System

Abstract

An object of a system according to an embodiment is to effectively provide coupons to users.SOLUTION: A system includes a wake-up alarm function, a voice advertisement reproduction function, and a coupon acquisition button display function. The wake-up alarm function provides a wake-up alarm. The voice advertisement playback function plays back a voice advertisement. The coupon acquisition button display function displays a coupon acquisition button.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional techniques have limited means for effectively providing coupons to users, and there is room for improvement.

[0005] The system according to the embodiment aims to effectively provide coupons to users. [Means for solving the problem]

[0006] The system according to the embodiment includes an alarm function, an audio advertisement playback function, and a coupon acquisition button display function. The alarm function provides an alarm. The audio advertisement playback function plays an audio advertisement. The coupon acquisition button display function displays a coupon acquisition button. [Effects of the Invention]

[0007] The system according to the embodiment can effectively provide coupons to users. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

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

[0028] (Example 1) The coupon provision system according to the embodiment of the present invention is a system that uses the alarm sound that users hear every morning as an audio advertisement in order to effectively provide coupons to users. This allows the coupon provision system to provide PayPay coupons that are just right for the user.

[0029] The coupon provision system according to the embodiment includes an alarm function, an audio advertisement playback function, and a coupon acquisition button display function. The alarm function sounds an alarm at a time set by the user. For example, if a user sets an alarm for 7:00 a.m. every morning, the alarm will sound at that time. The alarm function also includes a snooze function, which allows the user to press the snooze button and have the alarm sound again after a certain time. The alarm function also allows the user to select the type of alarm sound. For example, the user can choose from multiple alarm sounds, such as music or nature sounds. The audio advertisement playback function plays an audio advertisement as the alarm sound. For example, a generation AI (such as a text generation AI or a multimodal generation AI) analyzes user behavior data, generates optimal advertisement copy, and reads it aloud. The audio advertisement playback function can also adjust the playback timing and volume of advertisements. For example, advertisements related to stores or services frequently used by the user are played. The coupon acquisition button display function displays a coupon acquisition button on the smartphone screen while the alarm is sounding. For example, if the user presses the coupon acquisition button, the alarm sound stops and a coupon can be acquired. In addition, when an advertisement for a company that does not provide coupons is displayed, the button is changed to a PayPay point acquisition button. For example, when the coupon acquisition button is pressed, a coupon is provided within the PayPay app. This allows the coupon provision system according to the embodiment to effectively provide coupons to users.

[0030] The wake-up alarm function can analyze a user's sleep patterns, estimate the optimal time to wake up, and sound an alarm. For example, the wake-up alarm function uses a smartphone's sensors to detect the user's movements and sounds to analyze the user's sleep patterns. This allows the user to understand the cycle of deep and light sleep and estimate the optimal time to wake up. To analyze the sleep patterns, the wake-up alarm function models individual sleep cycles based on information the user enters before going to bed (e.g., bedtime and wake-up time). This allows for customized alarm settings for each user. Based on the results of the sleep pattern analysis, the wake-up alarm function estimates the time when the user will wake up most refreshed and sounds the alarm at that time. For example, the alarm can be set to target the light sleep period. This allows the user to wake up at the optimal time.

[0031] The wake-up alarm function can combine natural sounds and environmental sounds with the alarm sound to enhance the user's relaxation. For example, the wake-up alarm function can combine natural sounds such as birds chirping or the sound of waves with the alarm sound, allowing the user to wake up in a relaxed state. This allows the user to wake up with less stress. The wake-up alarm function can also incorporate environmental sounds such as the sound of rain or wind into the alarm sound, giving the user the feeling of waking up in nature. This supports a more comfortable awakening. The wake-up alarm function can also randomly combine natural sounds and environmental sounds to provide a different alarm sound every morning, allowing the user to experience a relaxed awakening without getting bored. This allows the user to wake up in a relaxed state.

[0032] The wake-up alarm function adds a weather forecast or news reading function to the alarm function, supporting users in gathering information in the morning. For example, the wake-up alarm function adds a function that reads out the day's weather forecast aloud at the same time as the alarm sounds. This allows users to know the weather information the moment they wake up. The wake-up alarm function also adds a function that reads out the latest news headlines aloud after the alarm sounds. This allows users to make effective use of their morning time while gathering information. The wake-up alarm function also adds a function that customizes the weather forecast and news reading content according to the user's interests. For example, sports news or economic news can be read out preferentially. This allows users to get the information they need the moment they wake up.

[0033] The wake-up alarm function allows the user to customize the alarm sound and set their favorite music or message. For example, the wake-up alarm function adds a function that allows the user to set their favorite music as the alarm sound. This allows the user to wake up to their favorite song. The wake-up alarm function also adds a function that allows the user to set a message that they have recorded themselves as the alarm sound. For example, a message from family or friends can be set as the alarm sound. The wake-up alarm function also provides a function to customize the alarm sound and allows the user to set a combination of multiple music and messages. This allows the user to enjoy a different alarm sound every morning. This allows the user to set the alarm sound to suit their preferences.

[0034] The audio ad playback function uses a generation AI to analyze a user's past purchase history and search history, allowing it to generate more personalized ads. For example, the audio ad playback function uses the generation AI to analyze a user's past purchase history and generate personalized ads based on that data. For example, it creates ads related to products that the user frequently purchases. The audio ad playback function also analyzes a user's search history and generates ads based on their interests. For example, it creates ads for products and services related to recently searched keywords. The audio ad playback function also combines purchase history and search history to generate ads that are optimal for the user. For example, it customizes ads based on past purchase trends and current search trends. This allows it to provide the user with the most optimal ads.

[0035] The audio ad playback function can add interactive elements to audio ads, allowing users to respond by voice. The audio ad playback function, for example, adds interactive elements to audio ads, providing a function that allows users to respond by voice. For example, a question can be posed within the ad, and the user can respond by voice. The audio ad playback function also adds a function that allows users to request more detailed information about products or services in which they are interested by voice through interactive audio ads. For example, the audio response of the user can be analyzed, and the content of the next ad can be customized based on the results. For example, related ads can be played in succession depending on the user's response. This allows users to respond to ads interactively.

[0036] The audio ad playback function adds visual elements to audio ads and can display related images and videos on the smartphone screen. For example, the audio ad playback function adds a function to display related images and videos on the smartphone screen when an audio ad is played. For example, it can display images of the product featured in the ad or a promotional video. The audio ad playback function also adds visual elements to make it easier for users to visually understand the content of the ad. For example, it can play a video that shows how to use the product in conjunction with the audio ad. The audio ad playback function also combines audio ads with visual elements to more easily attract users' interest. For example, it can explain the features of a product through audio while displaying detailed information about the product on the screen. This makes it easier for users to visually understand the content of the ad.

[0037] The audio ad playback function can automatically generate audio ads in different languages, enabling multilingual support. For example, the audio ad playback function uses generation AI to build a system that automatically generates audio ads in different languages. For example, it supports multiple languages ​​such as English, French, and Chinese. The audio ad playback function also adds a function that automatically plays audio ads in the appropriate language according to the user's language settings. This enables multilingual support. Furthermore, when generating audio ads in different languages, the audio ad playback function provides content that takes into consideration the culture and customs of each language. For example, it generates ad copy that reflects the characteristics of each region. This enables multilingual support.

[0038] The coupon get button display function can provide coupons that can be used at the nearest store based on the user's location information when the user presses the coupon get button. For example, when the coupon get button is pressed, the coupon get button display function uses the smartphone's GPS function to obtain the user's location information and provides coupons that can be used at the nearest store. The coupon get button display function also displays store information around the user's current location based on the user's location information and provides coupons for stores selected from that information. For example, it displays coupons for nearby cafes and restaurants. The coupon get button display function also uses location information to prioritize store coupons in areas that the user frequently visits. For example, it displays store coupons for stores along the user's commute route or near the user's home. This allows the user to easily obtain coupons that can be used at the nearest store.

[0039] The coupon get button display function can prioritize displaying relevant coupons based on the user's purchase history when the user presses the coupon get button. For example, when the coupon get button is pressed, the coupon get button display function analyzes the user's past purchase history and prioritizes displaying relevant coupons based on that data. For example, it provides coupons related to frequently purchased products and services. The coupon get button display function also automatically selects and displays coupons that the user is likely to be interested in based on the purchase history. For example, it prioritizes displaying coupons in the same category as products purchased in the past. The coupon get button display function also utilizes the purchase history to prioritize coupons for stores that the user frequently visits. For example, it displays coupons for cafes and restaurants that the user regularly visits. This makes it possible to provide coupons that are highly relevant to the user.

[0040] The Get Coupon button display function can promote social sharing by providing a coupon that can be shared with friends or family when the Get Coupon button is pressed. The Get Coupon button display function adds a function that provides a coupon that can be shared with friends and family when the Get Coupon button is pressed. For example, a share link can be generated to make it easy to share on social media or messaging apps. The Get Coupon button display function also provides benefits that can be used with friends and family by using the shared coupon. For example, coupons for group discounts or pair discounts can be provided. The Get Coupon button display function also promotes social sharing by encouraging users to use the coupon with friends and family through the coupon sharing function. For example, additional benefits can be provided when the shared coupon is used. This can promote social sharing by encouraging users to share the coupon with friends and family.

[0041] The Get Coupon Button Display function can encourage users to make purchases by displaying limited-time sales or special offers when the Get Coupon Button is pressed. The Get Coupon Button Display function adds a function to display limited-time sales or special offers when the Get Coupon Button is pressed. For example, it can provide discount coupons that can be used within a certain period of time. The Get Coupon Button Display function also encourages users to make purchases through limited-time sales or special offers. For example, it can provide discounts or special offers that are valid for a limited time. The Get Coupon Button Display function also automatically selects and displays special offers that the user may be interested in when the Get Coupon Button is pressed. For example, it can provide offers based on past purchase history or interests. This can encourage users to make purchases.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The coupon provision system can also analyze a user's health data and provide coupons according to their health condition. For example, based on the user's step count data, a fitness-related coupon can be provided when a certain number of steps is achieved. The coupon provision system can also analyze the user's food records and provide coupons for nutritionally balanced foods. Furthermore, based on the user's sleep data, it can provide coupons for products and services that support good quality sleep. This makes it possible to provide personalized coupons according to the user's health condition.

[0044] The coupon providing system can also provide coupons based on the user's hobbies and interests. For example, if the user likes music, coupons for concert tickets or music streaming services can be provided. If the user likes movies, coupons for movie theater tickets or movie streaming services can be provided. Furthermore, if the user likes traveling, coupons related to travel or discount coupons for accommodations can be provided. In this way, coupons can be provided that match the user's hobbies and interests.

[0045] The coupon providing system can also provide coupons according to the user's life events. For example, a special discount coupon can be provided for the user's birthday. Coupons for related products can also be provided for special occasions such as wedding anniversaries and children's birthdays. Furthermore, when a user starts a new job or moves, coupons for necessary products or services can also be provided. In this way, coupons can be provided according to the user's life events.

[0046] The coupon provision system can also analyze a user's social media activity and provide relevant coupons. For example, if a user mentions a particular brand or product on social media, a coupon for that brand or product can be provided. Also, if a user participates in a particular event, a coupon related to that event can be provided. Furthermore, it is possible to provide similar coupons based on coupons used by the user's followers and friends. This makes it possible to provide coupons that correspond to the user's social media activity.

[0047] The coupon providing system can also provide coupons that can only be used in a specific area based on the user's location information. For example, if the user is in a specific shopping mall, coupons that can be used at stores in the mall can be provided. Also, if the user is in a specific tourist spot, coupons for restaurants and souvenir shops in the area can be provided. Furthermore, if the user is at a specific event venue, coupons related to that event can be provided. In this way, coupons can be provided according to the user's location information.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The wake-up alarm function sounds an alarm at the time set by the user. For example, if a user sets an alarm for 7:00 a.m. every morning, the alarm will sound at that time. The wake-up alarm function also has a snooze function, and if the user presses the snooze button, the alarm will sound again after a certain period of time. Furthermore, the wake-up alarm function allows the user to select the type of alarm sound. For example, there are multiple alarm sounds to choose from, such as music or nature sounds. Step 2: The audio ad playback function plays an audio ad as an alarm sound. For example, a generation AI (text generation AI or multimodal generation AI) analyzes the user's behavioral data, generates the optimal ad copy, and reads it out loud. The audio ad playback function can also adjust the playback timing and volume of the ad. For example, it can play ads related to stores and services that the user frequently uses. Step 3: The coupon acquisition button display function displays a coupon acquisition button on the smartphone screen while the alarm is ringing. For example, if the user presses the coupon acquisition button, the alarm will stop and the user will be able to acquire a coupon. Also, if an advertisement for a company that does not offer coupons is played, it will be changed to a PayPay points acquisition button. For example, if the coupon acquisition button is pressed, a coupon will be provided within the PayPay app.

[0050] (Example 2) The coupon provision system according to the embodiment of the present invention is a system that uses the alarm sound that users hear every morning as an audio advertisement in order to effectively provide coupons to users. This allows the coupon provision system to provide PayPay coupons that are just right for the user.

[0051] The coupon provision system according to the embodiment includes an alarm function, an audio advertisement playback function, and a coupon acquisition button display function. The alarm function sounds an alarm at a time set by the user. For example, if a user sets an alarm for 7:00 a.m. every morning, the alarm will sound at that time. The alarm function also includes a snooze function, which allows the user to press the snooze button and have the alarm sound again after a certain time. The alarm function also allows the user to select the type of alarm sound. For example, the user can choose from multiple alarm sounds, such as music or nature sounds. The audio advertisement playback function plays an audio advertisement as the alarm sound. For example, a generation AI (such as a text generation AI or a multimodal generation AI) analyzes user behavior data, generates optimal advertisement copy, and reads it aloud. The audio advertisement playback function can also adjust the playback timing and volume of advertisements. For example, advertisements related to stores or services frequently used by the user are played. The coupon acquisition button display function displays a coupon acquisition button on the smartphone screen while the alarm is sounding. For example, if the user presses the coupon acquisition button, the alarm sound stops and a coupon can be acquired. In addition, when an advertisement for a company that does not provide coupons is displayed, the button is changed to a PayPay point acquisition button. For example, when the coupon acquisition button is pressed, a coupon is provided within the PayPay app. This allows the coupon provision system according to the embodiment to effectively provide coupons to users.

[0052] The wake-up alarm function can analyze a user's sleep patterns, estimate the optimal time to wake up, and sound an alarm. For example, the wake-up alarm function uses a smartphone's sensors to detect the user's movements and sounds to analyze the user's sleep patterns. This allows the user to understand the cycle of deep and light sleep and estimate the optimal time to wake up. To analyze the sleep patterns, the wake-up alarm function models individual sleep cycles based on information the user enters before going to bed (e.g., bedtime and wake-up time). This allows for customized alarm settings for each user. Based on the results of the sleep pattern analysis, the wake-up alarm function estimates the time when the user will wake up most refreshed and sounds the alarm at that time. For example, the alarm can be set to target the light sleep period. This allows the user to wake up at the optimal time.

[0053] The wake-up alarm function can combine natural sounds and environmental sounds with the alarm sound to enhance the user's relaxation. For example, the wake-up alarm function can combine natural sounds such as birds chirping or the sound of waves with the alarm sound, allowing the user to wake up in a relaxed state. This allows the user to wake up with less stress. The wake-up alarm function can also incorporate environmental sounds such as the sound of rain or wind into the alarm sound, giving the user the feeling of waking up in nature. This supports a more comfortable awakening. The wake-up alarm function can also randomly combine natural sounds and environmental sounds to provide a different alarm sound every morning, allowing the user to experience a relaxed awakening without getting bored. This allows the user to wake up in a relaxed state.

[0054] The wake-up alarm function uses the emotion estimation function to select an alarm sound that corresponds to the user's emotional state, thereby reducing stress. For example, the wake-up alarm function uses the emotion estimation function to analyze the user's emotional state in real time and selects an alarm sound based on the results. For example, if the user is highly stressed, it selects music with a relaxing effect. The wake-up alarm function also uses the smartphone's camera and microphone to detect facial expressions and tone of voice to analyze the user's emotional state. This allows for an accurate understanding of the user's emotional state. Furthermore, the wake-up alarm function automatically selects an alarm sound that relaxes the user based on the emotion estimation data, supporting a less stressful wake-up. For example, it selects calming music or natural sounds. This reduces the user's stress and supports a more comfortable wake-up.

[0055] The wake-up alarm function adds a weather forecast or news reading function to the alarm function, supporting users in gathering information in the morning. For example, the wake-up alarm function adds a function that reads out the day's weather forecast aloud at the same time as the alarm sounds. This allows users to know the weather information the moment they wake up. The wake-up alarm function also adds a function that reads out the latest news headlines aloud after the alarm sounds. This allows users to make effective use of their morning time while gathering information. The wake-up alarm function also adds a function that customizes the weather forecast and news reading content according to the user's interests. For example, sports news or economic news can be read out preferentially. This allows users to get the information they need the moment they wake up.

[0056] The wake-up alarm function allows the user to customize the alarm sound and set their favorite music or message. For example, the wake-up alarm function adds a function that allows the user to set their favorite music as the alarm sound. This allows the user to wake up to their favorite song. The wake-up alarm function also adds a function that allows the user to set a message that they have recorded themselves as the alarm sound. For example, a message from family or friends can be set as the alarm sound. The wake-up alarm function also provides a function to customize the alarm sound and allows the user to set a combination of multiple music and messages. This allows the user to enjoy a different alarm sound every morning. This allows the user to set the alarm sound to suit their preferences.

[0057] The wake-up alarm function can use the emotion estimation function to display a motivational message that corresponds to the user's mood after waking up. For example, the wake-up alarm function uses the emotion estimation function to analyze the user's mood after waking up and display a motivational message based on the results. For example, it displays positive messages or words of encouragement. The wake-up alarm function also uses the smartphone's camera and microphone to detect facial expressions and tone of voice to analyze the user's emotional state. This allows it to accurately grasp the user's mood. The wake-up alarm function also automatically displays a motivational message based on the emotion estimation data to help the user start their day in a positive way. For example, it displays success stories or famous quotes. This allows the user to start their day in a positive way.

[0058] The audio ad playback function uses a generation AI to analyze a user's past purchase history and search history, allowing it to generate more personalized ads. For example, the audio ad playback function uses the generation AI to analyze a user's past purchase history and generate personalized ads based on that data. For example, it creates ads related to products that the user frequently purchases. The audio ad playback function also analyzes a user's search history and generates ads based on their interests. For example, it creates ads for products and services related to recently searched keywords. The audio ad playback function also combines purchase history and search history to generate ads that are optimal for the user. For example, it customizes ads based on past purchase trends and current search trends. This allows it to provide the user with the most optimal ads.

[0059] The audio ad playback function can add interactive elements to audio ads, allowing users to respond by voice. The audio ad playback function, for example, adds interactive elements to audio ads, providing a function that allows users to respond by voice. For example, a question can be posed within the ad, and the user can respond by voice. The audio ad playback function also adds a function that allows users to request more detailed information about products or services in which they are interested by voice through interactive audio ads. For example, the audio response of the user can be analyzed, and the content of the next ad can be customized based on the results. For example, related ads can be played in succession depending on the user's response. This allows users to respond to ads interactively.

[0060] The audio ad playback function can use the emotion estimation function to read advertisements in a tone and tempo that corresponds to the user's emotional state. For example, the audio ad playback function uses the emotion estimation function to analyze the user's emotional state in real time and adjust the tone and tempo of the advertisement based on the results. For example, the audio ad playback function reads the advertisement in a calm tone for a user who is relaxed. The audio ad playback function also uses the smartphone's camera and microphone to detect facial expressions and tone of voice to analyze the user's emotional state. This optimizes the way the advertisement is read. The audio ad playback function also reads the advertisement in a tone and tempo that is most acceptable to the user based on the emotion estimation data. For example, the audio ad playback function reads the advertisement in an energetic tone for a user who is excited. This makes it possible to provide advertisements that correspond to the user's emotional state.

[0061] The audio ad playback function adds visual elements to audio ads and can display related images and videos on the smartphone screen. For example, the audio ad playback function adds a function to display related images and videos on the smartphone screen when an audio ad is played. For example, it can display images of the product featured in the ad or a promotional video. The audio ad playback function also adds visual elements to make it easier for users to visually understand the content of the ad. For example, it can play a video that shows how to use the product in conjunction with the audio ad. The audio ad playback function also combines audio ads with visual elements to more easily attract users' interest. For example, it can explain the features of a product through audio while displaying detailed information about the product on the screen. This makes it easier for users to visually understand the content of the ad.

[0062] The audio ad playback function can automatically generate audio ads in different languages, enabling multilingual support. For example, the audio ad playback function uses generation AI to build a system that automatically generates audio ads in different languages. For example, it supports multiple languages ​​such as English, French, and Chinese. The audio ad playback function also adds a function that automatically plays audio ads in the appropriate language according to the user's language settings. This enables multilingual support. Furthermore, when generating audio ads in different languages, the audio ad playback function provides content that takes into consideration the culture and customs of each language. For example, it generates ad copy that reflects the characteristics of each region. This enables multilingual support.

[0063] The audio ad playback function uses the emotion estimation function to collect emotional responses after users listen to an advertisement, allowing the effectiveness of the advertisement to be evaluated in real time. For example, the audio ad playback function uses the emotion estimation function to build a system that collects emotional responses after users listen to an advertisement in real time. For example, it analyzes the user's facial expressions and tone of voice. The audio ad playback function also evaluates the effectiveness of the advertisement in real time based on the user's emotional response data. For example, it gives a high rating to advertisements that receive a lot of positive emotional responses. The audio ad playback function also identifies areas for improvement in the advertisement based on the emotion estimation data and reflects these in the content of the next advertisement. For example, it corrects parts that receive a lot of negative responses. This allows the effectiveness of the advertisement to be evaluated in real time.

[0064] The coupon get button display function can provide coupons that can be used at the nearest store based on the user's location information when the user presses the coupon get button. For example, when the coupon get button is pressed, the coupon get button display function uses the smartphone's GPS function to obtain the user's location information and provides coupons that can be used at the nearest store. The coupon get button display function also displays store information around the user's current location based on the user's location information and provides coupons for stores selected from that information. For example, it displays coupons for nearby cafes and restaurants. The coupon get button display function also uses location information to prioritize store coupons in areas that the user frequently visits. For example, it displays store coupons for stores along the user's commute route or near the user's home. This allows the user to easily obtain coupons that can be used at the nearest store.

[0065] The coupon get button display function can prioritize displaying relevant coupons based on the user's purchase history when the user presses the coupon get button. For example, when the coupon get button is pressed, the coupon get button display function analyzes the user's past purchase history and prioritizes displaying relevant coupons based on that data. For example, it provides coupons related to frequently purchased products and services. The coupon get button display function also automatically selects and displays coupons that the user is likely to be interested in based on the purchase history. For example, it prioritizes displaying coupons in the same category as products purchased in the past. The coupon get button display function also utilizes the purchase history to prioritize coupons for stores that the user frequently visits. For example, it displays coupons for cafes and restaurants that the user regularly visits. This makes it possible to provide coupons that are highly relevant to the user.

[0066] The coupon get button display function uses the emotion estimation function to provide coupons that correspond to the user's emotional state, thereby increasing purchasing motivation. The coupon get button display function, for example, uses the emotion estimation function to analyze the user's emotional state in real time and provide coupons based on the results. For example, a special discount coupon is provided to a user in a positive emotional state. The coupon get button display function also uses the smartphone's camera and microphone to detect facial expressions and tone of voice to analyze the user's emotional state. This allows for an accurate understanding of the user's emotional state. The coupon get button display function also automatically selects and provides coupons that will most likely inspire the user to purchase based on the emotion estimation data. For example, a coupon for a refreshing product is provided to a user who is in a relaxed state. This makes it possible to increase purchasing motivation by providing coupons that correspond to the user's emotional state.

[0067] The Get Coupon button display function can promote social sharing by providing a coupon that can be shared with friends or family when the Get Coupon button is pressed. The Get Coupon button display function adds a function that provides a coupon that can be shared with friends and family when the Get Coupon button is pressed. For example, a share link can be generated to make it easy to share on social media or messaging apps. The Get Coupon button display function also provides benefits that can be used with friends and family by using the shared coupon. For example, coupons for group discounts or pair discounts can be provided. The Get Coupon button display function also promotes social sharing by encouraging users to use the coupon with friends and family through the coupon sharing function. For example, additional benefits can be provided when the shared coupon is used. This can promote social sharing by encouraging users to share the coupon with friends and family.

[0068] The Get Coupon Button Display function can encourage users to make purchases by displaying limited-time sales or special offers when the Get Coupon Button is pressed. The Get Coupon Button Display function adds a function to display limited-time sales or special offers when the Get Coupon Button is pressed. For example, it can provide discount coupons that can be used within a certain period of time. The Get Coupon Button Display function also encourages users to make purchases through limited-time sales or special offers. For example, it can provide discounts or special offers that are valid for a limited time. The Get Coupon Button Display function also automatically selects and displays special offers that the user may be interested in when the Get Coupon Button is pressed. For example, it can provide offers based on past purchase history or interests. This can encourage users to make purchases.

[0069] The coupon get button display function can use the emotion estimation function to analyze the emotional response of a user after obtaining a coupon and reflect this in the next coupon offering. The coupon get button display function, for example, uses the emotion estimation function to build a system that collects the emotional response of a user after obtaining a coupon in real time. For example, it analyzes the user's facial expression and tone of voice. The coupon get button display function also reflects this in the next coupon offering based on the user's emotional response data. For example, it prioritizes the offering of coupons that have a high number of positive emotional responses. The coupon get button display function also automatically selects and provides a coupon that will most satisfy the user based on the emotion estimation data. For example, it customizes the content of the coupon based on past emotional responses. This makes it possible to analyze the user's emotional response and reflect this in the next coupon offering.

[0070] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0071] The coupon provision system can also analyze a user's health data and provide coupons according to their health condition. For example, based on the user's step count data, a fitness-related coupon can be provided when a certain number of steps is achieved. The coupon provision system can also analyze the user's food records and provide coupons for nutritionally balanced foods. Furthermore, based on the user's sleep data, it can provide coupons for products and services that support good quality sleep. This makes it possible to provide personalized coupons according to the user's health condition.

[0072] The coupon providing system can also provide coupons based on the user's hobbies and interests. For example, if the user likes music, coupons for concert tickets or music streaming services can be provided. If the user likes movies, coupons for movie theater tickets or movie streaming services can be provided. Furthermore, if the user likes traveling, coupons related to travel or discount coupons for accommodations can be provided. In this way, coupons can be provided that match the user's hobbies and interests.

[0073] The coupon providing system can also provide coupons according to the user's life events. For example, a special discount coupon can be provided for the user's birthday. Coupons for related products can also be provided for special occasions such as wedding anniversaries and children's birthdays. Furthermore, when a user starts a new job or moves, coupons for necessary products or services can also be provided. In this way, coupons can be provided according to the user's life events.

[0074] The coupon provision system can also analyze a user's social media activity and provide relevant coupons. For example, if a user mentions a particular brand or product on social media, a coupon for that brand or product can be provided. Also, if a user participates in a particular event, a coupon related to that event can be provided. Furthermore, it is possible to provide similar coupons based on coupons used by the user's followers and friends. This makes it possible to provide coupons that correspond to the user's social media activity.

[0075] The coupon providing system can also provide coupons that can only be used in a specific area based on the user's location information. For example, if the user is in a specific shopping mall, coupons that can be used at stores in the mall can be provided. Also, if the user is in a specific tourist spot, coupons for restaurants and souvenir shops in the area can be provided. Furthermore, if the user is at a specific event venue, coupons related to that event can be provided. In this way, coupons can be provided according to the user's location information.

[0076] The coupon provision system can use the emotion estimation function to provide refreshment coupons according to the user's emotional state. For example, if the user is feeling stressed, coupons for relaxation facilities or massages can be provided. If the user is tired, coupons for cafes or restaurants can be provided. Furthermore, if the user is in a positive emotional state, coupons for entertainment facilities or activities can be provided. In this way, refreshment coupons can be provided according to the user's emotional state.

[0077] The coupon provision system can use the emotion estimation function to provide feedback according to the user's emotional state. For example, if the user is in a negative emotional state, it can provide an encouraging message or positive feedback. Alternatively, if the user is in a positive emotional state, it can provide a message of praise or words of gratitude. Furthermore, it is possible to collect feedback according to the user's emotional state to be reflected in the next coupon provision. This makes it possible to provide feedback according to the user's emotional state.

[0078] The coupon provision system can use the emotion estimation function to provide entertainment coupons according to the user's emotional state. For example, if the user is bored, coupons for movie theaters or game centers can be provided. If the user is excited, coupons for amusement parks or sporting events can be provided. Furthermore, if the user wants to relax, coupons for spas or hot spring facilities can be provided. In this way, entertainment coupons can be provided according to the user's emotional state.

[0079] The coupon provision system can use the emotion estimation function to provide health support coupons according to the user's emotional state. For example, if the user is feeling stressed, coupons for yoga or meditation can be provided. If the user is tired, coupons for fitness gyms or personal training can be provided. Furthermore, if the user is in a positive emotional state, coupons for health foods or supplements can be provided. In this way, health support coupons can be provided according to the user's emotional state.

[0080] The coupon provision system can use the emotion estimation function to provide special event coupons according to the user's emotional state. For example, if the user is excited, coupons for live concerts or sporting events can be provided. If the user wants to relax, coupons for art galleries or museums can be provided. Furthermore, if the user is in a positive emotional state, coupons for special dinners or date spots can be provided. In this way, special event coupons can be provided according to the user's emotional state.

[0081] The processing flow of the second embodiment will be briefly explained below.

[0082] Step 1: The wake-up alarm function sounds an alarm at the time set by the user. For example, if a user sets an alarm for 7:00 a.m. every morning, the alarm will sound at that time. The wake-up alarm function also has a snooze function, and if the user presses the snooze button, the alarm will sound again after a certain period of time. Furthermore, the wake-up alarm function allows the user to select the type of alarm sound. For example, there are multiple alarm sounds to choose from, such as music or nature sounds. Step 2: The audio ad playback function plays an audio ad as an alarm sound. For example, a generation AI (text generation AI or multimodal generation AI) analyzes the user's behavioral data, generates the optimal ad copy, and reads it out loud. The audio ad playback function can also adjust the playback timing and volume of the ad. For example, it can play ads related to stores and services that the user frequently uses. Step 3: The coupon acquisition button display function displays a coupon acquisition button on the smartphone screen while the alarm is ringing. For example, if the user presses the coupon acquisition button, the alarm will stop and the user will be able to acquire a coupon. Also, if an advertisement for a company that does not offer coupons is played, it will be changed to a PayPay points acquisition button. For example, if the coupon acquisition button is pressed, a coupon will be provided within the PayPay app.

[0083] 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.

[0084] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of 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.

[0085] 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.

[0086] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0087] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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).

[0092] 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.

[0093] 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.

[0094] 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.

[0095] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0096] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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).

[0107] 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.

[0108] 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.

[0109] 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.

[0110] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0111] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0127] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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).

[0136] 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.

[0137] 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."

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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]

[0150] 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. Wake-up alarm function and An audio ad playback function that plays audio ads, A coupon acquisition button display function for displaying a coupon acquisition button is provided. A system characterized by:

2. The wake-up alarm function Analyzes the user's sleep patterns, predicts the optimal time to wake up, and sounds an alarm 2. The system of claim 1.

3. The wake-up alarm function The alarm sound is combined with natural and environmental sounds to enhance the user's relaxation.

2. The system of claim 1.

4. The wake-up alarm function Select alarm sounds according to the user's emotional state to reduce stress 2. The system of claim 1.

5. The wake-up alarm function The alarm function will be enhanced with a weather forecast or news reading function to help users gather information in the morning.

2. The system of claim 1.

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