prompt analysis unit, for example, uses the emotion estimation function to analyze the user's emotion when entering a prompt in real time. For example, if the user is nervous, it suggests a joke that will help them relax. The prompt analysis unit also allows the generation AI to suggest appropriate humor based on the user's emotional state. For example, if the user is sad, it suggests a joke that will brighten their mood. The prompt analysis unit also allows the generation AI to continuously monitor the user's emotional state based on the emotion estimation data and suggest humor at the appropriate time. For example, it suggests a joke that will help them relax when they are feeling stressed. In this way, the user's emotion when entering a prompt can be analyzed in real time and humor that matches that emotion can be provided.

[0072] The provision unit can insert humor at the optimal timing depending on the content of a sales talk or presentation. For example, the provision unit analyzes the script of a sales talk or presentation, and the generation AI inserts humor at the optimal timing. For example, inserting an ice-breaker joke before a product introduction. The provision unit also analyzes the slides and materials of the presentation, and the generation AI inserts humor at the appropriate timing. For example, inserting a light-hearted joke before an important point. The provision unit also monitors the progress of the sales talk or presentation in real time, and the generation AI provides humor at the optimal timing. For example, inserting a joke while watching the audience's reaction. This makes it possible to attract the audience's attention by inserting humor at the optimal timing depending on the content of the sales talk or presentation.

[0073] The providing unit can provide a function that automatically incorporates generated humor into presentation slides and materials. For example, the providing unit integrates the generative AI into a presentation slide creation tool to provide a function that automatically incorporates humor into slides. For example, it automatically generates jokes that match the content of the slides. The providing unit also provides a function that automatically inserts humor generated by the generative AI into presentation materials. For example, it inserts jokes appropriate for each section of the materials. The providing unit also analyzes presentation slides and materials and develops a system in which the generative AI automatically incorporates appropriate humor. For example, it inserts an ice-breaker joke before an important point. This allows the quality of presentations to be improved by automatically incorporating generated humor into presentation slides and materials.

[0074] The presentation unit can use the emotion estimation function to analyze audience reactions in real time and adjust the timing and content of the next humor. For example, the presentation unit uses the emotion estimation function to analyze the audience's facial expressions and voice in real time and monitor their reactions. For example, it analyzes the audience's emotions using a camera or microphone. The presentation unit also has the generation AI adjust the timing and content of the next humor based on the audience's reactions. For example, if the audience is not laughing, it changes the next joke. The presentation unit also has the generation AI continuously monitor the audience's reactions based on the emotion estimation data and provide humor at the appropriate time. For example, it provides a joke that will refresh the audience when they are tired. This allows the effectiveness of the presentation to be maximized by analyzing the audience's reactions in real time and adjusting the timing and content of the next humor.

[0075] The providing unit can automatically synchronize the humor generated by the generation AI with devices used by salespeople and presenters. The providing unit automatically synchronizes the humor generated by the generation AI with, for example, smartphones and tablets used by salespeople and presenters. For example, jokes are displayed in real time during a presentation. The providing unit also develops a system that automatically synchronizes the humor generated by the generation AI with devices used by salespeople and presenters. For example, it inserts jokes in conjunction with a slide creation tool. The providing unit also provides a function that automatically synchronizes the humor generated by the generation AI with devices used by salespeople and presenters. For example, it displays jokes as the presentation progresses. This allows the efficiency of presentation preparation to be improved by automatically synchronizing the humor generated with devices used by salespeople and presenters.

[0076] The humor generation unit can generate humor appropriate for different industries and business situations. For example, the humor generation unit learns a dataset that the generation AI uses to generate humor appropriate for different industries and business situations. For example, it collects representative jokes from each industry and trains the generation AI. The humor generation unit also provides industries and business situations that the user can select, and the generation AI generates appropriate jokes based on that selection. For example, if the user selects the IT industry, it generates jokes specialized for the IT industry. In addition, to accommodate different industries and business situations, the humor generation unit allows the generation AI to combine various humor styles to create new jokes. For example, it generates humor that combines jokes from the medical and education industries. This allows the generation AI to generate humor appropriate for different industries and business situations, making it usable for a wide range of applications.

[0077] The providing unit can use the emotion estimation function to analyze the emotional state of the audience in real time and provide optimal humor. For example, the providing unit uses the emotion estimation function to analyze the audience's facial expressions and voices in real time and monitor their emotional state. For example, the providing unit analyzes the audience's emotions using a camera or microphone. The providing unit also has the generation AI provide appropriate humor according to the audience's emotional state. For example, if the audience is tired, it provides a refreshing joke. The providing unit also has the generation AI continuously monitor the audience's emotional state based on the emotion estimation data and provide humor at the appropriate time. For example, it provides a joke that will relax the audience when they are nervous. In this way, the effectiveness of the presentation can be maximized by analyzing the audience's emotional state in real time and providing optimal humor.

[0078] The providing unit can provide humor at the optimal timing according to the user's daily schedule and activities. The providing unit, for example, analyzes the user's daily schedule, and the generation AI provides humor at the optimal timing. For example, it provides a joke that will refresh the user during their morning commute. The providing unit also provides humor at the appropriate timing based on the user's activity data. For example, it provides a joke that will help the user relax between work. The providing unit also continuously monitors the user's daily schedule and activities, and the generation AI provides humor at the optimal timing. For example, it provides a joke that will help the user relax when they are feeling stressed. In this way, providing humor at the optimal timing according to the user's daily schedule and activities makes daily life more enjoyable.

[0079] The providing unit can analyze the user's past laughter history and provide individually customized humor. The providing unit, for example, analyzes the user's past laughter history, and the generation AI provides individually customized humor. For example, the providing unit learns the patterns of jokes that the user has liked in the past. The providing unit also allows the generation AI to provide appropriate humor based on the user's laughter history. For example, the generation AI generates new jokes based on the style of jokes that the user has laughed at in the past. The providing unit also continuously monitors the user's past laughter history, and the generation AI provides individually customized humor. For example, if the user likes jokes of a specific genre, the generation AI provides jokes specialized for that genre. In this way, by analyzing the user's past laughter history and providing individually customized humor, it is possible to provide humor that is more familiar to the user.

[0080] The providing unit can use the emotion estimation function to analyze the user's emotional state and provide humor to relieve stress and fatigue. For example, the providing unit uses the emotion estimation function to analyze the user's facial expressions and voice to estimate their current emotional state. For example, the providing unit analyzes the user's emotions in real time using a camera or microphone. The providing unit also has the generation AI provide appropriate humor according to the user's emotional state. For example, if the user is feeling stressed, it provides a relaxing joke. The providing unit also has the generation AI continuously monitor the user's emotional state based on the emotion estimation data and provide humor at an appropriate time. For example, it provides a refreshing joke when the user is tired. In this way, the system can support the user's physical and mental health by analyzing the user's emotional state and providing humor to relieve stress and fatigue.

[0081] The providing unit can work in conjunction with smart home devices to provide humor within the home. The providing unit works in conjunction with, for example, a smart speaker or smart display, and the generation AI provides humor within the home. For example, it plays a joke as an alarm in the morning. The providing unit also works in conjunction with smart home devices, and the generation AI provides humor according to the situation within the home. For example, it provides a joke that will help the family relax when they get together. The providing unit also develops a system that enables the generation AI to provide humor within the home through smart home devices. For example, it plays a joke when a smart light is turned on. In this way, by working in conjunction with smart home devices to provide humor within the home, it is possible to brighten the atmosphere within the home.

[0082] The humor generation unit can generate humor that matches the user's hobbies and interests. For example, the humor generation unit analyzes the user's hobbies and interests, and the generation AI generates humor that matches them. For example, if the user likes sports, the generation AI provides jokes related to sports. The humor generation unit also provides appropriate humor based on the user's hobbies and interests. For example, if the user likes movies, the generation AI provides jokes related to movies. The humor generation unit also continuously monitors the user's hobbies and interests, and the generation AI provides humor that matches them. For example, if the user takes up a new hobby, the generation AI provides jokes related to that hobby. This allows for humor that matches the user's hobbies and interests to be generated, making everyday life more enjoyable.

[0083] The providing unit can use the emotion estimation function to analyze the user's emotional state in real time and provide optimal humor. For example, the providing unit uses the emotion estimation function to analyze the user's facial expressions and voice in real time and monitor the emotional state. For example, the providing unit analyzes the user's emotions using a camera or microphone. The providing unit also has the generation AI provide appropriate humor according to the user's emotional state. For example, if the user is feeling stressed, it provides a relaxing joke. The providing unit also has the generation AI continuously monitor the user's emotional state based on the emotion estimation data and provide humor at an appropriate time. For example, it provides a refreshing joke when the user is tired. In this way, the user's emotional state can be analyzed in real time and optimal humor can be provided to improve the user's mood.

[0084] The humor generation unit can analyze a user's preferences and past usage history to provide individually customized humor. The humor generation unit, for example, analyzes a user's past usage history, and the generation AI provides individually customized humor. For example, the humor generation unit learns the patterns of jokes that the user has liked in the past. The humor generation unit also provides appropriate humor based on the user's preferences, and the generation AI provides jokes specific to that genre. The humor generation unit also continuously monitors the user's past usage history, and the generation AI provides individually customized humor. For example, if a user likes jokes of a specific genre, the generation AI provides jokes specific to that genre. In this way, by analyzing a user's preferences and past usage history and providing individually customized humor, it is possible to provide humor that is more familiar to the user.

[0085] The humor generation unit can continuously improve the quality of the humor generated based on user feedback. For example, the humor generation unit collects user ratings (e.g., star ratings and comments) on jokes, and the generation AI improves the next joke generation based on that feedback. For example, it avoids patterns in jokes that have received low ratings. The humor generation unit also analyzes user feedback and continuously improves the quality of the humor generated by the generation AI. For example, it learns the style of jokes that users prefer and generates new jokes based on that. The humor generation unit also develops a system that continuously improves the quality of the humor generated by the generation AI based on user feedback. For example, it analyzes user ratings in real time and reflects them in the generation of the next joke. In this way, the quality of the humor generated based on user feedback can be continuously improved, thereby providing higher quality humor.

[0086] The providing unit can use the emotion estimation function to provide customized humor according to the user's emotional state. For example, the providing unit uses the emotion estimation function to analyze the user's facial expressions and voice to estimate their current emotional state. For example, the providing unit analyzes the user's emotions in real time using a camera or microphone. The providing unit also causes the generation AI to provide appropriate humor according to the user's emotional state. For example, if the user is feeling stressed, the generation AI provides a relaxing joke. The providing unit also causes the generation AI to continuously monitor the user's emotional state based on the emotion estimation data and provide humor at an appropriate time. For example, the generation AI provides a refreshing joke when the user is tired. This makes it possible to improve the user's mood by providing customized humor according to the user's emotional state.

[0087] The providing unit can provide a function that allows a user to share customized humor with other users. The providing unit provides, for example, a function that allows a user to share customized jokes with other users. For example, jokes created by the user are shared on a social networking site or a messaging app. The providing unit also develops a platform for sharing customized humor. For example, a user posts their own jokes, and other users rate and comment on them. The providing unit also provides a function that allows a user to share customized humor with other users. For example, a joke created by a user is shared, allowing other users to use it. In this way, by providing a function that allows a user to share customized humor with other users, it is possible to spread the enjoyment of humor.

[0088] The providing unit can make the customized humor available on different devices and platforms. For example, the providing unit develops a system that allows users to use customized humor on different devices and platforms. For example, the system allows the same jokes to be used on smartphones, tablets, PCs, etc. The providing unit also stores the customized humor on the cloud and makes it accessible on different devices and platforms. For example, the system allows users to access their own jokes from any device. The providing unit also provides an API that allows the customized humor to be used on different devices and platforms. For example, the system allows other applications and services to use the customized jokes. This improves user convenience by allowing the customized humor to be used on different devices and platforms.

[0089] The providing unit can use the emotion estimation function to analyze the user's emotional state in real time and provide optimal customization. For example, the providing unit uses the emotion estimation function to analyze the user's facial expressions and voice in real time to monitor the emotional state. For example, the providing unit analyzes the user's emotions using a camera or microphone. The providing unit also has the generation AI provide appropriate customization according to the user's emotional state. For example, if the user is feeling stressed, the generation AI provides a relaxing joke. The providing unit also has the generation AI continuously monitor the user's emotional state based on the emotion estimation data and provide customized humor at an appropriate time. For example, when the user is tired, the generation AI provides a refreshing joke. In this way, the user's emotional state can be analyzed in real time and optimal customization can be provided to improve the user's mood.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The AI ​​Comedy Machine can also estimate the user's emotional state and generate humor based on that emotion. For example, if the user is feeling stressed, it can generate a joke that will relax them. Or, if the user is sad, it can generate a joke that will lighten their mood. Furthermore, it can continuously monitor the user's emotional state and provide humor at the appropriate time. This allows it to improve the user's mood by providing humor that matches the user's emotions.

[0092] The AI ​​Comedy Machine can also analyze a user's past laughing history and provide individually customized humor. For example, it can learn the patterns of jokes that the user liked in the past and generate new jokes based on that. Also, if a user likes jokes of a specific genre, it can provide jokes specialized for that genre. In this way, by analyzing a user's past laughing history and providing individually customized humor, it can provide humor that is more familiar to the user.

[0093] The AI ​​comedy machine can also be equipped with the ability to generate humor appropriate for different cultures and languages. For example, it can collect representative jokes from various countries and train the generation AI to learn them. It can also provide users with a choice of language and culture, generating appropriate jokes based on that selection. It can also generate the same joke in multiple languages, taking cultural nuances into account. This allows it to cater to an international audience by generating humor appropriate for different cultures and languages.

[0094] The AI ​​Comedy Machine can also be equipped with the ability to generate humor tailored to the user's hobbies and interests. For example, if the user likes sports, it can provide jokes related to sports. If the user likes movies, it can provide jokes related to movies. It can also continuously monitor the user's hobbies and interests and provide jokes related to new hobbies. This can make everyday life more enjoyable by generating humor tailored to the user's hobbies and interests.

[0095] The AI ​​Comedy Machine can also use its emotion estimation function to provide humor in real time that matches the user's emotional state. For example, if the user is nervous, it can provide a joke to relax them. Or, if the user is in a meeting, it can provide a light, ice-breaking joke. It can also continuously monitor the user's situation and provide humor at the appropriate time. This allows it to provide humor in real time that matches the user's emotional state, providing laughter that suits the situation.

[0096] The AI ​​Comedy Machine can also have a function that allows users to share their customized humor with other users. For example, users can share jokes they create on social media or messaging apps. A platform for sharing customized humor can also be developed, allowing users to post their own jokes and other users to rate and comment on them. Furthermore, it is possible for users to share their jokes and make them available to other users. This allows users to share their customized humor with other users, thereby broadening the enjoyment of humor.

[0097] The AI ​​Comedy Machine can also use its emotion estimation function to analyze the user's emotional state in real time and provide optimal customization. For example, if the user is feeling stressed, it can provide relaxing jokes. Or, if the user is tired, it can provide refreshing jokes. Furthermore, it can continuously monitor the user's emotional state and provide customized humor at the appropriate time. This allows the AI ​​Comedy Machine to analyze the user's emotional state in real time and provide optimal customization to improve the user's mood.

[0098] The AI ​​comedy machine can also be equipped with the ability to generate humor tailored to different industries and business situations. For example, it can collect representative jokes from each industry and train the generation AI to learn from them. It can also provide users with industries and business situations to choose from, generating appropriate jokes based on their selection. Furthermore, to accommodate different industries and business situations, the generation AI can combine various humor styles to create new jokes. This allows it to be used for a wide range of purposes by generating humor tailored to different industries and business situations.

[0099] The AI ​​Comedy Machine can also use its emotion estimation function to analyze the user's emotional state and provide humor to relieve stress and fatigue. For example, if the user is feeling stressed, it can provide relaxing jokes. Alternatively, if the user is tired, it can provide refreshing jokes. It can also continuously monitor the user's emotional state and provide humor at the appropriate time. This allows it to analyze the user's emotional state and provide humor to relieve stress and fatigue, thereby supporting the user's physical and mental health.

[0100] The AI ​​Comedy Machine can also be equipped with the ability to link with smart home devices and provide humor within the home. For example, by linking with a smart speaker or smart display, the generation AI can provide humor within the home. It can also provide humor according to the situation within the home. For example, it can provide relaxing jokes when the family gets together. Furthermore, it is possible to develop a system that allows the generation AI to provide humor within the home through smart home devices. This allows it to link with smart home devices and provide humor within the home, brightening the atmosphere within the home.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The prompt analysis unit analyzes the prompt entered by the user. For example, the prompt analysis unit uses natural language processing technology to understand the intent and background of the prompt, and uses keyword extraction technology to extract important information from the prompt. Specifically, it analyzes the prompt entered by the user, "Please tell me some jokes that can be used in sales talks," and extracts information needed to generate jokes suitable for sales talks. Step 2: The humor generator generates humor based on the prompt analyzed by the prompt analyzer. For example, the humor generator can generate jokes using text generation AI (e.g., GPT-3) and can also generate humor that includes not only text but also audio and video using multimodal generation AI. Specifically, it generates icebreaker jokes that can be used in sales talks. Step 3: The providing unit provides the humor generated by the humor generating unit. For example, the providing unit may display the generated joke in text format, play it as audio using speech synthesis technology, or provide it as animation or video. Specifically, the generated joke is displayed on the screen of a smartphone or tablet and played as audio.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0116] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0131] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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).

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0147] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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).

[0156] 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.

[0157] 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."

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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]

[0170] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. An AI comedy machine that uses generative AI to generate humor or laughter, a prompt analysis unit that analyzes a prompt input by a user; a humor generator that generates humor based on the prompt analyzed by the prompt analyzer; a providing unit that provides the humor generated by the humor generating unit. A system characterized by:

2. The prompt analysis unit Analyze the prompt and understand its intent and context 2. The system of claim 1.

3. The providing unit Provide the humor in text, audio, or video format 2. The system of claim 1.

4. The humor generation unit Generate humor that is appropriate for different cultures and languages 2. The system of claim 1.

5. The prompt analysis unit Analyzing the user's emotions when inputting a prompt and generating humor that matches those emotions 2. The system of claim 1.

6. The providing unit Analyze audience reactions in real time to adjust the timing and content of the next humor 2. The system of claim 1.

7. The providing unit Analyzing the emotional state of the user and providing the humor to relieve stress or fatigue 2. The system of claim 1.

8. The providing unit Providing the humor customized according to the emotional state of the user 2. The system of claim 1.

Images