System

Abstract

An object of a system according to an embodiment is to propose an optimal hairstyle based on information of a user.SOLUTION: A system according to an embodiment comprises a user-information collecting section, a hairstyle analyzing section, and a hairstyle suggesting section. The user information collection unit collects information on the shape of the face, the hair quality, and the lifestyle of the user. The hairstyle analyzing section analyzes the optimum hairstyle on the basis of the user information collected by the user information collecting section. The hairstyle proposing section proposes an optimum hairstyle to the user on the basis of the result analyzed by the hairstyle analyzing 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 technologies do not adequately collect and analyze information to suggest optimal hairstyles to users, and there is room for improvement.

[0005] The system according to the embodiment aims to propose an optimal hairstyle based on user information. [Means for solving the problem]

[0006] The system according to the embodiment includes a user information collection unit, a hairstyle analysis unit, and a hairstyle suggestion unit. The user information collection unit collects information on the user's face shape, hair type, and lifestyle. The hairstyle analysis unit analyzes an optimal hairstyle based on the user information collected by the user information collection unit. The hairstyle suggestion unit suggests an optimal hairstyle for the user based on the results of the analysis by the hairstyle analysis unit. [Effects of the Invention]

[0007] The system according to the embodiment can suggest the most suitable hairstyle based on the user's information. [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 hairstyle suggestion system according to an embodiment of the present invention uses generative AI to analyze the optimal hairstyle for each user and provide advice. This allows the hairstyle suggestion system to suggest the optimal hairstyle based on information such as the user's face shape, hair type, and lifestyle.

[0029] A hairstyle suggestion system according to an embodiment includes a user information collection unit, a hairstyle analysis unit, and a hairstyle suggestion unit. The user information collection unit collects information on the user's face shape, hair type, and lifestyle. For example, the user information collection unit collects face shape (round face, oval face, square face, etc.) input by the user. The user information collection unit can also collect hair type (straight hair, wavy hair, curly hair, etc.). The user information collection unit can also collect the user's lifestyle (job type, hobbies, daily activity level, etc.). The hairstyle analysis unit analyzes the optimal hairstyle based on the user information collected by the user information collection unit. For example, the hairstyle analysis unit can suggest a hairstyle that makes a user with a round face appear slimmer. The hairstyle analysis unit can also suggest a style that makes the most of the user's hair type to a user with straight hair. The hairstyle analysis unit can also suggest styles that are easy to maintain or styles suitable for formal occasions, depending on the user's lifestyle. The hairstyle suggestion unit suggests the optimal hairstyle for the user based on the results of the analysis by the hairstyle analysis unit. For example, the hairstyle suggestion unit may provide specific advice such as, "A style with swept bangs suits your face shape," or "A layered cut is suitable for your hair type." The hairstyle suggestion unit may also provide an image of the suggested hairstyle and a styling method. This allows the hairstyle suggestion system according to the embodiment to suggest an optimal hairstyle based on information such as the user's face shape, hair type, and lifestyle.

[0030] The user information collection unit can collect the user's past hairstyle history and analyze trends and changes in the hairstyle history. For example, the user information collection unit provides a function that allows the user to upload photos and records of hairstyles that they have tried in the past. This allows the past style history to be saved in a database. The user information collection unit also analyzes the past hairstyle history to understand changes in the user's preferences and trends. For example, it can analyze changes in styles with each season or trends in styles for specific events. The user information collection unit can also suggest the next style to try based on the user's past hairstyle history. For example, it can make new suggestions based on styles that were popular in the past. This allows trends and changes to be analyzed based on the user's past hairstyle history.

[0031] The user information collection unit can measure the user's health condition with sensors and collect that information. For example, the user information collection unit can install sensors in the hairbrush or shampoo used by the user to measure the health condition of the hair. For example, it can analyze the moisture content and damage level of the hair in real time. The user information collection unit can also use a wearable device to monitor the user's stress level and sleep state and collect that data. For example, it can analyze heart rate and electrodermal activity. The user information collection unit can also suggest optimal hair care products and styles for the user based on the health condition data. For example, it can recommend products with high moisturizing effects to users with highly damaged hair. In this way, the user's health condition can be measured with sensors and that information can be collected.

[0032] The user information collection unit collects the user's fashion style and clothing preferences, allowing it to coordinate with the user's hairstyle. For example, the user information collection unit uploads photos of the clothes the user wears on a daily basis and collects the data. For example, it can categorize styles into casual, formal, sporty, etc. The user information collection unit also suggests hairstyles based on the user's fashion style. For example, it can suggest relaxed hairstyles for casual clothing and elegant hairstyles for formal clothing. The user information collection unit also uses a generation AI to automatically suggest outfits to coordinate the user's fashion style and hairstyle. For example, it can provide a complete outfit for a specific event. This allows it to collect the user's fashion style and clothing preferences and coordinate with the user's hairstyle.

[0033] The user information collection unit can collect opinions of the user's friends or family and provide advice from a social perspective. The user information collection unit, for example, provides a function that allows the user to request opinions on hairstyles from friends and family. For example, the proposed styles can be shared and feedback can be collected. The user information collection unit also suggests the most suitable hairstyle for the user based on the opinions of friends and family. For example, it can aggregate multiple opinions and prioritize the most popular style. The user information collection unit also analyzes feedback from friends and family to select the most suitable style for the user in order to provide advice from a social perspective. For example, it can recommend a style that has a large number of positive comments. This makes it possible to collect opinions from the user's friends and family and provide advice from a social perspective.

[0034] The hairstyle analysis unit can perform an analysis that takes into account not only the user's face shape and hair type, but also bone structure and skin color. For example, the hairstyle analysis unit can build a system that analyzes the user's face shape and hair type, as well as bone structure and skin color. For example, it can propose an optimal hairstyle based on bone structure features and skin tone. The hairstyle analysis unit also proposes hairstyles that take bone structure and skin color into consideration. For example, it can propose a style that accentuates bone structure or a hair color that matches skin color. The hairstyle analysis unit can also develop a system that comprehensively analyzes the user's face shape, hair type, bone structure, and skin color and proposes an optimal hairstyle. For example, it can weight each element and perform an overall evaluation. This makes it possible to perform an analysis that takes into account not only the user's face shape and hair type, but also bone structure and skin color.

[0035] The hairstyle analysis unit can suggest hairstyles according to the season and weather based on the user's lifestyle. The hairstyle analysis unit, for example, collects lifestyle data of the user and suggests hairstyles according to the season and weather. For example, it can suggest cool styles in summer and warm styles in winter. The hairstyle analysis unit also collects weather data in real time and suggests hairstyles based on that information. For example, it can suggest styles that are resistant to humidity on rainy days. The hairstyle analysis unit also builds a system that suggests hairstyles taking into account the user's lifestyle, season, and weather. For example, it can suggest styles that are easy to maintain to a user who spends a lot of time outdoors. This makes it possible to suggest hairstyles according to the season and weather based on the user's lifestyle.

[0036] The hairstyle analysis unit can suggest an appropriate style by taking into consideration the user's occupation and social status. The hairstyle analysis unit, for example, suggests a hairstyle by taking into consideration the user's occupation and social status. For example, it can suggest a formal style to a business person and a unique style to a user in a creative occupation. The hairstyle analysis unit also builds a system that narrows down hairstyle options based on occupation and social status. For example, it can suggest styles that match the dress code for each occupation. The hairstyle analysis unit also analyzes the user's occupation and social status and suggests the optimal hairstyle based on that information. For example, it can reflect style trends according to occupation. This makes it possible to suggest an appropriate style by taking into consideration the user's occupation and social status.

[0037] The hairstyle analysis unit can suggest a style that reflects the user's hobbies and interests and brings out their individuality. The hairstyle analysis unit, for example, collects the user's hobbies and interests and suggests a hairstyle based on that information. For example, it can suggest an active style to a user who likes sports, and a creative style to a user who likes art. The hairstyle analysis unit also builds a system that suggests hairstyles that bring out their individuality based on the user's hobbies and interests. For example, it can suggest styles and colors related to a specific hobby. The hairstyle analysis unit also suggests hairstyles that reflect the user's hobbies and interests. For example, it can suggest an artistic style to a user who likes music. In this way, it is possible to suggest a style that reflects the user's hobbies and interests and brings out their individuality.

[0038] The hairstyle suggestion unit can collect user feedback on the proposed hairstyle and reflect it in the next suggestion. The hairstyle suggestion unit, for example, provides a function for collecting user feedback on the proposed hairstyle. For example, an interface can be provided that allows the user to input ratings and comments on the style. The hairstyle suggestion unit also builds a system that analyzes user feedback and reflects it in the next suggestion. For example, it can preferentially suggest styles that receive a lot of positive feedback. The hairstyle suggestion unit also accumulates feedback data and analyzes user preferences and trends. This enables more accurate hairstyle suggestions. This allows user feedback on the proposed hairstyle to be collected and reflected in the next suggestion.

[0039] The hairstyle suggestion unit can provide a video that provides detailed instructions on how to maintain and style the proposed hairstyle. For example, the hairstyle suggestion unit can provide a video that provides detailed instructions on how to maintain and style the proposed hairstyle. For example, the video can introduce how to set the hairstyle and the products to use. The hairstyle suggestion unit can also provide a step-by-step video guide so that the user can recreate the proposed hairstyle at home. For example, the video can explain how to use a hair iron and blow-drying techniques. The hairstyle suggestion unit can also provide a video that explains how to use hair care products and tools that match the proposed hairstyle. For example, the video can introduce how to use a specific shampoo and conditioner. This makes it possible to provide a video that provides detailed instructions on how to maintain and style the proposed hairstyle.

[0040] The hairstyle suggestion unit can also suggest makeup and accessories that match the proposed hairstyle. The hairstyle suggestion unit, for example, suggests makeup that matches the proposed hairstyle. For example, it can suggest eye makeup and lip color that matches a specific hairstyle. The hairstyle suggestion unit also suggests accessories that match the hairstyle. For example, it can suggest hairpins and earrings that match a specific hairstyle. The hairstyle suggestion unit also builds a system that suggests a total coordination of hairstyle, makeup, and accessories. For example, it can provide a total coordination for a specific event. This allows it to also suggest makeup and accessories that match the proposed hairstyle.

[0041] The hairstyle suggestion unit can display and refer to other users' ratings and comments on the proposed hairstyle. The hairstyle suggestion unit, for example, provides a function for displaying other users' ratings and comments on the proposed hairstyle. For example, an interface can be provided that allows users to input ratings and comments on the style. The hairstyle suggestion unit also builds a system that narrows down the options for proposed hairstyles based on other users' ratings and comments. For example, it can preferentially suggest styles that have many positive ratings. The hairstyle suggestion unit also analyzes feedback from other users and suggests the optimal hairstyle for the user. For example, it can recommend styles that have high ratings. This makes it possible to display and refer to other users' ratings and comments on the proposed hairstyle.

[0042] The hairstyle simulation unit displays the simulation results as a 3D model, providing a more realistic image. For example, the hairstyle simulation unit generates a 3D model based on a user's photograph and realistically simulates a proposed hairstyle. For example, it can create a 3D model that reflects the user's face shape and hair type. The hairstyle simulation unit also uses the 3D model to display the proposed hairstyle from multiple angles. For example, it can provide views from the front, side, and back. The hairstyle simulation unit also provides an interface that allows the user to manipulate the 3D model in real time, allowing the user to freely change the viewpoint. For example, it can add a function to rotate the model using a mouse or touch operation. This allows the simulation results to be displayed as a 3D model, providing a more realistic image.

[0043] The hairstyle simulation unit can display the simulation results from multiple angles, allowing the user to check the overall balance. The hairstyle simulation unit, for example, provides a function for displaying the simulation results from multiple angles. For example, it can provide views from the front, side, and back, allowing the user to check the overall balance. The hairstyle simulation unit also provides an interface that allows the user to freely manipulate the simulation results. For example, it can add a function for rotating the model by mouse or touch operation. The hairstyle simulation unit also allows the user to select the optimal hairstyle based on views from multiple angles. For example, it can display the views from each angle side by side to make it easier to compare them. This allows the simulation results to be displayed from multiple angles, allowing the user to check the overall balance.

[0044] The hairstyle simulation unit can provide a function for sharing the simulation results on social media and collecting opinions from friends and family. The hairstyle simulation unit, for example, provides a function for sharing the simulation results on social media. For example, a button for posting the simulation results on platforms such as Facebook and Instagram can be provided. The hairstyle simulation unit also provides a comment function for collecting opinions from friends and family. For example, feedback on the simulation results can be received on social media. The hairstyle simulation unit can also analyze ratings and comments on the simulation results shared on social media and suggest the most suitable hairstyle for the user. For example, it can prioritize suggestions for styles with a lot of positive feedback. This makes it possible to provide a function for sharing the simulation results on social media and collecting opinions from friends and family.

[0045] The hairstyle simulation unit can provide a function for saving simulation results and comparing them with past simulations. The hairstyle simulation unit, for example, provides a function for saving simulation results. For example, it can enable a user to save past simulation results and review them later. The hairstyle simulation unit also provides an interface for comparing saved simulation results. For example, it can display multiple simulation results side by side so that differences can be confirmed. The hairstyle simulation unit also builds a system for analyzing user preferences and trends based on past simulation results. For example, it can suggest optimal hairstyles based on past data. This makes it possible to provide a function for saving simulation results and comparing them with past simulations.

[0046] The hair care advice unit can periodically monitor the health condition of the user's hair and provide appropriate hair care advice. For example, the hair care advice unit uses a hairbrush or shampoo equipped with a sensor to periodically monitor the health condition of the user's hair. For example, it can measure the moisture content and damage level of the hair and collect the data. The hair care advice unit can also analyze the periodically collected hair health data and provide appropriate hair care advice. For example, if the hair is highly damaged, it can recommend a product with high moisturizing effects. The hair care advice unit can also monitor the health condition of the user's hair and build a system that provides hair care advice in real time based on the data. For example, the advice content can be updated every time the hair condition changes. This allows the health condition of the user's hair to be periodically monitored and appropriate hair care advice to be provided.

[0047] The hair care advice unit can explain the ingredients and effects of hair care products in detail and recommend the most suitable product to the user. For example, the hair care advice unit can build a database that explains the ingredients and effects of hair care products in detail and recommend the most suitable product to the user. For example, it can explain the effects and usage methods of products containing specific ingredients. The hair care advice unit can also develop a system that recommends the most suitable hair care product based on the user's hair condition and lifestyle. For example, it can recommend products with high moisturizing effects to users with severely damaged hair. The hair care advice unit can also provide videos that explain the ingredients and effects of hair care products in detail, making it easier for users to select products. For example, it can explain how to use the product and its effects through videos. This allows the ingredients and effects of hair care products to be explained in detail and the most suitable product to be recommended to the user.

[0048] The hair care advice unit can provide comprehensive hair care advice by taking into account the user's diet and lifestyle. The hair care advice unit, for example, collects information on the user's diet and lifestyle and provides comprehensive hair care advice based on that data. For example, the hair care advice unit can provide advice taking into account nutritional balance and sleep status. The hair care advice unit also builds a system that provides advice for maintaining healthy hair based on the user's diet and lifestyle. For example, it can recommend foods containing specific nutrients. The hair care advice unit also monitors the user's diet and lifestyle and provides hair care advice in real time based on that data. For example, it can adjust the advice content depending on the content of meals and the amount of exercise. This makes it possible to provide comprehensive hair care advice by taking into account the user's diet and lifestyle.

[0049] The hair care advice unit can provide appropriate hair care advice by taking the user's environment into consideration. The hair care advice unit, for example, collects information about the user's living environment and provides hair care advice based on that data. For example, it can provide advice based on the climate and water quality. The hair care advice unit also analyzes environmental data and builds a system that suggests optimal hair care products and methods to users. For example, it can suggest humidity-resistant products to users living in humid areas. The hair care advice unit also collects environmental data about the user in real time and provides hair care advice based on that data. For example, it can update the advice content every time the weather changes. This allows the hair care advice unit to provide appropriate hair care advice by taking the user's environment into consideration.

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

[0051] The hairstyle suggestion system can further include a hobby information collection unit that reflects the user's hobbies and interests. For example, if the user likes sports, a hairstyle that suits an active lifestyle can be suggested. Also, if the user likes art or music, creative styles or artistic hair colors can be suggested. Furthermore, the hobby information collection unit can also suggest styles that match events or activities related to the user's hobbies. For example, it can suggest styles that are suitable for attending a concert or art exhibition. This makes it possible to suggest unique hairstyles that reflect the user's hobbies and interests.

[0052] The hairstyle suggestion system can also be equipped with a health information collection unit that monitors the user's health condition. For example, sensors can be installed in the hairbrush or shampoo used by the user to measure the health of the hair. The system can analyze the moisture content and damage level of the hair in real time and suggest the most suitable hair care products and styles for the user. In addition, a wearable device can be used to monitor the user's stress level and sleep state, and hairstyle suggestions can be made based on that data. This makes it possible to suggest hairstyles that take the user's health condition into consideration.

[0053] The hairstyle suggestion system can further include a fashion information collection unit that reflects the user's fashion style. For example, the user can upload photos of the clothes they usually wear and collect that data. The system can categorize styles into casual, formal, sporty, etc., and suggest hairstyles based on the fashion style. For example, it can suggest relaxed hairstyles for casual clothing and elegant hairstyles for formal clothing. This makes it possible to suggest hairstyles that are consistent with the user's fashion style.

[0054] The hairstyle suggestion system may further include a social information gathering unit that collects opinions from the user's friends and family. For example, a function may be provided that allows the user to ask friends and family for their opinions on hairstyles. The suggested styles may be shared and feedback may be collected. Furthermore, the system may suggest the most suitable hairstyle for the user based on the opinions of friends and family. For example, multiple opinions may be aggregated and the most popular style may be suggested preferentially. This makes it possible to suggest hairstyles that reflect advice from a social perspective.

[0055] The hairstyle suggestion system can further include an occupational information collection unit that takes into account the user's occupation and social status. For example, it can suggest hairstyles based on the user's occupation and social status. Formal styles can be suggested for business people, and unique styles can be suggested for users in creative occupations. It can also suggest styles that match the dress code for each occupation. This makes it possible to suggest appropriate hairstyles that take into account the user's occupation and social status.

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

[0057] Step 1: The user information collection unit collects information about the user's face shape, hair type, and lifestyle. For example, the user may input information about their face shape (round, oval, square, etc.), hair type (straight, wavy, curly, etc.), and lifestyle (job, hobbies, daily activity, etc.). Step 2: The hairstyle analysis unit analyzes the optimal hairstyle based on the user information collected by the user information collection unit. For example, it suggests hairstyles that make a user with a round face appear slimmer, and suggests styles that make the most of the user's hair type for a user with straight hair. It also suggests styles that are easy to maintain or suitable for formal occasions, depending on the user's lifestyle. Step 3: The hairstyle suggestion unit suggests the optimal hairstyle for the user based on the results of the analysis by the hairstyle analysis unit. For example, it provides specific advice such as, "Your face shape will suit a style with swept bangs," or "A layered cut is suitable for your hair type." It also provides images of the suggested hairstyles and styling instructions.

[0058] (Example 2) The hairstyle suggestion system according to an embodiment of the present invention uses generative AI to analyze the optimal hairstyle for each user and provide advice. This allows the hairstyle suggestion system to suggest the optimal hairstyle based on information such as the user's face shape, hair type, and lifestyle.

[0059] A hairstyle suggestion system according to an embodiment includes a user information collection unit, a hairstyle analysis unit, and a hairstyle suggestion unit. The user information collection unit collects information on the user's face shape, hair type, and lifestyle. For example, the user information collection unit collects face shape (round face, oval face, square face, etc.) input by the user. The user information collection unit can also collect hair type (straight hair, wavy hair, curly hair, etc.). The user information collection unit can also collect the user's lifestyle (job type, hobbies, daily activity level, etc.). The hairstyle analysis unit analyzes the optimal hairstyle based on the user information collected by the user information collection unit. For example, the hairstyle analysis unit can suggest a hairstyle that makes a user with a round face appear slimmer. The hairstyle analysis unit can also suggest a style that makes the most of the user's hair type to a user with straight hair. The hairstyle analysis unit can also suggest styles that are easy to maintain or styles suitable for formal occasions, depending on the user's lifestyle. The hairstyle suggestion unit suggests the optimal hairstyle for the user based on the results of the analysis by the hairstyle analysis unit. For example, the hairstyle suggestion unit may provide specific advice such as, "A style with swept bangs suits your face shape," or "A layered cut is suitable for your hair type." The hairstyle suggestion unit may also provide an image of the suggested hairstyle and a styling method. This allows the hairstyle suggestion system according to the embodiment to suggest an optimal hairstyle based on information such as the user's face shape, hair type, and lifestyle.

[0060] The user information collecting unit can estimate the user's emotional state in real time and reflect hairstyle preferences based on the emotional state. For example, when the user inputs information, the user information collecting unit analyzes the user's emotional state in real time using a camera or microphone. For example, it analyzes facial expressions and voice tone to determine whether the user is relaxed or stressed. The user information collecting unit also estimates the user's preferred hairstyle tendency based on the emotional state. For example, it can suggest a casual style to a relaxed user and a refreshing style to a stressed user. The user information collecting unit also accumulates the user's emotional data and analyzes past emotional states and hairstyle preferences. This enables more accurate suggestions based on the user's emotional patterns. This makes it possible to reflect hairstyle preferences based on the user's emotional state.

[0061] The user information collection unit can collect the user's past hairstyle history and analyze trends and changes in the hairstyle history. For example, the user information collection unit provides a function that allows the user to upload photos and records of hairstyles that they have tried in the past. This allows the past style history to be saved in a database. The user information collection unit also analyzes the past hairstyle history to understand changes in the user's preferences and trends. For example, it can analyze changes in styles with each season or trends in styles for specific events. The user information collection unit can also suggest the next style to try based on the user's past hairstyle history. For example, it can make new suggestions based on styles that were popular in the past. This allows trends and changes to be analyzed based on the user's past hairstyle history.

[0062] The user information collection unit can measure the user's health condition with sensors and collect that information. For example, the user information collection unit can install sensors in the hairbrush or shampoo used by the user to measure the health condition of the hair. For example, it can analyze the moisture content and damage level of the hair in real time. The user information collection unit can also use a wearable device to monitor the user's stress level and sleep state and collect that data. For example, it can analyze heart rate and electrodermal activity. The user information collection unit can also suggest optimal hair care products and styles for the user based on the health condition data. For example, it can recommend products with high moisturizing effects to users with highly damaged hair. In this way, the user's health condition can be measured with sensors and that information can be collected.

[0063] The user information collection unit collects the user's fashion style and clothing preferences, allowing it to coordinate with the user's hairstyle. For example, the user information collection unit uploads photos of the clothes the user wears on a daily basis and collects the data. For example, it can categorize styles into casual, formal, sporty, etc. The user information collection unit also suggests hairstyles based on the user's fashion style. For example, it can suggest relaxed hairstyles for casual clothing and elegant hairstyles for formal clothing. The user information collection unit also uses a generation AI to automatically suggest outfits to coordinate the user's fashion style and hairstyle. For example, it can provide a complete outfit for a specific event. This allows it to collect the user's fashion style and clothing preferences and coordinate with the user's hairstyle.

[0064] The user information collection unit can collect opinions of the user's friends or family and provide advice from a social perspective. The user information collection unit, for example, provides a function that allows the user to request opinions on hairstyles from friends and family. For example, the proposed styles can be shared and feedback can be collected. The user information collection unit also suggests the most suitable hairstyle for the user based on the opinions of friends and family. For example, it can aggregate multiple opinions and prioritize the most popular style. The user information collection unit also analyzes feedback from friends and family to select the most suitable style for the user in order to provide advice from a social perspective. For example, it can recommend a style that has a large number of positive comments. This makes it possible to collect opinions from the user's friends and family and provide advice from a social perspective.

[0065] The user information collection unit uses the emotion estimation function to estimate the user's emotion when entering information in real time and make suggestions to elicit positive emotions. The user information collection unit, for example, estimates the user's emotion in real time using a camera or microphone when the user enters information. For example, it can analyze facial expressions and voice tone to determine the user's emotional state. The user information collection unit also makes suggestions to encourage the user to feel positive emotions based on the emotion estimation data. For example, it can adjust the interface so that the user enters information in a relaxed state. The user information collection unit also monitors the user's emotional state in real time, and if a negative emotion is detected, makes suggestions to elicit positive emotions. For example, it can present encouraging messages or success stories. This makes it possible to estimate the user's emotion when entering information in real time and make suggestions to elicit positive emotions.

[0066] The hairstyle analysis unit can analyze the user's emotional data and suggest a hairstyle based on the emotion. The hairstyle analysis unit, for example, collects the user's emotional data and suggests a hairstyle based on the user's emotional state. For example, it can suggest a casual style to a relaxed user and a refreshing style to a stressed user. The hairstyle analysis unit also analyzes the emotional data and identifies a hairstyle that evokes positive emotions in the user. For example, it can analyze past emotional data and hairstyle preferences to suggest an optimal style. The hairstyle analysis unit also monitors the user's emotional state in real time and suggests a hairstyle based on that data. For example, it can adjust the suggestion content each time the user's emotion changes. In this way, it is possible to analyze the user's emotional data and suggest a hairstyle based on the emotion.

[0067] The hairstyle analysis unit can perform an analysis that takes into account not only the user's face shape and hair type, but also bone structure and skin color. For example, the hairstyle analysis unit can build a system that analyzes the user's face shape and hair type, as well as bone structure and skin color. For example, it can propose an optimal hairstyle based on bone structure features and skin tone. The hairstyle analysis unit also proposes hairstyles that take bone structure and skin color into consideration. For example, it can propose a style that accentuates bone structure or a hair color that matches skin color. The hairstyle analysis unit can also develop a system that comprehensively analyzes the user's face shape, hair type, bone structure, and skin color and proposes an optimal hairstyle. For example, it can weight each element and perform an overall evaluation. This makes it possible to perform an analysis that takes into account not only the user's face shape and hair type, but also bone structure and skin color.

[0068] The hairstyle analysis unit can suggest hairstyles according to the season and weather based on the user's lifestyle. The hairstyle analysis unit, for example, collects lifestyle data of the user and suggests hairstyles according to the season and weather. For example, it can suggest cool styles in summer and warm styles in winter. The hairstyle analysis unit also collects weather data in real time and suggests hairstyles based on that information. For example, it can suggest styles that are resistant to humidity on rainy days. The hairstyle analysis unit also builds a system that suggests hairstyles taking into account the user's lifestyle, season, and weather. For example, it can suggest styles that are easy to maintain to a user who spends a lot of time outdoors. This makes it possible to suggest hairstyles according to the season and weather based on the user's lifestyle.

[0069] The hairstyle analysis unit can suggest an appropriate style by taking into consideration the user's occupation and social status. The hairstyle analysis unit, for example, suggests a hairstyle by taking into consideration the user's occupation and social status. For example, it can suggest a formal style to a business person and a unique style to a user in a creative occupation. The hairstyle analysis unit also builds a system that narrows down hairstyle options based on occupation and social status. For example, it can suggest styles that match the dress code for each occupation. The hairstyle analysis unit also analyzes the user's occupation and social status and suggests the optimal hairstyle based on that information. For example, it can reflect style trends according to occupation. This makes it possible to suggest an appropriate style by taking into consideration the user's occupation and social status.

[0070] The hairstyle analysis unit can suggest a style that reflects the user's hobbies and interests and brings out their individuality. The hairstyle analysis unit, for example, collects the user's hobbies and interests and suggests a hairstyle based on that information. For example, it can suggest an active style to a user who likes sports, and a creative style to a user who likes art. The hairstyle analysis unit also builds a system that suggests hairstyles that bring out their individuality based on the user's hobbies and interests. For example, it can suggest styles and colors related to a specific hobby. The hairstyle analysis unit also suggests hairstyles that reflect the user's hobbies and interests. For example, it can suggest an artistic style to a user who likes music. In this way, it is possible to suggest a style that reflects the user's hobbies and interests and brings out their individuality.

[0071] The hairstyle analysis unit can use the emotion estimation function to analyze hairstyle trends based on the user's emotions and reflect the results in suggestions. The hairstyle analysis unit, for example, uses the emotion estimation function to collect user emotion data and analyze hairstyle trends based on the data. For example, it can suggest styles that are associated with a high percentage of positive emotions as trends. The hairstyle analysis unit also analyzes the user's emotion data and identifies emotion-based hairstyle trends. For example, it can suggest styles that correspond to a specific emotional state. The hairstyle analysis unit also updates hairstyle trends in real time based on the emotion estimation data and reflects the latest trends in suggestions. For example, it can adjust trends according to changes in the emotion data. This makes it possible to analyze hairstyle trends based on the user's emotions and reflect the results in suggestions.

[0072] The hairstyle suggestion unit can suggest a hairstyle that matches the user's emotions based on the user's emotional data. For example, the hairstyle suggestion unit collects the user's emotional data and suggests a hairstyle that matches the user's emotions based on the data. For example, it can suggest a casual style to a relaxed user and a refreshing style to a stressed user. The hairstyle suggestion unit can also analyze the emotional data and identify a hairstyle that evokes positive emotions in the user. For example, it can analyze past emotional data and hairstyle preferences to suggest an optimal style. The hairstyle suggestion unit can also monitor the user's emotional state in real time and suggest a hairstyle based on the data. For example, it can adjust the suggestion content each time the user's emotions change. This makes it possible to suggest a hairstyle that matches the user's emotions based on the user's emotional data.

[0073] The hairstyle suggestion unit can collect user feedback on the proposed hairstyle and reflect it in the next suggestion. The hairstyle suggestion unit, for example, provides a function for collecting user feedback on the proposed hairstyle. For example, an interface can be provided that allows the user to input ratings and comments on the style. The hairstyle suggestion unit also builds a system that analyzes user feedback and reflects it in the next suggestion. For example, it can preferentially suggest styles that receive a lot of positive feedback. The hairstyle suggestion unit also accumulates feedback data and analyzes user preferences and trends. This enables more accurate hairstyle suggestions. This allows user feedback on the proposed hairstyle to be collected and reflected in the next suggestion.

[0074] The hairstyle suggestion unit can provide a video that provides detailed instructions on how to maintain and style the proposed hairstyle. For example, the hairstyle suggestion unit can provide a video that provides detailed instructions on how to maintain and style the proposed hairstyle. For example, the video can introduce how to set the hairstyle and the products to use. The hairstyle suggestion unit can also provide a step-by-step video guide so that the user can recreate the proposed hairstyle at home. For example, the video can explain how to use a hair iron and blow-drying techniques. The hairstyle suggestion unit can also provide a video that explains how to use hair care products and tools that match the proposed hairstyle. For example, the video can introduce how to use a specific shampoo and conditioner. This makes it possible to provide a video that provides detailed instructions on how to maintain and style the proposed hairstyle.

[0075] The hairstyle suggestion unit can also suggest makeup and accessories that match the proposed hairstyle. The hairstyle suggestion unit, for example, suggests makeup that matches the proposed hairstyle. For example, it can suggest eye makeup and lip color that matches a specific hairstyle. The hairstyle suggestion unit also suggests accessories that match the hairstyle. For example, it can suggest hairpins and earrings that match a specific hairstyle. The hairstyle suggestion unit also builds a system that suggests a total coordination of hairstyle, makeup, and accessories. For example, it can provide a total coordination for a specific event. This allows it to also suggest makeup and accessories that match the proposed hairstyle.

[0076] The hairstyle suggestion unit can display and refer to other users' ratings and comments on the proposed hairstyle. The hairstyle suggestion unit, for example, provides a function for displaying other users' ratings and comments on the proposed hairstyle. For example, an interface can be provided that allows users to input ratings and comments on the style. The hairstyle suggestion unit also builds a system that narrows down the options for proposed hairstyles based on other users' ratings and comments. For example, it can preferentially suggest styles that have many positive ratings. The hairstyle suggestion unit also analyzes feedback from other users and suggests the optimal hairstyle for the user. For example, it can recommend styles that have high ratings. This makes it possible to display and refer to other users' ratings and comments on the proposed hairstyle.

[0077] The hairstyle suggestion unit uses the emotion estimation function to monitor the user's emotional response to a proposed hairstyle in real time and make an optimal suggestion. The hairstyle suggestion unit, for example, uses the emotion estimation function to monitor the user's emotional response to a proposed hairstyle in real time. For example, it can analyze the user's facial expressions and voice and calculate an emotion score. The hairstyle suggestion unit also builds a system that suggests an optimal hairstyle based on the user's emotional response data. For example, it can preferentially suggest styles that have a high number of positive emotional responses. The hairstyle suggestion unit also develops a system that collects emotion estimation data in real time and dynamically adjusts the suggestion content. For example, it can update the suggestion content every time the user's emotion changes. This makes it possible to monitor the user's emotional response to a proposed hairstyle in real time and make an optimal suggestion.

[0078] The hairstyle simulation unit can simulate a hairstyle that matches the user's emotions based on the user's emotional data. For example, the hairstyle simulation unit collects the user's emotional data and simulates a hairstyle that matches the user's emotions based on the data. For example, it can simulate a casual style for a relaxed user and a refreshing style for a stressed user. The hairstyle simulation unit can also analyze the emotional data, identify a hairstyle that evokes positive emotions in the user, and simulate that style. For example, it can analyze past emotional data and hairstyle preferences to simulate an optimal style. The hairstyle simulation unit can also monitor the user's emotional state in real time and simulate a hairstyle based on that data. For example, it can adjust the simulation content each time the user's emotions change. This makes it possible to simulate a hairstyle that matches the user's emotions based on the user's emotional data.

[0079] The hairstyle simulation unit displays the simulation results as a 3D model, providing a more realistic image. For example, the hairstyle simulation unit generates a 3D model based on a user's photograph and realistically simulates a proposed hairstyle. For example, it can create a 3D model that reflects the user's face shape and hair type. The hairstyle simulation unit also uses the 3D model to display the proposed hairstyle from multiple angles. For example, it can provide views from the front, side, and back. The hairstyle simulation unit also provides an interface that allows the user to manipulate the 3D model in real time, allowing the user to freely change the viewpoint. For example, it can add a function to rotate the model using a mouse or touch operation. This allows the simulation results to be displayed as a 3D model, providing a more realistic image.

[0080] The hairstyle simulation unit can display the simulation results from multiple angles, allowing the user to check the overall balance. The hairstyle simulation unit, for example, provides a function for displaying the simulation results from multiple angles. For example, it can provide views from the front, side, and back, allowing the user to check the overall balance. The hairstyle simulation unit also provides an interface that allows the user to freely manipulate the simulation results. For example, it can add a function for rotating the model by mouse or touch operation. The hairstyle simulation unit also allows the user to select the optimal hairstyle based on views from multiple angles. For example, it can display the views from each angle side by side to make it easier to compare them. This allows the simulation results to be displayed from multiple angles, allowing the user to check the overall balance.

[0081] The hairstyle simulation unit can provide a function for sharing the simulation results on social media and collecting opinions from friends and family. The hairstyle simulation unit, for example, provides a function for sharing the simulation results on social media. For example, a button for posting the simulation results on platforms such as Facebook and Instagram can be provided. The hairstyle simulation unit also provides a comment function for collecting opinions from friends and family. For example, feedback on the simulation results can be received on social media. The hairstyle simulation unit can also analyze ratings and comments on the simulation results shared on social media and suggest the most suitable hairstyle for the user. For example, it can prioritize suggestions for styles with a lot of positive feedback. This makes it possible to provide a function for sharing the simulation results on social media and collecting opinions from friends and family.

[0082] The hairstyle simulation unit can provide a function for saving simulation results and comparing them with past simulations. The hairstyle simulation unit, for example, provides a function for saving simulation results. For example, it can enable a user to save past simulation results and review them later. The hairstyle simulation unit also provides an interface for comparing saved simulation results. For example, it can display multiple simulation results side by side so that differences can be confirmed. The hairstyle simulation unit also builds a system for analyzing user preferences and trends based on past simulation results. For example, it can suggest optimal hairstyles based on past data. This makes it possible to provide a function for saving simulation results and comparing them with past simulations.

[0083] The hairstyle simulation unit uses the emotion estimation function to monitor the user's emotional response to the simulation results in real time and perform an optimal simulation. The hairstyle simulation unit, for example, uses the emotion estimation function to monitor the user's emotional response to the simulation results in real time. For example, it can analyze the user's facial expressions and voice and calculate an emotion score. The hairstyle simulation unit also builds a system that performs an optimal simulation based on the user's emotional response data. For example, it can prioritize simulation of styles that have a high number of positive emotional responses. The hairstyle simulation unit also develops a system that collects emotion estimation data in real time and dynamically adjusts the simulation content. For example, it can update the simulation content every time the user's emotion changes. This allows the user's emotional response to the simulation results to be monitored in real time and perform an optimal simulation.

[0084] The hair care advice unit can provide hair care advice that matches the user's emotions based on the user's emotional data. For example, the hair care advice unit collects the user's emotional data and provides hair care advice that matches the user's emotions based on the data. For example, it can recommend a refreshing hair care product to a relaxed user and a product with a relaxing effect to a stressed user. The hair care advice unit can also analyze the emotional data and identify hair care products that evoke positive emotions in the user. For example, it can analyze past emotional data and the history of hair care product use to recommend the most suitable product. The hair care advice unit can also monitor the user's emotional state in real time and provide hair care advice based on the data. For example, it can adjust the advice content each time the user's emotions change. This makes it possible to provide hair care advice that matches the user's emotions based on the user's emotional data.

[0085] The hair care advice unit can periodically monitor the health condition of the user's hair and provide appropriate hair care advice. For example, the hair care advice unit uses a hairbrush or shampoo equipped with a sensor to periodically monitor the health condition of the user's hair. For example, it can measure the moisture content and damage level of the hair and collect the data. The hair care advice unit can also analyze the periodically collected hair health data and provide appropriate hair care advice. For example, if the hair is highly damaged, it can recommend a product with high moisturizing effects. The hair care advice unit can also monitor the health condition of the user's hair and build a system that provides hair care advice in real time based on the data. For example, the advice content can be updated every time the hair condition changes. This allows the health condition of the user's hair to be periodically monitored and appropriate hair care advice to be provided.

[0086] The hair care advice unit can explain the ingredients and effects of hair care products in detail and recommend the most suitable product to the user. For example, the hair care advice unit can build a database that explains the ingredients and effects of hair care products in detail and recommend the most suitable product to the user. For example, it can explain the effects and usage methods of products containing specific ingredients. The hair care advice unit can also develop a system that recommends the most suitable hair care product based on the user's hair condition and lifestyle. For example, it can recommend products with high moisturizing effects to users with severely damaged hair. The hair care advice unit can also provide videos that explain the ingredients and effects of hair care products in detail, making it easier for users to select products. For example, it can explain how to use the product and its effects through videos. This allows the ingredients and effects of hair care products to be explained in detail and the most suitable product to be recommended to the user.

[0087] The hair care advice unit can provide comprehensive hair care advice by taking into account the user's diet and lifestyle. The hair care advice unit, for example, collects information on the user's diet and lifestyle and provides comprehensive hair care advice based on that data. For example, the hair care advice unit can provide advice taking into account nutritional balance and sleep status. The hair care advice unit also builds a system that provides advice for maintaining healthy hair based on the user's diet and lifestyle. For example, it can recommend foods containing specific nutrients. The hair care advice unit also monitors the user's diet and lifestyle and provides hair care advice in real time based on that data. For example, it can adjust the advice content depending on the content of meals and the amount of exercise. This makes it possible to provide comprehensive hair care advice by taking into account the user's diet and lifestyle.

[0088] The hair care advice unit can provide appropriate hair care advice by taking the user's environment into consideration. The hair care advice unit, for example, collects information about the user's living environment and provides hair care advice based on that data. For example, it can provide advice based on the climate and water quality. The hair care advice unit also analyzes environmental data and builds a system that suggests optimal hair care products and methods to users. For example, it can suggest humidity-resistant products to users living in humid areas. The hair care advice unit also collects environmental data about the user in real time and provides hair care advice based on that data. For example, it can update the advice content every time the weather changes. This allows the hair care advice unit to provide appropriate hair care advice by taking the user's environment into consideration.

[0089] The hair care advice unit uses the emotion estimation function to monitor the user's emotional response to hair care advice in real time and provide optimal advice. The hair care advice unit, for example, uses the emotion estimation function to monitor the user's emotional response to hair care advice in real time. For example, it can analyze the user's facial expressions and voice and calculate an emotion score. The hair care advice unit also builds a system that provides optimal hair care advice based on the user's emotional response data. For example, it can prioritize the provision of advice with a high number of positive emotional responses. The hair care advice unit also develops a system that collects emotion estimation data in real time and dynamically adjusts the advice content. For example, it can update the advice content every time the user's emotion changes. This makes it possible to monitor the user's emotional response to hair care advice in real time and provide optimal advice.

[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 hairstyle suggestion system can further include a hobby information collection unit that reflects the user's hobbies and interests. For example, if the user likes sports, a hairstyle that suits an active lifestyle can be suggested. Also, if the user likes art or music, creative styles or artistic hair colors can be suggested. Furthermore, the hobby information collection unit can also suggest styles that match events or activities related to the user's hobbies. For example, it can suggest styles that are suitable for attending a concert or art exhibition. This makes it possible to suggest unique hairstyles that reflect the user's hobbies and interests.

[0092] The hairstyle suggestion system can also be equipped with a health information collection unit that monitors the user's health condition. For example, sensors can be installed in the hairbrush or shampoo used by the user to measure the health of the hair. The system can analyze the moisture content and damage level of the hair in real time and suggest the most suitable hair care products and styles for the user. In addition, a wearable device can be used to monitor the user's stress level and sleep state, and hairstyle suggestions can be made based on that data. This makes it possible to suggest hairstyles that take the user's health condition into consideration.

[0093] The hairstyle suggestion system can further include a fashion information collection unit that reflects the user's fashion style. For example, the user can upload photos of the clothes they usually wear and collect that data. The system can categorize styles into casual, formal, sporty, etc., and suggest hairstyles based on the fashion style. For example, it can suggest relaxed hairstyles for casual clothing and elegant hairstyles for formal clothing. This makes it possible to suggest hairstyles that are consistent with the user's fashion style.

[0094] The hairstyle suggestion system may further include a social information gathering unit that collects opinions from the user's friends and family. For example, a function may be provided that allows the user to ask friends and family for their opinions on hairstyles. The suggested styles may be shared and feedback may be collected. Furthermore, the system may suggest the most suitable hairstyle for the user based on the opinions of friends and family. For example, multiple opinions may be aggregated and the most popular style may be suggested preferentially. This makes it possible to suggest hairstyles that reflect advice from a social perspective.

[0095] The hairstyle suggestion system can further include an occupational information collection unit that takes into account the user's occupation and social status. For example, it can suggest hairstyles based on the user's occupation and social status. Formal styles can be suggested for business people, and unique styles can be suggested for users in creative occupations. It can also suggest styles that match the dress code for each occupation. This makes it possible to suggest appropriate hairstyles that take into account the user's occupation and social status.

[0096] The hairstyle suggestion system can further analyze the user's emotional data and suggest hairstyles based on the user's emotions. For example, it can suggest a casual style to a relaxed user and a refreshing style to a stressed user. It can also analyze the emotional data and identify hairstyles that evoke positive emotions in the user. It can analyze the user's past emotional data and hairstyle preferences to suggest the most suitable style. This makes it possible to suggest hairstyles based on the user's emotional data.

[0097] The hairstyle suggestion system can further use a user emotion estimation function to monitor the user's emotional response to proposed hairstyles in real time and make optimal suggestions. For example, it can analyze the user's facial expressions and voice to calculate an emotional score. Based on the user's emotional response data, it can prioritize suggestions that evoke a positive emotional response. It can also collect emotion estimation data in real time and dynamically adjust the suggestions. This allows it to monitor the user's emotional response to proposed hairstyles in real time and make optimal suggestions.

[0098] The hairstyle suggestion system can further use a user emotion estimation function to estimate the user's emotion in real time when entering information, and make suggestions that elicit positive emotions. For example, when a user enters information, emotions can be estimated in real time using a camera or microphone. Based on the emotion estimation data, suggestions that will elicit positive emotions can be made. The interface can be adjusted so that the user enters information in a relaxed state. This makes it possible to estimate the user's emotion in real time when entering information, and make suggestions that will elicit positive emotions.

[0099] The hairstyle suggestion system can further use a user emotion estimation function to analyze hairstyle trends based on emotions and reflect them in suggestions. For example, the emotion estimation function can be used to collect user emotion data and analyze hairstyle trends based on that data. Styles that evoke a lot of positive emotions can be suggested as trends. Furthermore, the emotion data can be analyzed to suggest styles that correspond to specific emotional states. This makes it possible to analyze hairstyle trends based on the user's emotions and reflect them in suggestions.

[0100] The hairstyle suggestion system can further use a user emotion estimation function to monitor the user's emotional response to proposed hairstyles in real time and make optimal suggestions. For example, it can analyze the user's facial expressions and voice to calculate an emotional score. Based on the user's emotional response data, it can prioritize suggestions that evoke a positive emotional response. It can also collect emotion estimation data in real time and dynamically adjust the suggestions. This allows it to monitor the user's emotional response to proposed hairstyles in real time and make optimal suggestions.

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

[0102] Step 1: The user information collection unit collects information about the user's face shape, hair type, and lifestyle. For example, the user may input information about their face shape (round, oval, square, etc.), hair type (straight, wavy, curly, etc.), and lifestyle (job, hobbies, daily activity, etc.). Step 2: The hairstyle analysis unit analyzes the optimal hairstyle based on the user information collected by the user information collection unit. For example, it suggests hairstyles that make a user with a round face appear slimmer, and suggests styles that make the most of the user's hair type for a user with straight hair. It also suggests styles that are easy to maintain or suitable for formal occasions, depending on the user's lifestyle. Step 3: The hairstyle suggestion unit suggests the optimal hairstyle for the user based on the results of the analysis by the hairstyle analysis unit. For example, it provides specific advice such as, "Your face shape will suit a style with swept bangs," or "A layered cut is suitable for your hair type." It also provides images of the suggested hairstyles and styling instructions.

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

[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. a user information collection unit that collects information on the user's face shape, hair type, and lifestyle; a hairstyle analysis unit that analyzes an optimal hairstyle based on the user information collected by the user information collection unit; a hairstyle suggestion unit that suggests an optimal hairstyle to the user based on the results of the analysis by the hairstyle analysis unit. A system characterized by:

2. The user information collection unit The user's emotional state is estimated in real time, and hairstyle preferences based on the emotional state are reflected.

2. The system of claim 1.

3. The hairstyle analysis unit The analysis takes into account not only the user's face shape and hair type, but also bone structure and skin color.

2. The system of claim 1.

4. The hairstyle suggestion unit Providing a video that provides detailed instructions on how to maintain and style the proposed hairstyle 2. The system of claim 1.

5. The hairstyle simulation section Based on the user's emotional data, we simulate hairstyles that match the emotion.

2. The system of claim 1.

6. Hair care advice section Providing emotionally appropriate hair care advice based on user emotional data 2. The system of claim 1.

Images