system

Abstract

We provide the system. [Solution] An application installed on the information processing device provides a means for collecting user voice input, A means of sending collected audio data to a server and converting it into text data using speech recognition, A means of performing sentiment analysis based on text data and generating statements according to the analysis results, A means of synthesizing and outputting the generated speech using a voice specified by the user, A means of continuously recording the user's mental state and managing trends in change, A means of determining and proposing the need for expert intervention based on recorded data, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern information technology society, many people are suffering from mental health problems such as stress and anxiety. In particular, they may not have time to get mental support during their daily busy lives, and the situation may deteriorate without their awareness. Also, it is difficult to determine whether it is necessary to consult an expert, and there is a possibility of missing that timing. Therefore, there is a need for a mechanism that can easily support mental health with a familiar voice in daily life and enable people to notice the changes.

Means for Solving the Problems

[0005] This invention is a personalized mental health support system designed to trigger a user's preference for a specific person's voice. Through an application installed on an information processing device, it collects the user's voice input, transmits it to a server for speech recognition, and converts it into text data. Furthermore, it performs sentiment analysis based on this data, generates statements corresponding to the results, and synthesizes and outputs them using a voice set by the user. By continuously recording the user's mental state and suggesting professional intervention as needed, the system provides a mechanism for effectively managing the user's mental health.

[0006] An "information processing device" is an electronic device that has the functions of inputting, processing, storing, and outputting data.

[0007] An "application" is a software program that runs on an information processing device to achieve a specific purpose.

[0008] A "user" is an individual who uses this system to receive mental health support.

[0009] "Voice input" refers to the act or process of a user sending voice data to a system using an input device such as a microphone.

[0010] "Audio data" refers to digital data collected through voice input.

[0011] A "server" is a large computer system that provides specific services or functions to information processing devices via a network.

[0012] "Speech recognition" refers to a technology or process that processes audio data and converts its content into text data.

[0013] "Text data" refers to character information generated by speech recognition.

[0014] "Sentiment analysis" refers to a technology or method for analyzing text data to estimate the user's sentiment state.

[0015] "Utterance" refers to the content of a message generated based on the results of sentiment analysis.

[0016] "Speech synthesis" refers to a technology or process for artificially creating speech based on the generated text data.

[0017] "Mental state" refers to the psychological and emotional health state of the user.

[0018] "Expert" refers to a profession that has knowledge and experience in mental health and has the qualification to provide guidance and treatment upon consultation.

Brief Description of Drawings

[0019] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [[ID=3C]] [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. <000009C> [Figure 9] Shows an emotion map to which a plurality of emotions are mapped. [Figure 10] Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0020] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0021] First, the language used in the following description will be described.

[0022] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units 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), and the like.

[0023] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0024] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0025] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] As shown in Figure 1, the 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.

[0030] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0032] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0039] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0040] This invention provides a system that allows users to easily receive mental health support in their daily lives. As an embodiment, it utilizes an application installed on an information processing device. This application receives voice input from the user and processes it in cooperation with a server. The details are described below.

[0041] First, the user installs the application on the information processing device and records a voice sample. The user can choose the voice of someone they are familiar with for this voice sample. This prepares the system to provide feedback in the user's preferred voice.

[0042] Next, the device notifies the user at a designated time each day, requesting voice input about their mood and physical condition for the day. The user's responses become important data in the process.

[0043] The input voice data is sent from the terminal to the server. The server receives the transmitted voice data and converts it into text using speech recognition technology. Next, the server performs sentiment analysis on the text data. Based on the results of this analysis, the user's emotions and stress level at that time are evaluated.

[0044] The server then generates appropriate advice and words of encouragement for the user based on the sentiment analysis results. The generated messages are then converted into a voice set by the user using speech synthesis technology.

[0045] This audio is ultimately played from the device, providing natural feedback to the user. For example, if a user responds in the morning with "I'm feeling a bit down today," they might hear a friendly voice offering advice such as, "Don't push yourself, take it slow."

[0046] Furthermore, the server accumulates this daily data, allowing for an analysis of long-term changes in the user's mental state. This data can also be used to make decisions regarding recommending consultations with specialists as needed.

[0047] In this way, the present invention can effectively manage the user's mental health and provide daily support. This system achieves the ease of use and immediacy that were difficult to achieve with conventional mental health care methods, and has a structure that makes it easy for busy modern people to use continuously.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The user launches an application installed on the information processing device and registers an account. The user records a voice sample and selects the voice they want to use. This recording data is saved by the device and used later for speech synthesis.

[0051] Step 2:

[0052] Every morning at a designated time, the device sends a notification to the user, asking in a voice, "How are you feeling today?" The notification uses the voice of a close friend or family member that the user has set.

[0053] Step 3:

[0054] The user uses voice input to describe their mood or state of mind for the day. For example, they might say, "I'm a little tired today."

[0055] Step 4:

[0056] The device records the user's voice input and sends that audio data to the server in real time.

[0057] Step 5:

[0058] After the server receives the audio data, it uses speech recognition technology to convert the data into text format.

[0059] Step 6:

[0060] The server analyzes the converted text data to perform sentiment analysis. This process evaluates the user's emotional state and stress level.

[0061] Step 7:

[0062] Based on the results of sentiment analysis, the server generates advice and encouraging messages tailored to the user.

[0063] Step 8:

[0064] The server uses speech synthesis technology to convert the generated message into the user's specified voice.

[0065] Step 9:

[0066] The synthesized audio file is sent to the device, and the user receives audio feedback.

[0067] Step 10:

[0068] The server stores sentiment analysis and user response results in a database to track long-term changes in mental state.

[0069] Step 11:

[0070] If necessary, the device will present the user with a suggestion such as, "Do you need to consult with an expert?"

[0071] This process allows users to have their mental health continuously monitored and receive support in a friendly voice when needed.

[0072] (Example 1)

[0073] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0074] In recent years, support for maintaining mental health has become increasingly important. However, traditional mental health care methods have been difficult for users to access and respond to immediately, making continuous use challenging for busy modern people. Furthermore, there is a lack of objective data to appropriately determine when professionals should intervene based on the user's psychological state.

[0075] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0076] In this invention, the server includes means for converting speech into text information using speech recognition technology, means for performing sentiment analysis and generating a response based on the analysis results, and means for determining and suggesting expert intervention based on the recorded information. This makes it possible to provide user-friendly and immediate management of the user's psychological health, and to appropriately suggest expert intervention when necessary.

[0077] An "information processing device" is a device equipped with functions for receiving, processing, and transmitting data.

[0078] "Speech recognition technology" is a technology that analyzes speech signals and converts their content into text data that a computer can understand.

[0079] "Text information" refers to character data converted using speech recognition technology.

[0080] "Sentiment analysis" is the process of analyzing text information to evaluate the speaker's emotions and psychological state.

[0081] "Speech synthesis technology" is a technology that artificially generates speech based on text data.

[0082] "Psychological information" refers to data about the user's mental state, including emotions, psychological tendencies, and stress levels.

[0083] "Expert intervention" refers to the appropriate involvement of a professional in the user's condition to provide psychological or medical guidance and advice.

[0084] This embodiment of the invention is an information processing system for supporting the psychological health of users. The components of this system and the technologies supporting them are described below.

[0085] The user first installs a dedicated application on the information processing device. This allows the user to record the voice of a familiar person and register it as a voice sample. This sample will later be used to generate voice feedback.

[0086] Next, the device notifies the user at a designated time each day, requesting voice input regarding their mood and physical condition for the day. The voice data provided by the user forms the core of the system and is used to evaluate their mental state.

[0087] The device sends voice data to the server. The server is equipped with speech recognition technology, where the voice data is converted into text data. For example, if the user says, "I'm feeling a little stressed today," it will be converted into text.

[0088] The server performs sentiment analysis based on text data. Using a generative AI model, it evaluates the user's emotions and psychological tendencies, and generates appropriate advice and encouraging messages based on the results. The generated text messages are converted into speech using speech synthesis technology with a voice sample set by the user.

[0089] Ultimately, the device can play synthesized voices to the user, providing friendly feedback. For example, the user might hear gentle advice such as, "Don't push yourself, take it slow."

[0090] Furthermore, the server continuously accumulates this data and analyzes changes in the user's mental state over the long term. This data is used when expert judgment is needed and provides information to suggest the need for timely intervention.

[0091] A concrete example of a prompt might be, "Convert today's voice input from the user to text, analyze the user's sentiment from that text, and generate appropriate advice."

[0092] In this way, the system possesses both user-friendliness and immediacy, enabling it to effectively support the mental health of today's busy users.

[0093] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0094] Step 1:

[0095] The user installs a dedicated application on the information processing device. During this process, the user records the voice of someone they feel familiar with and registers it as a voice sample in the application. This voice sample is used in subsequent processing for feedback generation. The input is the user's voice, and the output is the saved voice sample.

[0096] Step 2:

[0097] The device sends a notification to the user at a set time and requests voice input regarding their daily mood and physical condition. It uses the system clock to verify that the user has specified the time. The input is system clock information, and the output is the notification to the user.

[0098] Step 3:

[0099] The user inputs voice data about their mood and physical condition for the day in response to notifications from their device. This voice data is important for later analysis. The input is the user's voice, and the output is the voice data stored on the device.

[0100] Step 4:

[0101] The terminal sends the recorded audio data to the server. Upon successful transmission of the audio data, the server begins the receiving process. The input is the audio data from the terminal, and the output is the audio data sent to the server.

[0102] Step 5:

[0103] The server converts the received audio data into text data using speech recognition technology. Here, the speech recognition engine operates, converting the audio signal into a string of characters. The input is audio data, and the output is text data.

[0104] Step 6:

[0105] The server uses a generative AI model to perform sentiment analysis on text data and evaluate the user's psychological state. The model uses natural language processing techniques to analyze the text and assess the user's emotions. The input is text data, and the output is the result of the sentiment analysis.

[0106] Step 7:

[0107] The server generates personalized advice and encouraging messages for the user based on the sentiment analysis results. This process utilizes a generative AI model to produce text messages. The input is the sentiment analysis results, and the output is the generated text message.

[0108] Step 8:

[0109] The server converts the generated text message using speech synthesis technology and creates voice feedback using the voice sample set by the user. The speech synthesis engine operates to create a friendly feedback voice. The input is a text message, and the output is synthesized speech.

[0110] Step 9:

[0111] The terminal plays synthesized speech received from the server and provides it to the user as feedback. When the voice playback device is activated, the user can hear appropriate feedback. The input is synthesized speech from the server, and the output is the played voice feedback.

[0112] Step 10:

[0113] The server stores voice data and sentiment analysis results to track changes in the user's mental state over time. This allows it to indicate when the need for professional consultation arises. The input is daily voice data and sentiment analysis results, and the output is the accumulated psychological data of the user.

[0114] (Application Example 1)

[0115] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0116] Modern consumers seek to understand their own mental state through their everyday shopping experiences and make better purchasing decisions. However, existing systems lack the means to adequately link mental health with purchasing activities, making it a challenge to improve consumer mental well-being and the purchasing experience.

[0117] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0118] In this invention, the server includes means for performing sentiment analysis based on the user's voice input and generating statements corresponding to the results, means for synthesizing the generated statements with a voice specified by the user, and means for providing product information based on the user's voice input and making recommendations to improve the user's willingness to purchase. This enables the user to make the optimal product selection while taking into account their own mental health condition.

[0119] An "information processing device" is a device that uses a computer to collect, process, and analyze data.

[0120] An "application" is a program installed on an information processing device to perform a specific function.

[0121] "Voice input" refers to the act of a device capturing the user's voice and using it as data.

[0122] A "server" is a computer system that receives and processes information from other devices via a network.

[0123] "Speech recognition" is a technology that automatically converts speech into text data.

[0124] "Text data" refers to character information converted from speech.

[0125] "Sentiment analysis" is a technique that analyzes text data to determine a person's emotions and psychological state.

[0126] "Means of generating statements" refers to the process of creating appropriate messages based on analysis results.

[0127] "Speech synthesis" is a technology that converts text information into a speech format that can be played back.

[0128] "Mental state" refers to an indicator of an individual's psychological health and stress level.

[0129] "Product information" refers to providing consumers with product information that can be used as a reference when making purchasing decisions.

[0130] "Purchase intent" refers to the psychological state in which consumers feel the desire to buy a product.

[0131] The ideal configuration for this system involves an information processing unit, a server, and a smart display device. The information processing unit plays the role of routinely collecting user voice input. When a user provides voice input through a smart device, that data is immediately sent to the server. The server uses speech recognition to convert this voice into text data.

[0132] The text data is further analyzed by an emotion analysis engine to evaluate the user's emotional state and mental burden at that time. Based on this analysis, the server starts the process of generating the most appropriate statements for the user using a generative AI model. The statements are output using speech synthesis technology in the voice of a close person selected by the user and provided to the user as feedback.

[0133] Furthermore, this system also has a function to support users' purchasing activities. It provides voice-guided product recommendations tailored to the user's mental state, psychologically supporting their desire to buy. For example, if a user inputs, "I feel like relaxing today," the system will provide a friendly voice recommendation such as, "We have a recommended aromatherapy candle," helping to pique their interest in a specific section or product.

[0134] The following is an example of how this system works, using prompt messages.

[0135] "Analyze the user's voice input for emotional analysis, and based on the results, generate appropriate product information in a gentle tone."

[0136] This design allows users to naturally care for their mental health in their daily lives while also having a better shopping experience.

[0137] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0138] Step 1:

[0139] The user provides voice input through a smart device. The input is the user's voice, which is captured by the smart device's microphone and processed by the information processing unit. The user can freely talk about their everyday emotions and physical state.

[0140] Step 2:

[0141] The terminal receives the audio data and sends it to the server. Using this audio data as input, the server runs a speech recognition algorithm and converts it into text data. In this way, the audio input is converted into a format that can be processed by a machine.

[0142] Step 3:

[0143] The server sends the converted text data to the sentiment analysis engine. The sentiment analysis engine analyzes the input text data and outputs the user's emotions and stress levels as numerical values ​​or categories. This allows the user's mental status to be evaluated.

[0144] Step 4:

[0145] The server generates feedback messages using a generative AI model based on the results of sentiment analysis. This model generates appropriate message candidates using the prompt "Analyze the user's voice input and generate appropriate product information in a gentle tone based on the results."

[0146] Step 5:

[0147] The server generates a message and forwards it to a speech synthesis engine. The speech synthesis engine converts the input message into a voice preferred by the user and outputs the voice information. This provides the user with user-friendly feedback.

[0148] Step 6:

[0149] The device plays back audio feedback to the user. Through the played feedback, the user can receive advice on their mental health and product recommendations tailored to their emotional state.

[0150] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0151] This invention provides an information processing system for more precisely recognizing user emotions and providing personalized mental health support. This system functions using an application installed on an information processing device and a server.

[0152] First, the user installs the application on their information processing device, records a voice sample, and selects the voice to use. This selected voice sample is then stored on the device as basic data for speech synthesis.

[0153] Providing daily mental health support begins with the device sending a notification at a designated time, asking the user, "How are you feeling today?" Crucially, the emotion engine recognizes the user's facial expressions, tone of voice, and verbal responses in real time. For example, even if the user utters a short phrase like, "I'm feeling a little down," the system can analyze facial tension and tone of voice to grasp the nuances in detail.

[0154] The user's responses are recorded by the device, and the audio data is quickly sent to the server. The server uses speech recognition technology to convert the recorded data into text, and then a detailed sentiment analysis is performed by an emotion engine. The emotion engine quantifies the user's emotional state based on their series of responses and the content of their words, and stores this data.

[0155] Based on this detailed emotional data, the server generates advice and words of encouragement that are best suited to the user. The generated message is synthesized into a pre-selected, pleasant voice and fed back to the user via the device. For example, a voice message such as "Let's take it easy today and move forward one step at a time" might be played in the voice of the user's favorite person.

[0156] Furthermore, the emotion engine analyzes long-term accumulated emotional data to create individual emotional profiles for each user. This serves as a guide for users to deepen their self-understanding and maintain better mental health. In addition, if the accumulated data indicates that support from a professional is needed, the server will provide referrals and consultation suggestions to appropriate professionals.

[0157] Through these procedures, the present invention provides users with accurate and personalized mental health support, enabling them to live their daily lives with support. This allows users to maintain better mental health and receive appropriate intervention when needed.

[0158] The following describes the processing flow.

[0159] Step 1:

[0160] The user installs the application on the information processing device. Upon first launch, they create an account and record and save a voice sample of someone they consider close to them.

[0161] Step 2:

[0162] Every morning, the device notifies the user at a designated time, asking in a voice, "How are you feeling today?" This voice is synthesized using the voice of a person the user likes.

[0163] Step 3:

[0164] The user answers aloud to the device about their mood and condition for the day. Their facial expressions are also analyzed by the camera during this process.

[0165] Step 4:

[0166] The device records the user's voice and facial expression data and sends it to the server.

[0167] Step 5:

[0168] The server converts the received audio into text using speech recognition technology, and an emotion engine analyzes the user's emotional state in detail from the text and facial expressions.

[0169] Step 6:

[0170] Based on the results of the sentiment analysis, the server generates advice and messages tailored to the user. For example, if the user feels "a little stressed," it will generate a message such as, "It would be good to make time to relax."

[0171] Step 7:

[0172] The generated message is synthesized using a voice setting pre-configured by the user and then sent to the device.

[0173] Step 8:

[0174] The device plays synthesized speech, providing feedback to the user in a friendly voice.

[0175] Step 9:

[0176] The server collects emotional data and creates a long-term emotional profile of the user. This profile is updated regularly to help the user understand themselves better.

[0177] Step 10:

[0178] If necessary, the server will analyze the data it has accumulated, and if it is determined that expert intervention is appropriate, it will introduce the user to an expert or suggest a consultation.

[0179] This series of steps allows users to receive continuous feedback and support in understanding and improving their own mental state.

[0180] (Example 2)

[0181] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0182] In recent years, as the management of individual mental health has become increasingly important, establishing means to provide individually tailored mental health support is a challenge. In particular, there is a need to accurately grasp the emotional state of users in real time and provide prompt, individualized advice based on that assessment. Furthermore, there is a lack of mechanisms to effectively manage long-term changes in mental state and appropriately suggest professional intervention when necessary.

[0183] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0184] In this invention, the server includes means for converting audio data into text data by acoustic analysis, means for generating a response according to the analysis results by emotion analysis, and means for accumulating emotion data and profiling an individual's emotional characteristics. This makes it possible to understand the user's emotional state in detail, manage long-term changes in their mental state, and provide timely and optimal mental health support.

[0185] An "information processing device" is an electronic device that has the function of processing data.

[0186] A "program" is a set of instructions written for a computer to perform a specific task.

[0187] "User" refers to an individual who uses this system.

[0188] "Voice input" refers to audio data that a user provides to an information processing device via a microphone.

[0189] "Communication equipment" refers to devices or networks used for sending and receiving data.

[0190] "Acoustic analysis" is the process of analyzing audio data and converting its content into text data.

[0191] "Text data" refers to text information that is obtained after voice input has been converted into text.

[0192] "Sentiment analysis" refers to data processing performed to infer a user's emotions from text data.

[0193] A "response" is a message or instruction generated and provided to the user based on the results of sentiment analysis.

[0194] "Speech synthesis" is a technology that generates speech based on text data.

[0195] "Mental state" refers to the psychological state related to the user's mental health.

[0196] "Emotional characteristics" refer to profile information that shows the user's emotional tendencies and patterns.

[0197] "Expert intervention" refers to guidance or advice provided by individuals with specialized knowledge.

[0198] This invention is a system that recognizes a user's emotional state in real time and provides individually tailored mental health support. The system functions through a program installed on an information processing device and a communication device.

[0199] The terminal is an information processing device equipped with a microphone for acquiring the user's voice input. The user records their voice through an application and registers it as basic data for speech synthesis. This voice data is stored on the user's terminal.

[0200] The server converts the audio data acquired using speech recognition technology into text data. Specifically, the server uses a generative AI model to analyze the information extracted from the audio and quantify the user's emotions.

[0201] Depending on the user's emotional state, the server generates words of encouragement and advice. This utilizes a generative AI model with individually tailored prompts. For example, if the user's emotional analysis indicates they are "feeling a little down," the server will generate a message such as "Don't push yourself today, take it easy and rest," and deliver it as synthesized speech in a voice selected by the user.

[0202] The synthesized voice message is delivered to the user through the device. This allows the user to receive appropriate support tailored to their emotional state. An example of a prompt is the instruction, "Create a support message for when the user feels 'a little down'."

[0203] In this way, the system continuously accumulates user emotional data and supports the improvement of users' mental health through long-term analysis. If it is determined that professional intervention is necessary, it is possible to make such a suggestion through the server.

[0204] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0205] Step 1:

[0206] The user launches the application and records a voice sample. The application receives an audio signal acquired through the microphone as input. This audio signal is stored on the device as basic data for speech synthesis. Specifically, the user presses the record button and records a specific phrase in their own voice.

[0207] Step 2:

[0208] The device sends a notification at a specified time. The system uses pre-configured time information as input. The device then verbally outputs the message, "How are you feeling today?", prompting the user for a response. Specifically, the device's alarm function activates, and the message is played through the speaker.

[0209] Step 3:

[0210] The device records the user's response and sends it to the server as audio data. It receives an audio signal generated by the user's response as input. This audio signal is sent to the server via the network. Specifically, after recording begins, the device compresses the audio data and uploads it at high speed.

[0211] Step 4:

[0212] The server receives audio data and converts it into text data through acoustic analysis. The input is audio data sent from the terminal. The server uses a speech recognition algorithm to convert the audio into text and passes the output to the sentiment analysis process. Specifically, the server starts the speech recognition engine and converts the data into text.

[0213] Step 5:

[0214] The server performs sentiment analysis based on text data. The input is text data converted from speech. The server uses a generative AI model to quantify the user's emotions from the text data and stores the results in a database. Specifically, the AI ​​engine extracts emotional characteristics from the text and generates a numerical score.

[0215] Step 6:

[0216] The server generates an appropriate feedback message based on the results of sentiment analysis. The input is numerical data obtained from sentiment analysis. The server uses a generative AI model to create an appropriate message and synthesizes it in the voice selected by the user. Specifically, the server designs the message based on the prompt text and goes through a process of synthesizing it from text to speech.

[0217] Step 7:

[0218] The device plays a synthesized voice message to the user. It receives an audio file from the server as input. This file is delivered to the user as audio information through the device's audio system. Specifically, the device downloads the audio file and plays it through its speaker.

[0219] (Application Example 2)

[0220] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0221] In modern society, there is a demand for the precise recognition and appropriate response to individual emotions, but conventional information systems have not been able to adequately achieve this. Furthermore, while providing services tailored to the emotions of customers in physical stores is considered to contribute to improving the quality of customer service, it is difficult to achieve with existing methods.

[0222] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0223] In this invention, the server includes means for collecting voice input from users, means for converting the collected voice data into symbolic data by speech recognition, means for performing emotion analysis based on the symbolic data and generating statements according to the analysis results, and means for generating and outputting guidance according to the emotions of the customers using an information machine. This enables precise responses to individual emotions and personalized responses according to the emotional state of the customers.

[0224] An "information processing device" is an electronic device used to input, process, and output data.

[0225] An "application program" is software installed on an information processing device to perform a specific function.

[0226] A "user" is an individual who receives services by operating an information processing device or application program.

[0227] "Voice input" refers to sound data that a user provides to an information processing device as voice.

[0228] A "central computing system" is a centrally managed group of computers used to process and analyze collected data.

[0229] "Speech recognition" is a technology that converts voice input into a format such as text.

[0230] "Symbolic data" refers to digital data such as text converted by speech recognition.

[0231] "Emotional analysis" is a technology that analyzes a user's emotional state from text or audio.

[0232] "Means for generating statements" refers to the technology of creating appropriate response sentences based on sentiment analysis results.

[0233] A "speech synthesis model" is a technological model for reproducing digital data as speech.

[0234] An "information machine" is an electronic control device that provides information and guidance.

[0235] "Means for generating and outputting guidance" refers to technologies that present appropriate information to users in the form of audio or text.

[0236] "Means for determining and proposing the need for expert intervention" refers to techniques for proposing necessary expert advice based on accumulated data.

[0237] This invention is an information processing system that provides better service to individual users by precisely recognizing their emotions and personalizing customer service and guidance in physical stores. This system includes an information processing device, a central processing system, and an information machine.

[0238] The server uses application programs installed on an information processing device equipped with a microphone to receive voice input from users. The voice data is converted into symbolic data and sent to a central processing system for sentiment analysis. Specific software used for processing includes dedicated libraries for speech recognition and sentiment analysis.

[0239] The central computing system uses the collected data to analyze the user's emotional state. This emotional analysis incorporates facial expression analysis and voice tone analysis technologies, and the resulting emotional data is used to generate the optimal response for the user. A speech synthesis model is used to output the generated response as speech.

[0240] Information machines provide customers with emotionally responsive guidance via voice and displays. For example, a tired customer might be offered a thoughtful message such as, "Let me show you a relaxing area." Conversely, a cheerful customer might be offered proactive suggestions such as, "Let me introduce you to our new products," thereby enhancing the quality of customer service.

[0241] As a concrete example, consider the case where this system is implemented in the information center of a department store. This system analyzes the facial expressions and voices of customers and provides appropriate guidance in real time according to their emotions. An example of a prompt in the generative AI model might be: "Based on the customer's emotional data, automatically generate the most appropriate greeting and guidance. Also, analyze the emotional profile over the long term and suggest ways to provide special services to customers who visit frequently."

[0242] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0243] Step 1:

[0244] The terminal uses a microphone to receive voice input from the user. By incorporating the input voice data into the system, data collection begins.

[0245] Step 2:

[0246] The terminal collects audio data and transmits it to a central processing system, where it is converted into symbolic data using speech recognition software. The speech recognition engine then extracts text data from the audio data. The resulting text data serves as the basis for sentiment analysis.

[0247] Step 3:

[0248] The server performs sentiment analysis based on symbolic data. Here, a sentiment analysis engine is used to analyze and quantify the user's emotional state from the symbolic data. The analysis results are output as digital data indicating the user's specific emotional state.

[0249] Step 4:

[0250] The central processing system generates the optimal response based on the analysis results. An AI model is used to create the optimal message for the user, inferred from emotional data. This model outputs an appropriate response based on the generated prompt.

[0251] Step 5:

[0252] The server synthesizes the speech using the user's specified voice, and the terminal outputs it as audio. Text data is converted into audio data by a speech synthesis engine and played back using the user's set voice.

[0253] Step 6:

[0254] The device records voice data, and the server records the data to suggest professional intervention as needed. Long-term data accumulation allows for the detection of important mental health trends and outputs information for intervention as required.

[0255] Step 7:

[0256] The server controls the information machines and provides customers with emotionally resonant guidance. It generates guidance that matches the store environment in real time, improving the user experience.

[0257] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0258] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0259] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0260] [Second Embodiment]

[0261] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0262] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0263] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0264] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0265] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0266] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0267] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0268] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0269] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0270] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0271] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0272] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0273] This invention provides a system that allows users to easily receive mental health support in their daily lives. As an embodiment, it utilizes an application installed on an information processing device. This application receives voice input from the user and processes it in cooperation with a server. The details are described below.

[0274] First, the user installs the application on the information processing device and records a voice sample. The user can choose the voice of someone they are familiar with for this voice sample. This prepares the system to provide feedback in the user's preferred voice.

[0275] Next, the device notifies the user at a designated time each day, requesting voice input about their mood and physical condition for the day. The user's responses become important data in the process.

[0276] The input voice data is sent from the terminal to the server. The server receives the transmitted voice data and converts it into text using speech recognition technology. Next, the server performs sentiment analysis on the text data. Based on the results of this analysis, the user's emotions and stress level at that time are evaluated.

[0277] The server then generates appropriate advice and words of encouragement for the user based on the sentiment analysis results. The generated messages are then converted into a voice set by the user using speech synthesis technology.

[0278] This audio is ultimately played from the device, providing natural feedback to the user. For example, if a user answers "I'm feeling a bit down today" in the morning, they might hear a friendly voice offering advice such as, "Don't push yourself, take it slow."

[0279] Furthermore, the server accumulates this daily data, allowing for an analysis of long-term changes in the user's mental state. This data can also be used to make decisions regarding recommending consultations with specialists as needed.

[0280] In this way, the present invention can effectively manage the user's mental health and provide daily support. This system achieves the ease of use and immediacy that were difficult to achieve with conventional mental health care methods, and has a structure that makes it easy for busy modern people to use continuously.

[0281] The following describes the processing flow.

[0282] Step 1:

[0283] The user launches an application installed on the information processing device and performs account registration. The user records a voice sample and selects the voice to be used. This recorded data is saved by the terminal and used for subsequent voice synthesis.

[0284] Step 2:

[0285] Every morning, the terminal sends a notification to the user at the specified time, asking in voice, "How are you feeling today?" The voice of a familiar person set by the user is used for the notification.

[0286] Step 3:

[0287] The user makes a voice input to the terminal about their mood and state for that day. For example, answering "I'm a little tired today."

[0288] Step 4:

[0289] The terminal records the user's voice input and sends the voice data to the server in real time.

[0290] Step 5:

[0291] After receiving the voice data, the server uses voice recognition technology to convert the data into text format.

[0292] Step 6:

[0293] The server analyzes the converted text data to perform sentiment analysis. The user's emotional state and stress level are evaluated in this process.

[0294] Step 7:

[0295] Based on the results of the sentiment analysis, the server generates advice or encouraging messages suitable for the user.

[0296] Step 8:

[0297] The server uses voice synthesis technology to convert the generated message into the voice specified by the user.

[0298] Step 9:

[0299] The synthesized voice file is sent to the terminal, and voice feedback is provided to the user.

[0300] Step 10:

[0301] The server accumulates the sentiment analysis and the user's reaction results in the database to track the long-term changes in the mental state.

[0302] Step 11:

[0303] If necessary, the terminal presents a proposal such as "Do you need to consult an expert?" to the user.

[0304] Through this process, the user can continuously manage their mental health and receive support in a familiar voice when needed.

[0305] (Example 1)

[0306] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0307] In recent years, support for maintaining mental health has been emphasized. However, in traditional mental health care methods, it is difficult for users to seek familiarity and immediacy, and it is difficult for busy modern people to use continuously. There is also a problem that there is a lack of objective data for experts to appropriately judge the timing of intervention in the user's psychological state.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0309] In this invention, the server includes means for converting speech into text information using speech recognition technology, means for performing sentiment analysis and generating a response based on the analysis results, and means for determining and suggesting expert intervention based on the recorded information. This makes it possible to provide user-friendly and immediate management of the user's psychological health, and to appropriately suggest expert intervention when necessary.

[0310] An "information processing device" is a device equipped with functions for receiving, processing, and transmitting data.

[0311] "Speech recognition technology" is a technology that analyzes speech signals and converts their content into text data that a computer can understand.

[0312] "Text information" refers to character data converted using speech recognition technology.

[0313] "Sentiment analysis" is the process of analyzing text information to evaluate the speaker's emotions and psychological state.

[0314] "Speech synthesis technology" is a technology that artificially generates speech based on text data.

[0315] "Psychological information" refers to data about the user's mental state, including emotions, psychological tendencies, and stress levels.

[0316] "Expert intervention" refers to the appropriate involvement of a professional in the user's condition to provide psychological or medical guidance and advice.

[0317] This embodiment of the invention is an information processing system for supporting the psychological health of users. The components of this system and the technologies supporting them are described below.

[0318] The user first installs a dedicated application on the information processing device. This allows the user to record the voice of a familiar person and register it as a voice sample. This sample will later be used to generate voice feedback.

[0319] Next, the device notifies the user at a designated time each day, requesting voice input regarding their mood and physical condition for the day. The voice data provided by the user forms the core of the system and is used to evaluate their mental state.

[0320] The device sends voice data to the server. The server is equipped with speech recognition technology, where the voice data is converted into text data. For example, if the user says, "I'm feeling a little stressed today," it will be converted into text.

[0321] The server performs sentiment analysis based on text data. Using a generative AI model, it evaluates the user's emotions and psychological tendencies, and generates appropriate advice and encouraging messages based on the results. The generated text messages are converted into speech using speech synthesis technology with a voice sample set by the user.

[0322] Ultimately, the device can play synthesized voices to the user, providing friendly feedback. For example, the user might hear gentle advice such as, "Don't push yourself, take it slow."

[0323] Furthermore, the server continuously accumulates this data and analyzes changes in the user's mental state over the long term. This data is used when expert judgment is needed and provides information to suggest the need for timely intervention.

[0324] A concrete example of a prompt might be, "Convert today's voice input from the user to text, analyze the user's sentiment from that text, and generate appropriate advice."

[0325] In this way, the system possesses both user-friendliness and immediacy, enabling it to effectively support the mental health of today's busy users.

[0326] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0327] Step 1:

[0328] The user installs a dedicated application on the information processing device. During this process, the user records the voice of someone they feel familiar with and registers it as a voice sample in the application. This voice sample is used in subsequent processing for feedback generation. The input is the user's voice, and the output is the saved voice sample.

[0329] Step 2:

[0330] The device sends a notification to the user at a set time and requests voice input regarding their daily mood and physical condition. It uses the system clock to verify that the user has specified the time. The input is system clock information, and the output is the notification to the user.

[0331] Step 3:

[0332] The user inputs voice data about their mood and physical condition for the day in response to notifications from their device. This voice data is important for later analysis. The input is the user's voice, and the output is the voice data stored on the device.

[0333] Step 4:

[0334] The terminal sends the recorded audio data to the server. Upon successful transmission of the audio data, the server begins the receiving process. The input is the audio data from the terminal, and the output is the audio data sent to the server.

[0335] Step 5:

[0336] The server converts the received audio data into text data using speech recognition technology. Here, the speech recognition engine operates, converting the audio signal into a string of characters. The input is audio data, and the output is text data.

[0337] Step 6:

[0338] The server uses a generative AI model to perform sentiment analysis on text data and evaluate the user's psychological state. The model uses natural language processing techniques to analyze the text and evaluate the user's emotions. The input is text data, and the output is the result of the sentiment analysis.

[0339] Step 7:

[0340] The server generates personalized advice and encouraging messages for the user based on the sentiment analysis results. This process utilizes a generative AI model to produce text messages. The input is the sentiment analysis results, and the output is the generated text message.

[0341] Step 8:

[0342] The server converts the generated text message using speech synthesis technology and creates voice feedback using the voice sample set by the user. The speech synthesis engine operates to create a friendly feedback voice. The input is a text message, and the output is synthesized speech.

[0343] Step 9:

[0344] The terminal plays synthesized speech received from the server and provides it to the user as feedback. When the voice playback device is activated, the user can hear appropriate feedback. The input is synthesized speech from the server, and the output is the played voice feedback.

[0345] Step 10:

[0346] The server stores voice data and sentiment analysis results to track changes in the user's mental state over time. This allows it to indicate when the need for professional consultation arises. The input is daily voice data and sentiment analysis results, and the output is the accumulated user psychological data.

[0347] (Application Example 1)

[0348] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0349] Modern consumers seek to understand their own mental state through their everyday shopping experiences and make better purchasing decisions. However, existing systems lack the means to adequately link mental health with purchasing activities, making it a challenge to improve consumer mental well-being and the purchasing experience.

[0350] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0351] In this invention, the server includes means for performing sentiment analysis based on the user's voice input and generating statements corresponding to the results, means for synthesizing the generated statements with a voice specified by the user, and means for providing product information based on the user's voice input and making recommendations to improve the user's willingness to purchase. This enables the user to make the optimal product selection while taking into account their own mental health condition.

[0352] An "information processing device" is a device that uses a computer to collect, process, and analyze data.

[0353] An "application" is a program installed on an information processing device to perform a specific function.

[0354] "Voice input" refers to the act of a device capturing the user's voice and using it as data.

[0355] A "server" is a computer system that receives and processes information from other devices via a network.

[0356] "Speech recognition" is a technology that automatically converts speech into text data.

[0357] "Text data" refers to character information converted from speech.

[0358] "Sentiment analysis" is a technique that analyzes text data to determine a person's emotions and psychological state.

[0359] "Means of generating statements" refers to the process of creating appropriate messages based on analysis results.

[0360] "Speech synthesis" is a technology that converts text information into a speech format that can be played back.

[0361] "Mental state" refers to an indicator of an individual's psychological health and stress level.

[0362] "Product information" refers to providing consumers with product information that can be used as a reference when making purchasing decisions.

[0363] "Purchase intent" refers to the psychological state in which consumers feel the desire to buy a product.

[0364] The ideal configuration for this system involves an information processing unit, a server, and a smart display device. The information processing unit plays the role of routinely collecting user voice input. When a user provides voice input through a smart device, that data is immediately sent to the server. The server uses speech recognition to convert this voice into text data.

[0365] The text data is further analyzed by an emotion analysis engine to evaluate the user's emotional state and mental burden at that time. Based on this analysis, the server starts the process of generating the most appropriate statements for the user using a generative AI model. The statements are output using speech synthesis technology in the voice of a close person selected by the user and provided to the user as feedback.

[0366] Furthermore, this system also has a function to support users' purchasing activities. It provides voice-guided product recommendations tailored to the user's mental state, psychologically supporting their desire to buy. For example, if a user inputs, "I feel like relaxing today," the system will provide a friendly voice recommendation such as, "We have a recommended aromatherapy candle," helping to pique their interest in a specific section or product.

[0367] The following is an example of how this system works, using prompt messages.

[0368] "Analyze the user's voice input for emotional analysis, and based on the results, generate appropriate product information in a gentle tone."

[0369] This design allows users to naturally care for their mental health in their daily lives while also having a better shopping experience.

[0370] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0371] Step 1:

[0372] The user provides voice input through a smart device. The input is the user's voice, which is captured by the smart device's microphone and processed by the information processing unit. The user can freely talk about their everyday emotions and physical state.

[0373] Step 2:

[0374] The terminal receives the audio data and sends it to the server. Using this audio data as input, the server runs a speech recognition algorithm and converts it into text data. In this way, the audio input is converted into a format that can be processed by a machine.

[0375] Step 3:

[0376] The server sends the converted text data to the sentiment analysis engine. The sentiment analysis engine analyzes the input text data and outputs the user's emotions and stress levels as numerical values ​​or categories. This allows the user's mental status to be evaluated.

[0377] Step 4:

[0378] The server generates feedback messages using a generative AI model based on the results of sentiment analysis. This model generates appropriate message candidates using the prompt "Analyze the user's voice input and generate appropriate product information in a gentle tone based on the results."

[0379] Step 5:

[0380] The server generates a message and forwards it to a speech synthesis engine. The speech synthesis engine converts the input message into a voice preferred by the user and outputs the voice information. This provides the user with user-friendly feedback.

[0381] Step 6:

[0382] The device plays back audio feedback to the user. Through the played feedback, the user can receive advice on their mental health and product recommendations tailored to their emotional state.

[0383] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0384] This invention provides an information processing system for more precisely recognizing user emotions and providing personalized mental health support. This system functions using an application installed on an information processing device and a server.

[0385] First, the user installs the application on their information processing device, records a voice sample, and selects the voice to use. This selected voice sample is then stored on the device as basic data for speech synthesis.

[0386] Providing daily mental health support begins with the device sending a notification at a designated time, asking the user, "How are you feeling today?" Crucially, the emotion engine recognizes the user's facial expressions, tone of voice, and verbal responses in real time. For example, even if the user utters a short phrase like, "I'm feeling a little down," the system can analyze facial tension and tone of voice to grasp the nuances in detail.

[0387] The user's responses are recorded by the device, and the audio data is quickly sent to the server. The server uses speech recognition technology to convert the recorded data into text, and then a detailed sentiment analysis is performed by an emotion engine. The emotion engine quantifies the user's emotional state based on their series of responses and the content of their words, and stores this data.

[0388] Based on this detailed emotional data, the server generates advice and words of encouragement that are best suited to the user. The generated message is synthesized into a pre-selected, pleasant voice and fed back to the user via the device. For example, a voice message such as "Let's take it easy today and move forward one step at a time" might be played in the voice of the user's favorite person.

[0389] Furthermore, the emotion engine analyzes long-term accumulated emotional data to create individual emotional profiles for each user. This serves as a guide for users to deepen their self-understanding and maintain better mental health. In addition, if the accumulated data indicates that support from a professional is needed, the server will provide referrals and consultation suggestions to appropriate professionals.

[0390] Through these procedures, the present invention provides users with accurate and personalized mental health support, enabling them to live their daily lives with support. This allows users to maintain better mental health and receive appropriate intervention when needed.

[0391] The following describes the processing flow.

[0392] Step 1:

[0393] The user installs the application on the information processing device. Upon first launch, they create an account and record and save a voice sample of someone they consider close to them.

[0394] Step 2:

[0395] Every morning, the device notifies the user at a specified time, asking in a voice, "How are you feeling today?" This voice is synthesized using the voice of a person the user likes.

[0396] Step 3:

[0397] The user answers aloud to the device about their mood and condition for the day. Their facial expressions are also analyzed by the camera during this process.

[0398] Step 4:

[0399] The device records the user's voice and facial expression data and sends it to the server.

[0400] Step 5:

[0401] The server converts the received audio into text using speech recognition technology, and an emotion engine analyzes the user's emotional state in detail from the text and facial expressions.

[0402] Step 6:

[0403] Based on the results of the sentiment analysis, the server generates advice and messages tailored to the user. For example, if the user feels "a little stressed," it will generate a message such as, "It would be good to make time to relax."

[0404] Step 7:

[0405] The generated message is synthesized using a voice setting pre-configured by the user and then sent to the device.

[0406] Step 8:

[0407] The device plays synthesized speech, providing feedback to the user in a friendly voice.

[0408] Step 9:

[0409] The server collects emotional data and creates a long-term emotional profile of the user. This profile is updated regularly to help the user understand themselves better.

[0410] Step 10:

[0411] If necessary, the server will analyze the data it has accumulated, and if it is determined that expert intervention is appropriate, it will introduce the user to an expert or suggest a consultation.

[0412] This series of steps allows users to receive continuous feedback and support in understanding and improving their own mental state.

[0413] (Example 2)

[0414] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0415] In recent years, as the management of individual mental health has become increasingly important, establishing means to provide individually tailored mental health support is a challenge. In particular, there is a need to accurately grasp the emotional state of users in real time and provide prompt, individualized advice based on that assessment. Furthermore, there is a lack of mechanisms to effectively manage long-term changes in mental state and appropriately suggest professional intervention when necessary.

[0416] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0417] In this invention, the server includes means for converting audio data into text data by acoustic analysis, means for generating a response according to the analysis results by emotion analysis, and means for accumulating emotion data and profiling an individual's emotional characteristics. This makes it possible to understand the user's emotional state in detail, manage long-term changes in their mental state, and provide timely and optimal mental health support.

[0418] An "information processing device" is an electronic device that has the function of processing data.

[0419] A "program" is a set of instructions written for a computer to perform a specific task.

[0420] "User" refers to an individual who uses this system.

[0421] "Voice input" refers to audio data that a user provides to an information processing device via a microphone.

[0422] "Communication equipment" refers to devices or networks used for sending and receiving data.

[0423] "Acoustic analysis" is the process of analyzing audio data and converting its content into text data.

[0424] "Text data" refers to text information that is obtained after voice input has been converted into text.

[0425] "Sentiment analysis" refers to data processing performed to infer a user's emotions from text data.

[0426] A "response" is a message or instruction generated and provided to the user based on the results of sentiment analysis.

[0427] "Speech synthesis" is a technology that generates speech based on text data.

[0428] "Mental state" refers to the psychological state related to the user's mental health.

[0429] "Emotional characteristics" refer to profile information that shows the user's emotional tendencies and patterns.

[0430] "Expert intervention" refers to guidance or advice provided by individuals with specialized knowledge.

[0431] This invention is a system that recognizes a user's emotional state in real time and provides individually tailored mental health support. The system functions through a program installed on an information processing device and a communication device.

[0432] The terminal is an information processing device equipped with a microphone for acquiring the user's voice input. The user records their voice through an application and registers it as basic data for speech synthesis. This voice data is stored on the user's terminal.

[0433] The server converts the audio data acquired using speech recognition technology into text data. Specifically, the server uses a generative AI model to analyze the information extracted from the audio and quantify the user's emotions.

[0434] Depending on the user's emotional state, the server generates words of encouragement and advice. This utilizes a generative AI model with individually tailored prompts. For example, if the user's emotional analysis indicates they are "feeling a little down," the server will generate a message such as "Don't push yourself today, take it easy and rest," and deliver it as synthesized speech in a voice selected by the user.

[0435] The synthesized voice message is delivered to the user through the device. This allows the user to receive appropriate support tailored to their emotional state. An example of a prompt is the instruction, "Create a support message for when the user feels 'a little down'."

[0436] In this way, the system continuously accumulates user emotional data and supports the improvement of users' mental health through long-term analysis. If it is determined that professional intervention is necessary, it is possible to make such a suggestion through the server.

[0437] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0438] Step 1:

[0439] The user launches the application and records a voice sample. The application receives an audio signal acquired through the microphone as input. This audio signal is stored on the device as basic data for speech synthesis. Specifically, the user presses the record button and records a specific phrase in their own voice.

[0440] Step 2:

[0441] The device sends a notification at a specified time. The system uses pre-configured time information as input. The device then voices the message, "How are you feeling today?", prompting the user for a response. Specifically, the device's alarm function activates, and the message is played through the speaker.

[0442] Step 3:

[0443] The device records the user's response and sends it to the server as audio data. It receives an audio signal generated by the user's response as input. This audio signal is sent to the server via the network. Specifically, after recording begins, the device compresses the audio data and uploads it at high speed.

[0444] Step 4:

[0445] The server receives audio data and converts it into text data through acoustic analysis. The input is audio data sent from the terminal. The server uses a speech recognition algorithm to convert the audio into text and passes the output to the sentiment analysis process. Specifically, the server starts the speech recognition engine and converts the data into text.

[0446] Step 5:

[0447] The server performs sentiment analysis based on text data. The input is text data converted from speech. The server uses a generative AI model to quantify the user's emotions from the text data and stores the results in a database. Specifically, the AI ​​engine extracts emotional characteristics from the text and generates a numerical score.

[0448] Step 6:

[0449] The server generates an appropriate feedback message based on the results of sentiment analysis. The input is numerical data obtained from sentiment analysis. The server uses a generative AI model to create an appropriate message and synthesizes it in the voice selected by the user. Specifically, the server designs the message based on the prompt text and goes through a process of synthesizing it from text to speech.

[0450] Step 7:

[0451] The device plays a synthesized voice message to the user. It receives an audio file from the server as input. This file is delivered to the user as audio information through the device's audio system. Specifically, the device downloads the audio file and plays it through its speaker.

[0452] (Application Example 2)

[0453] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0454] In modern society, there is a demand for the precise recognition and appropriate response to individual emotions, but conventional information systems have not been able to adequately achieve this. Furthermore, while providing services tailored to the emotions of customers in physical stores is considered to contribute to improving the quality of customer service, it is difficult to achieve with existing methods.

[0455] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0456] In this invention, the server includes means for collecting voice input from users, means for converting the collected voice data into symbolic data by speech recognition, means for performing emotion analysis based on the symbolic data and generating statements according to the analysis results, and means for generating and outputting guidance according to the emotions of the customers using an information machine. This enables precise responses to individual emotions and personalized responses according to the emotional state of the customers.

[0457] An "information processing device" is an electronic device used to input, process, and output data.

[0458] An "application program" is software installed on an information processing device to perform a specific function.

[0459] A "user" is an individual who receives services by operating an information processing device or application program.

[0460] "Voice input" refers to sound data that a user provides to an information processing device as voice.

[0461] A "central computing system" is a centrally managed group of computers used to process and analyze collected data.

[0462] "Speech recognition" is a technology that converts voice input into a format such as text.

[0463] "Symbolic data" refers to digital data such as text converted by speech recognition.

[0464] "Emotional analysis" is a technology that analyzes a user's emotional state from text or audio.

[0465] "Means for generating statements" refers to the technology of creating appropriate response sentences based on sentiment analysis results.

[0466] A "speech synthesis model" is a technological model for reproducing digital data as speech.

[0467] An "information machine" is an electronic control device that provides information and guidance.

[0468] "Means for generating and outputting guidance" refers to technologies that present appropriate information to users in the form of audio or text.

[0469] "Means for determining and proposing the need for expert intervention" refers to techniques for proposing necessary expert advice based on accumulated data.

[0470] This invention is an information processing system that provides better service to individual users by precisely recognizing their emotions and personalizing customer service and guidance in physical stores. This system includes an information processing device, a central processing system, and an information machine.

[0471] The server uses application programs installed on an information processing device equipped with a microphone to receive voice input from users. The voice data is converted into symbolic data and sent to a central processing system for sentiment analysis. Specific software used for processing includes dedicated libraries for speech recognition and sentiment analysis.

[0472] The central computing system uses the collected data to analyze the user's emotional state. This emotional analysis incorporates facial expression analysis and voice tone analysis technologies, and the resulting emotional data is used to generate the optimal response for the user. A speech synthesis model is used to output the generated response as speech.

[0473] Information machines provide customers with emotionally responsive guidance via voice and displays. For example, a tired customer might be offered a thoughtful message such as, "Let me show you a relaxing area." Conversely, a cheerful customer might be offered proactive suggestions such as, "Let me introduce you to our new products," thereby enhancing the quality of customer service.

[0474] As a concrete example, consider the case where this system is implemented in the information center of a department store. This system analyzes the facial expressions and voices of customers and provides appropriate guidance in real time according to their emotions. An example of a prompt in the generative AI model might be: "Based on the customer's emotional data, automatically generate the most appropriate greeting and guidance. Also, analyze the emotional profile over the long term and suggest ways to provide special services to customers who visit frequently."

[0475] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0476] Step 1:

[0477] The terminal uses a microphone to receive voice input from the user. By incorporating the input voice data into the system, data collection begins.

[0478] Step 2:

[0479] The terminal collects audio data and transmits it to a central processing system, where it is converted into symbolic data using speech recognition software. The speech recognition engine then extracts text data from the audio data. The resulting text data serves as the basis for sentiment analysis.

[0480] Step 3:

[0481] The server performs sentiment analysis based on symbolic data. Here, a sentiment analysis engine is used to analyze and quantify the user's emotional state from the symbolic data. The analysis results are output as digital data indicating the user's specific emotional state.

[0482] Step 4:

[0483] The central processing system generates the optimal response based on the analysis results. An AI model is used to create the optimal message for the user, inferred from emotional data. This model outputs an appropriate response based on the generated prompt.

[0484] Step 5:

[0485] The server synthesizes the speech using the user's specified voice, and the terminal outputs it as audio. Text data is converted into audio data by a speech synthesis engine and played back using the user's set voice.

[0486] Step 6:

[0487] The device records voice data, and the server records the data to suggest professional intervention as needed. Long-term data accumulation allows for the detection of important mental health trends and outputs information for intervention as required.

[0488] Step 7:

[0489] The server controls the information machines and provides customers with emotionally resonant guidance. It generates guidance that matches the store environment in real time, improving the user experience.

[0490] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0491] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0492] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0493] [Third Embodiment]

[0494] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0495] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0496] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0497] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0498] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0499] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0500] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0501] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0502] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0503] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0504] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0505] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0506] This invention provides a system that allows users to easily receive mental health support in their daily lives. As an embodiment, it utilizes an application installed on an information processing device. This application receives voice input from the user and processes it in cooperation with a server. The details are described below.

[0507] First, the user installs the application on the information processing device and records a voice sample. The user can choose the voice of someone they are familiar with for this voice sample. This prepares the system to provide feedback in the user's preferred voice.

[0508] Next, the device notifies the user at a designated time each day, requesting voice input about their mood and physical condition for the day. The user's responses become important data in the process.

[0509] The input voice data is sent from the terminal to the server. The server receives the transmitted voice data and converts it into text using speech recognition technology. Next, the server performs sentiment analysis on the text data. Based on the results of this analysis, the user's emotions and stress level at that time are evaluated.

[0510] The server then generates appropriate advice and words of encouragement for the user based on the sentiment analysis results. The generated messages are then converted into a voice set by the user using speech synthesis technology.

[0511] This audio is ultimately played from the device, providing natural feedback to the user. For example, if a user answers "I'm feeling a bit down today" in the morning, they might hear a friendly voice offering advice such as, "Don't push yourself, take it slow."

[0512] Furthermore, the server accumulates this daily data, allowing for an analysis of long-term changes in the user's mental state. This data can also be used to make decisions regarding recommending consultations with specialists as needed.

[0513] In this way, the present invention can effectively manage the user's mental health and provide daily support. This system achieves the ease of use and immediacy that were difficult to achieve with conventional mental health care methods, and has a structure that makes it easy for busy modern people to use continuously.

[0514] The following describes the processing flow.

[0515] Step 1:

[0516] The user launches an application installed on the information processing device and registers an account. The user records a voice sample and selects the voice they want to use. This recording data is saved by the device and used later for speech synthesis.

[0517] Step 2:

[0518] Every morning at a designated time, the device sends a notification to the user, asking in a voice, "How are you feeling today?" The notification uses the voice of a close friend or family member that the user has set.

[0519] Step 3:

[0520] The user uses voice input to describe their mood or state of mind for the day. For example, they might say, "I'm a little tired today."

[0521] Step 4:

[0522] The device records the user's voice input and sends that audio data to the server in real time.

[0523] Step 5:

[0524] After the server receives the audio data, it uses speech recognition technology to convert the data into text format.

[0525] Step 6:

[0526] The server analyzes the converted text data to perform sentiment analysis. This process evaluates the user's emotional state and stress level.

[0527] Step 7:

[0528] Based on the results of sentiment analysis, the server generates advice and encouraging messages tailored to the user.

[0529] Step 8:

[0530] The server uses speech synthesis technology to convert the generated message into the user's specified voice.

[0531] Step 9:

[0532] The synthesized audio file is sent to the device, and the user receives audio feedback.

[0533] Step 10:

[0534] The server stores sentiment analysis and user response results in a database to track long-term changes in mental state.

[0535] Step 11:

[0536] If necessary, the device will present the user with a suggestion such as, "Do you need to consult with an expert?"

[0537] This process allows users to have their mental health continuously monitored and receive support in a friendly voice when needed.

[0538] (Example 1)

[0539] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0540] In recent years, support for maintaining mental health has become increasingly important. However, traditional mental health care methods have been difficult for users to access and respond to immediately, making continuous use challenging for busy modern people. Furthermore, there is a lack of objective data to appropriately determine when professionals should intervene based on the user's psychological state.

[0541] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0542] In this invention, the server includes means for converting speech into text information using speech recognition technology, means for performing sentiment analysis and generating a response based on the analysis results, and means for determining and suggesting expert intervention based on the recorded information. This makes it possible to provide user-friendly and immediate management of the user's psychological health, and to appropriately suggest expert intervention when necessary.

[0543] An "information processing device" is a device equipped with functions for receiving, processing, and transmitting data.

[0544] "Speech recognition technology" is a technology that analyzes speech signals and converts their content into text data that a computer can understand.

[0545] "Text information" refers to character data converted using speech recognition technology.

[0546] "Sentiment analysis" is the process of analyzing text information to evaluate the speaker's emotions and psychological state.

[0547] "Speech synthesis technology" is a technology that artificially generates speech based on text data.

[0548] "Psychological information" refers to data about the user's mental state, including emotions, psychological tendencies, and stress levels.

[0549] "Expert intervention" refers to the appropriate involvement of a professional in the user's condition to provide psychological or medical guidance and advice.

[0550] This embodiment of the invention is an information processing system for supporting the psychological health of users. The components of this system and the technologies supporting them are described below.

[0551] The user first installs a dedicated application on the information processing device. This allows the user to record the voice of a familiar person and register it as a voice sample. This sample will later be used to generate voice feedback.

[0552] Next, the device notifies the user at a designated time each day, requesting voice input regarding their mood and physical condition for the day. The voice data provided by the user forms the core of the system and is used to evaluate their mental state.

[0553] The device sends voice data to the server. The server is equipped with speech recognition technology, where the voice data is converted into text data. For example, if the user says, "I'm feeling a little stressed today," it will be converted into text.

[0554] The server performs sentiment analysis based on text data. Using a generative AI model, it evaluates the user's emotions and psychological tendencies, and generates appropriate advice and encouraging messages based on the results. The generated text messages are converted into speech using speech synthesis technology with a voice sample set by the user.

[0555] Ultimately, the device can play synthesized voices to the user, providing friendly feedback. For example, the user might hear gentle advice such as, "Don't push yourself, take it slow."

[0556] Furthermore, the server continuously accumulates this data and analyzes changes in the user's mental state over the long term. This data is used when expert judgment is needed and provides information to suggest the need for timely intervention.

[0557] A concrete example of a prompt might be, "Convert today's voice input from the user to text, analyze the user's sentiment from that text, and generate appropriate advice."

[0558] In this way, the system possesses both user-friendliness and immediacy, enabling it to effectively support the mental health of today's busy users.

[0559] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0560] Step 1:

[0561] The user installs a dedicated application on the information processing device. During this process, the user records the voice of someone they feel familiar with and registers it as a voice sample in the application. This voice sample is used in subsequent processing for feedback generation. The input is the user's voice, and the output is the saved voice sample.

[0562] Step 2:

[0563] The device sends a notification to the user at a set time and requests voice input regarding their daily mood and physical condition. It uses the system clock to verify that the user has specified the time. The input is system clock information, and the output is the notification to the user.

[0564] Step 3:

[0565] The user inputs voice data about their mood and physical condition for the day in response to notifications from their device. This voice data is important for later analysis. The input is the user's voice, and the output is the voice data stored on the device.

[0566] Step 4:

[0567] The terminal sends the recorded audio data to the server. Upon successful transmission of the audio data, the server begins the receiving process. The input is the audio data from the terminal, and the output is the audio data sent to the server.

[0568] Step 5:

[0569] The server converts the received audio data into text data using speech recognition technology. Here, the speech recognition engine operates, converting the audio signal into a string of characters. The input is audio data, and the output is text data.

[0570] Step 6:

[0571] The server uses a generative AI model to perform sentiment analysis on text data and evaluate the user's psychological state. The model uses natural language processing techniques to analyze the text and evaluate the user's emotions. The input is text data, and the output is the result of the sentiment analysis.

[0572] Step 7:

[0573] The server generates personalized advice and encouraging messages for the user based on the sentiment analysis results. This process utilizes a generative AI model to produce text messages. The input is the sentiment analysis results, and the output is the generated text message.

[0574] Step 8:

[0575] The server converts the generated text message using speech synthesis technology and creates voice feedback using the voice sample set by the user. The speech synthesis engine operates to create a friendly feedback voice. The input is a text message, and the output is synthesized speech.

[0576] Step 9:

[0577] The terminal plays synthesized speech received from the server and provides it to the user as feedback. When the voice playback device is activated, the user can hear appropriate feedback. The input is synthesized speech from the server, and the output is the played voice feedback.

[0578] Step 10:

[0579] The server stores voice data and sentiment analysis results to track changes in the user's mental state over time. This allows it to indicate when the need for professional consultation arises. The input is daily voice data and sentiment analysis results, and the output is the accumulated user psychological data.

[0580] (Application Example 1)

[0581] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0582] Modern consumers seek to understand their own mental state through their everyday shopping experiences and make better purchasing decisions. However, existing systems lack the means to adequately link mental health with purchasing activities, making it a challenge to improve consumer mental well-being and the purchasing experience.

[0583] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0584] In this invention, the server includes means for performing sentiment analysis based on the user's voice input and generating statements corresponding to the results, means for synthesizing the generated statements with a voice specified by the user, and means for providing product information based on the user's voice input and making recommendations to improve the user's willingness to purchase. This enables the user to make the optimal product selection while taking into account their own mental health condition.

[0585] An "information processing device" is a device that uses a computer to collect, process, and analyze data.

[0586] An "application" is a program installed on an information processing device to perform a specific function.

[0587] "Voice input" refers to the act of a device capturing the user's voice and using it as data.

[0588] A "server" is a computer system that receives and processes information from other devices via a network.

[0589] "Speech recognition" is a technology that automatically converts speech into text data.

[0590] "Text data" refers to character information converted from speech.

[0591] "Sentiment analysis" is a technique that analyzes text data to determine a person's emotions and psychological state.

[0592] "Means of generating statements" refers to the process of creating appropriate messages based on analysis results.

[0593] "Speech synthesis" is a technology that converts text information into a speech format that can be played back.

[0594] "Mental state" refers to an indicator of an individual's psychological health and stress level.

[0595] "Product information" refers to providing consumers with product information that can be used as a reference when making purchasing decisions.

[0596] "Purchase intent" refers to the psychological state in which consumers feel the desire to buy a product.

[0597] The ideal configuration for this system involves an information processing unit, a server, and a smart display device. The information processing unit plays the role of routinely collecting user voice input. When a user provides voice input through a smart device, that data is immediately sent to the server. The server uses speech recognition to convert this voice into text data.

[0598] The text data is further analyzed by an emotion analysis engine to evaluate the user's emotional state and mental burden at that time. Based on this analysis, the server starts the process of generating the most appropriate statements for the user using a generative AI model. The statements are output using speech synthesis technology in the voice of a close person selected by the user and provided to the user as feedback.

[0599] Furthermore, this system also has a function to support users' purchasing activities. It provides voice-guided product recommendations tailored to the user's mental state, psychologically supporting their desire to buy. For example, if a user inputs, "I feel like relaxing today," the system will provide a friendly voice recommendation such as, "We have a recommended aromatherapy candle," helping to pique their interest in a specific section or product.

[0600] The following is an example of how this system works, using prompt messages.

[0601] "Analyze the user's voice input for emotional analysis, and based on the results, generate appropriate product information in a gentle tone."

[0602] This design allows users to naturally care for their mental health in their daily lives while also having a better shopping experience.

[0603] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0604] Step 1:

[0605] The user provides voice input through a smart device. The input is the user's voice, which is captured by the smart device's microphone and processed by the information processing unit. The user can freely speak about their everyday emotions and physical state.

[0606] Step 2:

[0607] The terminal receives the audio data and sends it to the server. Using this audio data as input, the server runs a speech recognition algorithm and converts it into text data. In this way, the audio input is converted into a format that can be processed by a machine.

[0608] Step 3:

[0609] The server sends the converted text data to the sentiment analysis engine. The sentiment analysis engine analyzes the input text data and outputs the user's emotions and stress levels as numerical values ​​or categories. This allows the user's mental status to be evaluated.

[0610] Step 4:

[0611] The server generates feedback messages using a generative AI model based on the results of sentiment analysis. This model generates appropriate message candidates using the prompt "Analyze the user's voice input and generate appropriate product information in a gentle tone based on the results."

[0612] Step 5:

[0613] The server generates a message and forwards it to a speech synthesis engine. The speech synthesis engine converts the input message into a voice preferred by the user and outputs the voice information. This provides the user with user-friendly feedback.

[0614] Step 6:

[0615] The device plays back audio feedback to the user. Through the played feedback, the user can receive advice on their mental health and product recommendations tailored to their emotional state.

[0616] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0617] This invention provides an information processing system for more precisely recognizing user emotions and providing personalized mental health support. This system functions using an application installed on an information processing device and a server.

[0618] First, the user installs the application on their information processing device, records a voice sample, and selects the voice to use. This selected voice sample is then stored on the device as basic data for speech synthesis.

[0619] Providing daily mental health support begins with the device sending a notification at a designated time, asking the user, "How are you feeling today?" Crucially, the emotion engine recognizes the user's facial expressions, tone of voice, and verbal responses in real time. For example, even if the user utters a short phrase like, "I'm feeling a little down," the system can analyze facial tension and tone of voice to grasp the nuances in detail.

[0620] The user's responses are recorded by the device, and the audio data is quickly sent to the server. The server uses speech recognition technology to convert the recorded data into text, and then a detailed sentiment analysis is performed by an emotion engine. The emotion engine quantifies the user's emotional state based on their series of responses and the content of their words, and stores this data.

[0621] Based on this detailed emotional data, the server generates advice and words of encouragement that are best suited to the user. The generated message is synthesized into a pre-selected, pleasant voice and fed back to the user via the device. For example, a voice message such as "Let's take it easy today and move forward one step at a time" might be played in the voice of the user's favorite person.

[0622] Furthermore, the emotion engine analyzes long-term accumulated emotional data to create individual emotional profiles for each user. This serves as a guide for users to deepen their self-understanding and maintain better mental health. In addition, if the accumulated data indicates that support from a professional is needed, the server will provide referrals and consultation suggestions to appropriate professionals.

[0623] Through these procedures, the present invention provides users with accurate and personalized mental health support, enabling them to live their daily lives with support. This allows users to maintain better mental health and receive appropriate intervention when needed.

[0624] The following describes the processing flow.

[0625] Step 1:

[0626] The user installs the application on the information processing device. Upon first launch, they create an account and record and save a voice sample of someone they consider close to them.

[0627] Step 2:

[0628] Every morning, the device notifies the user at a specified time, asking in a voice, "How are you feeling today?" This voice is synthesized using the voice of a person the user likes.

[0629] Step 3:

[0630] The user answers aloud to the device about their mood and condition for the day. Their facial expressions are also analyzed by the camera during this process.

[0631] Step 4:

[0632] The device records the user's voice and facial expression data and sends it to the server.

[0633] Step 5:

[0634] The server converts the received audio into text using speech recognition technology, and an emotion engine analyzes the user's emotional state in detail from the text and facial expressions.

[0635] Step 6:

[0636] Based on the results of the sentiment analysis, the server generates advice and messages tailored to the user. For example, if the user feels "a little stressed," it will generate a message such as, "It would be good to make time to relax."

[0637] Step 7:

[0638] The generated message is synthesized using a voice setting pre-configured by the user and then sent to the device.

[0639] Step 8:

[0640] The device plays synthesized speech, providing feedback to the user in a friendly voice.

[0641] Step 9:

[0642] The server collects emotional data and creates a long-term emotional profile of the user. This profile is updated regularly to help the user understand themselves better.

[0643] Step 10:

[0644] If necessary, the server will analyze the data it has accumulated, and if it is determined that expert intervention is appropriate, it will introduce the user to an expert or suggest a consultation.

[0645] This series of steps allows users to receive continuous feedback and support in understanding and improving their own mental state.

[0646] (Example 2)

[0647] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0648] In recent years, as the management of individual mental health has become increasingly important, establishing means to provide individually tailored mental health support is a challenge. In particular, there is a need to accurately grasp the emotional state of users in real time and provide prompt, individualized advice based on that assessment. Furthermore, there is a lack of mechanisms to effectively manage long-term changes in mental state and appropriately suggest professional intervention when necessary.

[0649] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0650] In this invention, the server includes means for converting audio data into text data by acoustic analysis, means for generating a response according to the analysis results by emotion analysis, and means for accumulating emotion data and profiling an individual's emotional characteristics. This makes it possible to understand the user's emotional state in detail, manage long-term changes in their mental state, and provide timely and optimal mental health support.

[0651] An "information processing device" is an electronic device that has the function of processing data.

[0652] A "program" is a set of instructions written for a computer to perform a specific task.

[0653] "User" refers to an individual who uses this system.

[0654] "Voice input" refers to audio data that a user provides to an information processing device via a microphone.

[0655] "Communication equipment" refers to devices or networks used for sending and receiving data.

[0656] "Acoustic analysis" is the process of analyzing audio data and converting its content into text data.

[0657] "Text data" refers to text information that is obtained after voice input has been converted into text.

[0658] "Sentiment analysis" refers to data processing performed to infer a user's emotions from text data.

[0659] A "response" is a message or instruction generated and provided to the user based on the results of sentiment analysis.

[0660] "Speech synthesis" is a technology that generates speech based on text data.

[0661] "Mental state" refers to the psychological state related to the user's mental health.

[0662] "Emotional characteristics" refer to profile information that shows the user's emotional tendencies and patterns.

[0663] "Expert intervention" refers to guidance or advice provided by individuals with specialized knowledge.

[0664] This invention is a system that recognizes a user's emotional state in real time and provides individually tailored mental health support. The system functions through a program installed on an information processing device and a communication device.

[0665] The terminal is an information processing device equipped with a microphone for acquiring the user's voice input. The user records their voice through an application and registers it as basic data for speech synthesis. This voice data is stored on the user's terminal.

[0666] The server converts the audio data acquired using speech recognition technology into text data. Specifically, the server uses a generative AI model to analyze the information extracted from the audio and quantify the user's emotions.

[0667] Depending on the user's emotional state, the server generates words of encouragement and advice. This utilizes a generative AI model with individually tailored prompts. For example, if the user's emotional analysis indicates they are "feeling a little down," the server will generate a message such as "Don't push yourself today, take it easy and rest," and deliver it as synthesized speech in a voice selected by the user.

[0668] The synthesized voice message is delivered to the user through the device. This allows the user to receive appropriate support tailored to their emotional state. An example of a prompt is the instruction, "Create a support message for when the user feels 'a little down'."

[0669] In this way, the system continuously accumulates user emotional data and supports the improvement of users' mental health through long-term analysis. If it is determined that professional intervention is necessary, it is possible to make such a suggestion through the server.

[0670] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0671] Step 1:

[0672] The user launches the application and records a voice sample. The application receives an audio signal acquired through the microphone as input. This audio signal is stored on the device as basic data for speech synthesis. Specifically, the user presses the record button and records a specific phrase in their own voice.

[0673] Step 2:

[0674] The device sends a notification at a specified time. The system uses pre-configured time information as input. The device then voices the message, "How are you feeling today?", prompting the user for a response. Specifically, the device's alarm function activates, and the message is played through the speaker.

[0675] Step 3:

[0676] The device records the user's response and sends it to the server as audio data. It receives an audio signal generated by the user's response as input. This audio signal is sent to the server via the network. Specifically, after recording begins, the device compresses the audio data and uploads it at high speed.

[0677] Step 4:

[0678] The server receives audio data and converts it into text data through acoustic analysis. The input is audio data sent from the terminal. The server uses a speech recognition algorithm to convert the audio into text and passes the output to the sentiment analysis process. Specifically, the server starts the speech recognition engine and converts the data into text.

[0679] Step 5:

[0680] The server performs sentiment analysis based on text data. The input is text data converted from speech. The server uses a generative AI model to quantify the user's emotions from the text data and stores the results in a database. Specifically, the AI ​​engine extracts emotional characteristics from the text and generates a numerical score.

[0681] Step 6:

[0682] The server generates an appropriate feedback message based on the results of sentiment analysis. The input is numerical data obtained from sentiment analysis. The server uses a generative AI model to create an appropriate message and synthesizes it in the voice selected by the user. Specifically, the server designs the message based on the prompt text and goes through a process of synthesizing it from text to speech.

[0683] Step 7:

[0684] The device plays a synthesized voice message to the user. It receives an audio file from the server as input. This file is delivered to the user as audio information through the device's audio system. Specifically, the device downloads the audio file and plays it through its speaker.

[0685] (Application Example 2)

[0686] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0687] In modern society, there is a demand for the precise recognition and appropriate response to individual emotions, but conventional information systems have not been able to adequately achieve this. Furthermore, while providing services tailored to the emotions of customers in physical stores is considered to contribute to improving the quality of customer service, it is difficult to achieve with existing methods.

[0688] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0689] In this invention, the server includes means for collecting voice input from users, means for converting the collected voice data into symbolic data by speech recognition, means for performing emotion analysis based on the symbolic data and generating statements according to the analysis results, and means for generating and outputting guidance according to the emotions of the customers using an information machine. This enables precise responses to individual emotions and personalized responses according to the emotional state of the customers.

[0690] An "information processing device" is an electronic device used to input, process, and output data.

[0691] An "application program" is software installed on an information processing device to perform a specific function.

[0692] A "user" is an individual who receives services by operating an information processing device or application program.

[0693] "Voice input" refers to sound data that a user provides to an information processing device as voice.

[0694] A "central computing system" is a centrally managed group of computers used to process and analyze collected data.

[0695] "Speech recognition" is a technology that converts voice input into a format such as text.

[0696] "Symbolic data" refers to digital data such as text converted by speech recognition.

[0697] "Emotional analysis" is a technology that analyzes a user's emotional state from text or audio.

[0698] "Means for generating statements" refers to the technology of creating appropriate response sentences based on sentiment analysis results.

[0699] A "speech synthesis model" is a technological model for reproducing digital data as speech.

[0700] An "information machine" is an electronic control device that provides information and guidance.

[0701] "Means for generating and outputting guidance" refers to technologies that present appropriate information to users in the form of audio or text.

[0702] "Means for determining and proposing the need for expert intervention" refers to techniques for proposing necessary expert advice based on accumulated data.

[0703] This invention is an information processing system that provides better service to individual users by precisely recognizing their emotions and personalizing customer service and guidance in physical stores. This system includes an information processing device, a central processing system, and an information machine.

[0704] The server uses application programs installed on an information processing device equipped with a microphone to receive voice input from users. The voice data is converted into symbolic data and sent to a central processing system for sentiment analysis. Specific software used for processing includes dedicated libraries for speech recognition and sentiment analysis.

[0705] The central computing system uses the collected data to analyze the user's emotional state. This emotional analysis incorporates facial expression analysis and voice tone analysis technologies, and the resulting emotional data is used to generate the optimal response for the user. A speech synthesis model is used to output the generated response as speech.

[0706] Information machines provide customers with emotionally responsive guidance via voice and displays. For example, a tired customer might be offered a thoughtful message such as, "Let me show you a relaxing area." Conversely, a cheerful customer might be offered proactive suggestions such as, "Let me introduce you to our new products," thereby enhancing the quality of customer service.

[0707] As a concrete example, consider the case where this system is implemented in the information center of a department store. This system analyzes the facial expressions and voices of customers and provides appropriate guidance in real time according to their emotions. An example of a prompt in the generative AI model might be: "Based on the customer's emotional data, automatically generate the most appropriate greeting and guidance. Also, analyze the emotional profile over the long term and suggest ways to provide special services to customers who visit frequently."

[0708] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0709] Step 1:

[0710] The terminal uses a microphone to receive voice input from the user. By incorporating the input voice data into the system, data collection begins.

[0711] Step 2:

[0712] The terminal collects audio data and transmits it to a central processing system, where it is converted into symbolic data using speech recognition software. The speech recognition engine then extracts text data from the audio data. The resulting text data serves as the basis for sentiment analysis.

[0713] Step 3:

[0714] The server performs sentiment analysis based on symbolic data. Here, a sentiment analysis engine is used to analyze and quantify the user's emotional state from the symbolic data. The analysis results are output as digital data indicating the user's specific emotional state.

[0715] Step 4:

[0716] The central processing system generates the optimal response based on the analysis results. An AI model is used to create the optimal message for the user, inferred from emotional data. This model outputs an appropriate response based on the generated prompt.

[0717] Step 5:

[0718] The server synthesizes the speech using the user's specified voice, and the terminal outputs it as audio. Text data is converted into audio data by a speech synthesis engine and played back using the user's set voice.

[0719] Step 6:

[0720] The device records voice data, and the server records the data to suggest professional intervention as needed. Long-term data accumulation allows for the detection of important mental health trends and outputs information for intervention as required.

[0721] Step 7:

[0722] The server controls the information machines and provides customers with emotionally resonant guidance. It generates guidance that matches the store environment in real time, improving the user experience.

[0723] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0724] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0725] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0726] [Fourth Embodiment]

[0727] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0728] As shown in Figure 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.

[0729] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0730] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0731] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0732] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0733] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0734] The controlled 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0735] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0736] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0737] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0738] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0739] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0740] This invention provides a system that allows users to easily receive mental health support in their daily lives. As an embodiment, it utilizes an application installed on an information processing device. This application receives voice input from the user and processes it in cooperation with a server. The details are described below.

[0741] First, the user installs the application on the information processing device and records a voice sample. The user can choose the voice of someone they are familiar with for this voice sample. This prepares the system to provide feedback in the user's preferred voice.

[0742] Next, the device notifies the user at a designated time each day, requesting voice input about their mood and physical condition for the day. The user's responses become important data in the process.

[0743] The input voice data is sent from the terminal to the server. The server receives the transmitted voice data and converts it into text using speech recognition technology. Next, the server performs sentiment analysis on the text data. Based on the results of this analysis, the user's emotions and stress level at that time are evaluated.

[0744] The server then generates appropriate advice and words of encouragement for the user based on the sentiment analysis results. The generated messages are then converted into a voice set by the user using speech synthesis technology.

[0745] This audio is ultimately played from the device, providing natural feedback to the user. For example, if a user answers "I'm feeling a bit down today" in the morning, they might hear a friendly voice offering advice such as, "Don't push yourself, take it slow."

[0746] Furthermore, the server accumulates this daily data, allowing for an analysis of long-term changes in the user's mental state. This data can also be used to make decisions regarding recommending consultations with specialists as needed.

[0747] In this way, the present invention can effectively manage the user's mental health and provide daily support. This system achieves the ease of use and immediacy that were difficult to achieve with conventional mental health care methods, and has a structure that makes it easy for busy modern people to use continuously.

[0748] The following describes the processing flow.

[0749] Step 1:

[0750] The user launches an application installed on the information processing device and registers an account. The user records a voice sample and selects the voice they want to use. This recording data is saved by the device and used later for speech synthesis.

[0751] Step 2:

[0752] Every morning at a designated time, the device sends a notification to the user, asking in a voice, "How are you feeling today?" The notification uses the voice of a close friend or family member that the user has set.

[0753] Step 3:

[0754] The user uses voice input to describe their mood or state of mind for the day. For example, they might say, "I'm a little tired today."

[0755] Step 4:

[0756] The device records the user's voice input and sends that audio data to the server in real time.

[0757] Step 5:

[0758] After the server receives the audio data, it uses speech recognition technology to convert the data into text format.

[0759] Step 6:

[0760] The server analyzes the converted text data to perform sentiment analysis. This process evaluates the user's emotional state and stress level.

[0761] Step 7:

[0762] Based on the results of sentiment analysis, the server generates advice and encouraging messages tailored to the user.

[0763] Step 8:

[0764] The server uses speech synthesis technology to convert the generated message into the user's specified voice.

[0765] Step 9:

[0766] The synthesized audio file is sent to the device, and the user receives audio feedback.

[0767] Step 10:

[0768] The server stores sentiment analysis and user response results in a database to track long-term changes in mental state.

[0769] Step 11:

[0770] If necessary, the device will present the user with a suggestion such as, "Do you need to consult with an expert?"

[0771] This process allows users to have their mental health continuously monitored and receive support in a friendly voice when needed.

[0772] (Example 1)

[0773] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0774] In recent years, support for maintaining mental health has become increasingly important. However, traditional mental health care methods have been difficult for users to access and respond to immediately, making continuous use challenging for busy modern people. Furthermore, there is a lack of objective data to appropriately determine when professionals should intervene based on the user's psychological state.

[0775] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0776] In this invention, the server includes means for converting speech into text information using speech recognition technology, means for performing sentiment analysis and generating a response based on the analysis results, and means for determining and suggesting expert intervention based on the recorded information. This makes it possible to provide user-friendly and immediate management of the user's psychological health, and to appropriately suggest expert intervention when necessary.

[0777] An "information processing device" is a device equipped with functions for receiving, processing, and transmitting data.

[0778] "Speech recognition technology" is a technology that analyzes speech signals and converts their content into text data that a computer can understand.

[0779] "Text information" refers to character data converted using speech recognition technology.

[0780] "Sentiment analysis" is the process of analyzing text information to evaluate the speaker's emotions and psychological state.

[0781] "Speech synthesis technology" is a technology that artificially generates speech based on text data.

[0782] "Psychological information" refers to data about the user's mental state, including emotions, psychological tendencies, and stress levels.

[0783] "Expert intervention" refers to the appropriate involvement of a professional in the user's condition to provide psychological or medical guidance and advice.

[0784] This embodiment of the invention is an information processing system for supporting the psychological health of users. The components of this system and the technologies supporting them are described below.

[0785] The user first installs a dedicated application on the information processing device. This allows the user to record the voice of a familiar person and register it as a voice sample. This sample will later be used to generate voice feedback.

[0786] Next, the device notifies the user at a designated time each day, requesting voice input regarding their mood and physical condition for the day. The voice data provided by the user forms the core of the system and is used to evaluate their mental state.

[0787] The device sends voice data to the server. The server is equipped with speech recognition technology, where the voice data is converted into text data. For example, if the user says, "I'm feeling a little stressed today," it will be converted into text.

[0788] The server performs sentiment analysis based on text data. Using a generative AI model, it evaluates the user's emotions and psychological tendencies, and generates appropriate advice and encouraging messages based on the results. The generated text messages are converted into speech using speech synthesis technology with a voice sample set by the user.

[0789] Ultimately, the device can play synthesized voices to the user, providing friendly feedback. For example, the user might hear gentle advice such as, "Don't push yourself, take it slow."

[0790] Furthermore, the server continuously accumulates this data and analyzes changes in the user's mental state over the long term. This data is used when expert judgment is needed and provides information to suggest the need for timely intervention.

[0791] A concrete example of a prompt might be, "Convert today's voice input from the user to text, analyze the user's sentiment from that text, and generate appropriate advice."

[0792] In this way, the system possesses both user-friendliness and immediacy, enabling it to effectively support the mental health of today's busy users.

[0793] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0794] Step 1:

[0795] The user installs a dedicated application on the information processing device. During this process, the user records the voice of someone they feel familiar with and registers it as a voice sample in the application. This voice sample is used in subsequent processing for feedback generation. The input is the user's voice, and the output is the saved voice sample.

[0796] Step 2:

[0797] The device sends a notification to the user at a set time and requests voice input regarding their daily mood and physical condition. It uses the system clock to verify that the user has specified the time. The input is system clock information, and the output is the notification to the user.

[0798] Step 3:

[0799] The user inputs voice data about their mood and physical condition for the day in response to notifications from their device. This voice data is important for later analysis. The input is the user's voice, and the output is the voice data stored on the device.

[0800] Step 4:

[0801] The terminal sends the recorded audio data to the server. Upon successful transmission of the audio data, the server begins the receiving process. The input is the audio data from the terminal, and the output is the audio data sent to the server.

[0802] Step 5:

[0803] The server converts the received audio data into text data using speech recognition technology. Here, the speech recognition engine operates, converting the audio signal into a string of characters. The input is audio data, and the output is text data.

[0804] Step 6:

[0805] The server uses a generative AI model to perform sentiment analysis on text data and evaluate the user's psychological state. The model uses natural language processing techniques to analyze the text and evaluate the user's emotions. The input is text data, and the output is the result of the sentiment analysis.

[0806] Step 7:

[0807] The server generates personalized advice and encouraging messages for the user based on the sentiment analysis results. This process utilizes a generative AI model to produce text messages. The input is the sentiment analysis results, and the output is the generated text message.

[0808] Step 8:

[0809] The server converts the generated text message using speech synthesis technology and creates voice feedback using the voice sample set by the user. The speech synthesis engine operates to create a friendly feedback voice. The input is a text message, and the output is synthesized speech.

[0810] Step 9:

[0811] The terminal plays synthesized speech received from the server and provides it to the user as feedback. When the voice playback device is activated, the user can hear appropriate feedback. The input is synthesized speech from the server, and the output is the played voice feedback.

[0812] Step 10:

[0813] The server stores voice data and sentiment analysis results to track changes in the user's mental state over time. This allows it to indicate when the need for professional consultation arises. The input is daily voice data and sentiment analysis results, and the output is the accumulated user psychological data.

[0814] (Application Example 1)

[0815] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0816] Modern consumers seek to understand their own mental state through their everyday shopping experiences and make better purchasing decisions. However, existing systems lack the means to adequately link mental health with purchasing activities, making it a challenge to improve consumer mental well-being and the purchasing experience.

[0817] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0818] In this invention, the server includes means for performing sentiment analysis based on the user's voice input and generating statements corresponding to the results, means for synthesizing the generated statements with a voice specified by the user, and means for providing product information based on the user's voice input and making recommendations to improve the user's willingness to purchase. This enables the user to make the optimal product selection while taking into account their own mental health condition.

[0819] An "information processing device" is a device that uses a computer to collect, process, and analyze data.

[0820] An "application" is a program installed on an information processing device to perform a specific function.

[0821] "Voice input" refers to the act of a device capturing the user's voice and using it as data.

[0822] A "server" is a computer system that receives and processes information from other devices via a network.

[0823] "Speech recognition" is a technology that automatically converts speech into text data.

[0824] "Text data" refers to character information converted from speech.

[0825] "Sentiment analysis" is a technique that analyzes text data to determine a person's emotions and psychological state.

[0826] "Means of generating statements" refers to the process of creating appropriate messages based on analysis results.

[0827] "Speech synthesis" is a technology that converts text information into a speech format that can be played back.

[0828] "Mental state" refers to an indicator of an individual's psychological health and stress level.

[0829] "Product information" refers to providing consumers with product information that can be used as a reference when making purchasing decisions.

[0830] "Purchase intent" refers to the psychological state in which consumers feel the desire to buy a product.

[0831] The ideal configuration for this system involves an information processing unit, a server, and a smart display device. The information processing unit plays the role of routinely collecting user voice input. When a user provides voice input through a smart device, that data is immediately sent to the server. The server uses speech recognition to convert this voice into text data.

[0832] The text data is further analyzed by an emotion analysis engine to evaluate the user's emotional state and mental burden at that time. Based on this analysis, the server starts the process of generating the most appropriate statements for the user using a generative AI model. The statements are output using speech synthesis technology in the voice of a close person selected by the user and provided to the user as feedback.

[0833] Furthermore, this system also has a function to support users' purchasing activities. It provides voice-guided product recommendations tailored to the user's mental state, psychologically supporting their desire to buy. For example, if a user inputs, "I feel like relaxing today," the system will provide a friendly voice recommendation such as, "We have a recommended aromatherapy candle," helping to pique their interest in a specific section or product.

[0834] The following is an example of how this system works, using prompt messages.

[0835] "Analyze the user's voice input for emotional analysis, and based on the results, generate appropriate product information in a gentle tone."

[0836] This design allows users to naturally care for their mental health in their daily lives while also having a better shopping experience.

[0837] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0838] Step 1:

[0839] The user provides voice input through a smart device. The input is the user's voice, which is captured by the smart device's microphone and processed by the information processing unit. The user can freely speak about their everyday emotions and physical state.

[0840] Step 2:

[0841] The terminal receives the audio data and sends it to the server. Using this audio data as input, the server runs a speech recognition algorithm and converts it into text data. In this way, the audio input is converted into a format that can be processed by a machine.

[0842] Step 3:

[0843] The server sends the converted text data to the sentiment analysis engine. The sentiment analysis engine analyzes the input text data and outputs the user's emotions and stress levels as numerical values ​​or categories. This allows the user's mental status to be evaluated.

[0844] Step 4:

[0845] The server generates feedback messages using a generative AI model based on the results of sentiment analysis. This model generates appropriate message candidates using the prompt "Analyze the user's voice input and generate appropriate product information in a gentle tone based on the results."

[0846] Step 5:

[0847] The server generates a message and forwards it to a speech synthesis engine. The speech synthesis engine converts the input message into a voice preferred by the user and outputs the voice information. This provides the user with user-friendly feedback.

[0848] Step 6:

[0849] The device plays back audio feedback to the user. Through the played feedback, the user can receive advice on their mental health and product recommendations tailored to their emotional state.

[0850] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0851] This invention provides an information processing system for more precisely recognizing user emotions and providing personalized mental health support. This system functions using an application installed on an information processing device and a server.

[0852] First, the user installs the application on their information processing device, records a voice sample, and selects the voice to use. This selected voice sample is then stored on the device as basic data for speech synthesis.

[0853] Providing daily mental health support begins with the device sending a notification at a designated time, asking the user, "How are you feeling today?" Crucially, the emotion engine recognizes the user's facial expressions, tone of voice, and verbal responses in real time. For example, even if the user utters a short phrase like, "I'm feeling a little down," the system can analyze facial tension and tone of voice to grasp the nuances in detail.

[0854] The user's responses are recorded by the device, and the audio data is quickly sent to the server. The server uses speech recognition technology to convert the recorded data into text, and then a detailed sentiment analysis is performed by an emotion engine. The emotion engine quantifies the user's emotional state based on their series of responses and the content of their words, and stores this data.

[0855] Based on this detailed emotional data, the server generates advice and words of encouragement that are best suited to the user. The generated message is synthesized into a pre-selected, pleasant voice and fed back to the user via the device. For example, a voice message such as "Let's take it easy today and move forward one step at a time" might be played in the voice of the user's favorite person.

[0856] Furthermore, the emotion engine analyzes long-term accumulated emotional data to create individual emotional profiles for each user. This serves as a guide for users to deepen their self-understanding and maintain better mental health. In addition, if the accumulated data indicates that support from a professional is needed, the server will provide referrals and consultation suggestions to appropriate professionals.

[0857] Through these procedures, the present invention provides users with accurate and personalized mental health support, enabling them to live their daily lives with support. This allows users to maintain better mental health and receive appropriate intervention when needed.

[0858] The following describes the processing flow.

[0859] Step 1:

[0860] The user installs the application on the information processing device. Upon first launch, they create an account and record and save a voice sample of someone they consider close to them.

[0861] Step 2:

[0862] Every morning, the device notifies the user at a specified time, asking in a voice, "How are you feeling today?" This voice is synthesized using the voice of a person the user likes.

[0863] Step 3:

[0864] The user answers aloud to the device about their mood and condition for the day. Their facial expressions are also analyzed by the camera during this process.

[0865] Step 4:

[0866] The device records the user's voice and facial expression data and sends it to the server.

[0867] Step 5:

[0868] The server converts the received audio into text using speech recognition technology, and an emotion engine analyzes the user's emotional state in detail from the text and facial expressions.

[0869] Step 6:

[0870] Based on the results of the sentiment analysis, the server generates advice and messages tailored to the user. For example, if the user feels "a little stressed," it will generate a message such as, "It would be good to make time to relax."

[0871] Step 7:

[0872] The generated message is synthesized using a voice setting pre-configured by the user and then sent to the device.

[0873] Step 8:

[0874] The device plays synthesized speech, providing feedback to the user in a friendly voice.

[0875] Step 9:

[0876] The server collects emotional data and creates a long-term emotional profile of the user. This profile is updated regularly to help the user understand themselves better.

[0877] Step 10:

[0878] If necessary, the server will analyze the data it has accumulated, and if it is determined that expert intervention is appropriate, it will introduce the user to an expert or suggest a consultation.

[0879] This series of steps allows users to receive continuous feedback and support in understanding and improving their own mental state.

[0880] (Example 2)

[0881] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0882] In recent years, as the management of individual mental health has become increasingly important, establishing means to provide individually tailored mental health support is a challenge. In particular, there is a need to accurately grasp the emotional state of users in real time and provide prompt, individualized advice based on that assessment. Furthermore, there is a lack of mechanisms to effectively manage long-term changes in mental state and appropriately suggest professional intervention when necessary.

[0883] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0884] In this invention, the server includes means for converting audio data into text data by acoustic analysis, means for generating a response according to the analysis results by emotion analysis, and means for accumulating emotion data and profiling an individual's emotional characteristics. This makes it possible to understand the user's emotional state in detail, manage long-term changes in their mental state, and provide timely and optimal mental health support.

[0885] An "information processing device" is an electronic device that has the function of processing data.

[0886] A "program" is a set of instructions written for a computer to perform a specific task.

[0887] "User" refers to an individual who uses this system.

[0888] "Voice input" refers to audio data that a user provides to an information processing device via a microphone.

[0889] "Communication equipment" refers to devices or networks used for sending and receiving data.

[0890] "Acoustic analysis" is the process of analyzing audio data and converting its content into text data.

[0891] "Text data" refers to text information that is obtained after voice input has been converted into text.

[0892] "Sentiment analysis" refers to data processing performed to infer a user's emotions from text data.

[0893] A "response" is a message or instruction generated and provided to the user based on the results of sentiment analysis.

[0894] "Speech synthesis" is a technology that generates speech based on text data.

[0895] "Mental state" refers to the psychological state related to the user's mental health.

[0896] "Emotional characteristics" refer to profile information that shows the user's emotional tendencies and patterns.

[0897] "Expert intervention" refers to guidance or advice provided by individuals with specialized knowledge.

[0898] This invention is a system that recognizes a user's emotional state in real time and provides individually tailored mental health support. The system functions through a program installed on an information processing device and a communication device.

[0899] The terminal is an information processing device equipped with a microphone for acquiring the user's voice input. The user records their voice through an application and registers it as basic data for speech synthesis. This voice data is stored on the user's terminal.

[0900] The server converts the audio data acquired using speech recognition technology into text data. Specifically, the server uses a generative AI model to analyze the information extracted from the audio and quantify the user's emotions.

[0901] Depending on the user's emotional state, the server generates words of encouragement and advice. This utilizes a generative AI model with individually tailored prompts. For example, if the user's emotional analysis indicates they are "feeling a little down," the server will generate a message such as "Don't push yourself today, take it easy and rest," and deliver it as synthesized speech in a voice selected by the user.

[0902] The synthesized voice message is delivered to the user through the device. This allows the user to receive appropriate support tailored to their emotional state. An example of a prompt is the instruction, "Create a support message for when the user feels 'a little down'."

[0903] In this way, the system continuously accumulates user emotional data and supports the improvement of users' mental health through long-term analysis. If it is determined that professional intervention is necessary, it is possible to make such a suggestion through the server.

[0904] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0905] Step 1:

[0906] The user launches the application and records a voice sample. The application receives an audio signal acquired through the microphone as input. This audio signal is stored on the device as basic data for speech synthesis. Specifically, the user presses the record button and records a specific phrase in their own voice.

[0907] Step 2:

[0908] The device sends a notification at a specified time. The system uses pre-configured time information as input. The device then voices the message, "How are you feeling today?", prompting the user for a response. Specifically, the device's alarm function activates, and the message is played through the speaker.

[0909] Step 3:

[0910] The device records the user's response and sends it to the server as audio data. It receives an audio signal generated by the user's response as input. This audio signal is sent to the server via the network. Specifically, after recording begins, the device compresses the audio data and uploads it at high speed.

[0911] Step 4:

[0912] The server receives audio data and converts it into text data through acoustic analysis. The input is audio data sent from the terminal. The server uses a speech recognition algorithm to convert the audio into text and passes the output to the sentiment analysis process. Specifically, the server starts the speech recognition engine and converts the data into text.

[0913] Step 5:

[0914] The server performs sentiment analysis based on text data. The input is text data converted from speech. The server uses a generative AI model to quantify the user's emotions from the text data and stores the results in a database. Specifically, the AI ​​engine extracts emotional characteristics from the text and generates a numerical score.

[0915] Step 6:

[0916] The server generates an appropriate feedback message based on the results of sentiment analysis. The input is numerical data obtained from sentiment analysis. The server uses a generative AI model to create an appropriate message and synthesizes it in the voice selected by the user. Specifically, the server designs the message based on the prompt text and goes through a process of synthesizing it from text to speech.

[0917] Step 7:

[0918] The device plays a synthesized voice message to the user. It receives an audio file from the server as input. This file is delivered to the user as audio information through the device's audio system. Specifically, the device downloads the audio file and plays it through its speaker.

[0919] (Application Example 2)

[0920] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0921] In modern society, there is a demand for the precise recognition and appropriate response to individual emotions, but conventional information systems have not been able to adequately achieve this. Furthermore, while providing services tailored to the emotions of customers in physical stores is considered to contribute to improving the quality of customer service, it is difficult to achieve with existing methods.

[0922] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0923] In this invention, the server includes means for collecting voice input from users, means for converting the collected voice data into symbolic data by speech recognition, means for performing emotion analysis based on the symbolic data and generating statements according to the analysis results, and means for generating and outputting guidance according to the emotions of the customers using an information machine. This enables precise responses to individual emotions and personalized responses according to the emotional state of the customers.

[0924] An "information processing device" is an electronic device used to input, process, and output data.

[0925] An "application program" is software installed on an information processing device to perform a specific function.

[0926] A "user" is an individual who receives services by operating an information processing device or application program.

[0927] "Voice input" refers to sound data that a user provides to an information processing device as voice.

[0928] A "central computing system" is a centrally managed group of computers used to process and analyze collected data.

[0929] "Speech recognition" is a technology that converts voice input into a format such as text.

[0930] "Symbolic data" refers to digital data such as text converted by speech recognition.

[0931] "Emotional analysis" is a technology that analyzes a user's emotional state from text or audio.

[0932] "Means for generating statements" refers to the technology of creating appropriate response sentences based on sentiment analysis results.

[0933] A "speech synthesis model" is a technological model for reproducing digital data as speech.

[0934] An "information machine" is an electronic control device that provides information and guidance.

[0935] "Means for generating and outputting guidance" refers to technologies that present appropriate information to users in the form of audio or text.

[0936] "Means for determining and proposing the need for expert intervention" refers to techniques for proposing necessary expert advice based on accumulated data.

[0937] This invention is an information processing system that provides better service to individual users by precisely recognizing their emotions and personalizing customer service and guidance in physical stores. This system includes an information processing device, a central processing system, and an information machine.

[0938] The server uses application programs installed on an information processing device equipped with a microphone to receive voice input from users. The voice data is converted into symbolic data and sent to a central processing system for sentiment analysis. Specific software used for processing includes dedicated libraries for speech recognition and sentiment analysis.

[0939] The central computing system uses the collected data to analyze the user's emotional state. This emotional analysis incorporates facial expression analysis and voice tone analysis technologies, and the resulting emotional data is used to generate the optimal response for the user. A speech synthesis model is used to output the generated response as speech.

[0940] Information machines provide customers with emotionally responsive guidance via voice and displays. For example, a tired customer might be offered a thoughtful message such as, "Let me show you a relaxing area." Conversely, a cheerful customer might be offered proactive suggestions such as, "Let me introduce you to our new products," thereby enhancing the quality of customer service.

[0941] As a concrete example, consider the case where this system is implemented in the information center of a department store. This system analyzes the facial expressions and voices of customers and provides appropriate guidance in real time according to their emotions. An example of a prompt in the generative AI model might be: "Based on the customer's emotional data, automatically generate the most appropriate greeting and guidance. Also, analyze the emotional profile over the long term and suggest ways to provide special services to customers who visit frequently."

[0942] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0943] Step 1:

[0944] The terminal uses a microphone to receive voice input from the user. By incorporating the input voice data into the system, data collection begins.

[0945] Step 2:

[0946] The terminal collects audio data and transmits it to a central processing system, where it is converted into symbolic data using speech recognition software. The speech recognition engine then extracts text data from the audio data. The resulting text data serves as the basis for sentiment analysis.

[0947] Step 3:

[0948] The server performs sentiment analysis based on symbolic data. Here, a sentiment analysis engine is used to analyze and quantify the user's emotional state from the symbolic data. The analysis results are output as digital data indicating the user's specific emotional state.

[0949] Step 4:

[0950] The central processing system generates the optimal response based on the analysis results. An AI model is used to create the optimal message for the user, inferred from emotional data. This model outputs an appropriate response based on the generated prompt.

[0951] Step 5:

[0952] The server synthesizes the speech using the user's specified voice, and the terminal outputs it as audio. Text data is converted into audio data by a speech synthesis engine and played back using the user's set voice.

[0953] Step 6:

[0954] The device records voice data, and the server records the data to suggest professional intervention as needed. Long-term data accumulation allows for the detection of important mental health trends and outputs information for intervention as required.

[0955] Step 7:

[0956] The server controls the information machines and provides customers with emotionally resonant guidance. It generates guidance that matches the store environment in real time, improving the user experience.

[0957] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0958] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0959] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0960] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0961] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0962] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0963] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0964] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0965] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0966] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0967] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0968] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0969] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0970] 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.

[0971] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0972] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0973] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0974] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0975] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0976] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0977] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0978] The following is further disclosed regarding the embodiments described above.

[0979] (Claim 1)

[0980] An application installed on the information processing device provides a means for collecting user voice input,

[0981] A means of sending collected audio data to a server and converting it into text data using speech recognition,

[0982] A means of performing sentiment analysis based on text data and generating statements according to the analysis results,

[0983] A means of synthesizing and outputting the generated speech using a voice specified by the user,

[0984] A means of continuously recording the user's mental state and managing trends in change,

[0985] A means of determining and proposing the need for expert intervention based on recorded data,

[0986] A system that includes this.

[0987] (Claim 2)

[0988] The system according to claim 1, comprising means for recording speech based on user selection and adjusting a speech synthesis model using the recorded data.

[0989] (Claim 3)

[0990] The system according to claim 1, comprising means for graphing long-term changes in mental state and providing them to the user visually through data storage and analysis on a server.

[0991] "Example 1"

[0992] (Claim 1)

[0993] An application installed on the information processing device provides a means for collecting audio information,

[0994] A means of transmitting collected audio data to a server via a communication device and converting it into text information using speech recognition technology,

[0995] A means for analyzing text information, performing sentiment analysis, and generating an appropriate response based on the analysis results,

[0996] A means for outputting the generated response using speech synthesis technology with a voice pre-selected by the user,

[0997] A means of continuously recording user psychological information and managing trends in change,

[0998] A means of determining and suggesting expert intervention based on recorded information,

[0999] A system that includes this.

[1000] (Claim 2)

[1001] The system according to claim 1, comprising means for recording speech based on user selection and adjusting speech synthesis technology using the speech data.

[1002] (Claim 3)

[1003] The system according to claim 1, comprising means for visualizing and providing to a user long-term changes in psychological state through data storage and analysis on a server.

[1004] "Application Example 1"

[1005] (Claim 1)

[1006] An application installed on the information processing device provides a means for collecting user voice input,

[1007] A means of sending collected audio data to a server and converting it into text data using speech recognition,

[1008] A means of performing sentiment analysis based on text data and generating statements according to the analysis results,

[1009] A means of synthesizing and outputting the generated speech using a voice specified by the user,

[1010] A means of continuously recording the user's mental state and managing trends in change,

[1011] A means of determining and proposing the need for expert intervention based on recorded data,

[1012] A means of providing product information and making recommendations to improve purchasing intent based on the user's voice input,

[1013] A system that includes this.

[1014] (Claim 2)

[1015] The system according to claim 1, comprising means for recording speech based on user selection and adjusting a speech synthesis model using the recorded data.

[1016] (Claim 3)

[1017] The system according to claim 1, comprising means for graphing long-term changes in mental state and providing them to the user visually through data storage and analysis on a server.

[1018] "Example 2 of combining an emotion engine"

[1019] (Claim 1)

[1020] A means of collecting user voice input through a program installed on the information processing device,

[1021] A means of transmitting collected audio data to a communication device and converting it into text data through acoustic analysis,

[1022] A means for performing sentiment analysis based on text data and generating a response according to the analysis results,

[1023] A means of synthesizing the generated response with a voice selected by the user and outputting it,

[1024] A means of continuously recording the user's mental state and managing trends in change,

[1025] A method for analyzing long-term accumulated emotional data and profiling individual emotional characteristics,

[1026] A means of determining and proposing the need for expert intervention based on recorded information,

[1027] A system that includes this.

[1028] (Claim 2)

[1029] The system according to claim 1, comprising means for recording speech based on user selection and adjusting the basic model of speech synthesis using the recorded data.

[1030] (Claim 3)

[1031] The system according to claim 1, comprising means for visually representing and providing to a user long-term changes in mental state through data storage and analysis using a communication device.

[1032] "Application example 2 when combining with an emotional engine"

[1033] (Claim 1)

[1034] An application program installed on the information processing device provides a means for collecting the user's voice input,

[1035] A means for transmitting collected audio data to a central processing system and converting it into symbolic data through speech recognition,

[1036] A means for performing sentiment analysis based on symbolic data and generating statements according to the analysis results,

[1037] A means of synthesizing the generated speech with a voice specified by the user and outputting it,

[1038] A means of continuously recording the user's mental state and managing trends in change,

[1039] A means of determining and proposing the need for expert intervention based on recorded data,

[1040] A means of generating and outputting guidance tailored to the customer's emotions using an information machine,

[1041] A system that includes this.

[1042] (Claim 2)

[1043] The system according to claim 1, comprising means for recording speech based on the user's selection and adjusting a speech synthesis model using the recorded data.

[1044] (Claim 3)

[1045] The system according to claim 1, comprising means for visualizing long-term changes in mental state and providing them to the user visually through data accumulation and analysis on a central computing system. [Explanation of symbols]

[1046] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An application installed on the information processing device provides a means for collecting user voice input, A means of sending collected audio data to a server and converting it into text data using speech recognition, A means of performing sentiment analysis based on text data and generating statements according to the analysis results, A means of synthesizing and outputting the generated speech using a voice specified by the user, A means of continuously recording the user's mental state and managing trends in change, A means of determining and proposing the need for expert intervention based on recorded data, A system that includes this.

2. The system according to claim 1, comprising means for recording speech based on user selection and adjusting a speech synthesis model using the recorded data.

3. The system according to claim 1, comprising means for graphing long-term changes in mental state and providing them to the user visually through data storage and analysis on a server.

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