System

Abstract

The system according to the embodiment aims to listen to a child's conversation and provide appropriate feedback even when a guardian is busy.SOLUTION: A system according to an embodiment includes a listening unit, a cooperation unit, and a consultation unit. The listener listens to the child. The cooperation unit transmits the information heard by the listening unit to the voice device. The consultation unit provides feedback to the guardian based on the information transmitted by the coordination unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has faced challenges, such as making it difficult for busy parents to fully listen to what their children have to say, and lacking support to help children develop self-esteem.

[0005] The system according to the embodiment aims to enable parents to listen to their children and provide appropriate feedback even when they are busy. [Means for solving the problem]

[0006] The system according to the embodiment includes a listening unit, a coordinating unit, and a consultation unit. The listening unit listens to what the child is saying. The coordinating unit transmits information listened to by the listening unit to an audio device. The consultation unit provides feedback to the parent based on the information transmitted by the coordinating unit. [Effects of the Invention]

[0007] The system according to the embodiment allows parents to listen to their children and provide appropriate feedback even when they are busy. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) An app according to an embodiment of the present invention is designed to enhance children's self-esteem. This app supports chat and voice communication and aims to be a valuable ally for parents who find it difficult to listen to their children's stories during busy days. By linking with a voice device, the app can monitor interactions with children in real time. It also serves as a confidant, providing gentle support like a mother would at home. For example, a user launches the app and begins interacting with their child. The app has a function for listening to the child's story and responding gently. For example, if a child says, "I had fun at school today," the app responds with, "That's great! What did you enjoy?" Next, the app links with a voice device to monitor interactions with the child in real time. For example, parents can listen to their children's stories through the voice device even while they're doing housework. Furthermore, the app can also serve as a confidant for parents. For example, if a parent feels their child has been feeling unwell lately, the app can offer advice such as, "That's worrying. Did something special happen?" This allows the app to increase mental space and smiles in families with children. This allows the app to provide support to increase children's self-esteem. For example, by making communication with children smoother, parents can reduce stress and enjoy spending time with their children more. In addition, by providing a voice for parents to talk to, the app allows parents to focus on raising their children with peace of mind, without feeling alone.

[0029] An app for enhancing a child's self-esteem according to an embodiment includes a listening unit, a linking unit, and a consultation unit. The listening unit listens to the child's stories. Examples of the child's stories include, but are not limited to, everyday conversations, worries, and emotional expressions. For example, when a child says, "I had fun at school today," the listening unit responds by saying, "That's great! What did you enjoy?" The linking unit transmits the information listened to by the listening unit to an audio device. Examples of the audio device include, but are not limited to, smart speakers and voice assistants. For example, the linking unit can listen to the child's stories through the audio device even while the parent is doing housework. The consultation unit provides feedback to the parent based on the information transmitted by the linking unit. Examples of feedback include, but are not limited to, voice messages, text messages, and advice. For example, when a parent feels that their child has been feeling unwell recently, the consultation unit can provide advice such as, "That's worrying. Did something special happen?" As a result, the app for increasing children's self-esteem according to the embodiment can increase children's self-esteem by listening to what the child says, transmitting the information to an audio device, and providing feedback to the parent.

[0030] The listening unit may include an analysis unit that analyzes what the child says. The analysis unit analyzes what the child says using, for example, natural language processing technology. For example, the analysis unit classifies the content of the child's speech by topic and selects an appropriate response. The analysis unit can also estimate the child's emotions using emotion analysis technology. For example, the analysis unit analyzes the tone and speed of the child's voice to estimate emotions. Furthermore, the analysis unit can extract important points from what the child says using topic modeling technology. For example, the analysis unit picks out particularly important information in what the child says and generates a response based on that. This enables the listening unit to provide a more appropriate response by analyzing what the child says.

[0031] The linking unit can link with the voice device. The linking unit links with the voice device using, for example, Bluetooth (registered trademark) technology. For example, the linking unit connects to a smart speaker via Bluetooth and transmits the child's speech to the voice device. The linking unit can also link with the voice device using Wi-Fi technology. For example, the linking unit connects to a voice assistant via Wi-Fi and transmits the child's speech in real time. The linking unit can also link with the voice device using API linking. For example, the linking unit uses the API of the voice device to transmit the child's speech to the device and provide appropriate feedback. In this way, by linking with the voice device, the linking unit can grasp interactions with the child in real time.

[0032] The counseling unit may include a providing unit that provides feedback to the guardian. The providing unit provides feedback to the guardian, for example, using a real-time notification function. For example, the providing unit sends a real-time notification to the guardian's smartphone to convey the content of the child's conversation. The providing unit may also provide feedback using a periodic report function. For example, the providing unit may send a report summarizing the content of the child's conversation to the guardian on a weekly or monthly basis. Furthermore, the providing unit may also provide feedback using a voice message function. For example, the providing unit may send a voice message to the guardian to convey the content of the child's conversation and advice. In this way, the counseling unit can support the guardian by providing feedback to the guardian.

[0033] The listening unit can respond gently to what the child is saying. For example, the listening unit can respond gently by adjusting the tone of voice. For example, the listening unit can respond in a gentle tone depending on what the child is saying. The listening unit can also respond gently by using clever language. For example, the listening unit can respond politely to what the child is saying. Furthermore, the listening unit can respond gently by adjusting the speed of its response. For example, the listening unit can wait until the child finishes speaking and then respond slowly. In this way, the listening unit can increase the child's self-esteem by responding gently to what the child is saying.

[0034] The coordination unit can grasp interactions with children in real time. The coordination unit can grasp such interactions in real time by, for example, increasing the frequency of data updates. For example, the coordination unit updates the content of what the child is saying every few seconds and conveys it to the parent in real time. The coordination unit can also grasp such interactions in real time by minimizing delay time. For example, the coordination unit uses a high-speed communication protocol to minimize communication delay. Furthermore, the coordination unit can grasp interactions with children in real time by synchronizing data in real time. For example, the coordination unit synchronizes the content of what the child is saying in real time and conveys it to the parent immediately. This allows the coordination unit to grasp interactions with children in real time and take appropriate action.

[0035] The counseling department can provide advice to parents. For example, the counseling department provides advice to parents in the form of questions. For example, if a parent feels that their child has been feeling unwell recently, the counseling department may ask, "That's worrying. Has anything special happened?" The counseling department can also provide advice to parents in the form of advice. For example, if a parent consults the counseling department about their child's fight with a friend at school, the counseling department may provide advice such as, "That's tough. First, listen carefully to what your child has to say." Furthermore, the counseling department can provide advice to parents in a dialogue format. For example, if a parent consults the counseling department about their child's inability to concentrate on their studies, the counseling department may provide advice through a dialogue such as, "That's troubling. What kind of situation could be causing this?" In this way, the counseling department can support parents by providing advice to them.

[0036] The listening unit can estimate a child's emotions and dig deeper into the content of the conversation based on the estimated child's emotions. The listening unit, for example, estimates a child's emotions using voice analysis technology. For example, the listening unit analyzes the tone and speed of the child's voice to estimate emotions. The listening unit can also estimate a child's emotions using facial expression analysis technology. For example, the listening unit captures the child's facial expressions with a camera and estimates emotions using a facial expression analysis algorithm. The listening unit can also estimate a child's emotions using text analysis technology. For example, the listening unit analyzes the text of the child's conversation to estimate emotions. This makes it easier for the listening unit to understand the child's feelings by digging deeper into the content of the conversation based on the child's emotions. For example, if a child sounds sad, the listening unit can ask, "What happened?" to find out more details. If a child sounds excited, the listening unit can encourage the child to continue talking by saying, "That's amazing! Tell me more." Furthermore, if a child speaks in an anxious tone, the listening team will ask, "Why do you feel that way?" to find out the cause.

[0037] The active listening unit can automatically classify the topics of a child's conversation and select an appropriate response. The active listening unit, for example, uses a clustering algorithm to classify the topics of a child's conversation. For example, the active listening unit clusters the content of a child's conversation and extracts related topics. The active listening unit can also classify the topics of a child's conversation using topic modeling technology. For example, the active listening unit extracts the topics of a child's conversation using LDA (Latent Dirichlet Allocation). The active listening unit can also classify the topics of a child's conversation using a topic classification algorithm and select an appropriate response. For example, if a child is talking about school, the active listening unit asks, "What happened at school?" If a child is talking about their friends, the active listening unit asks, "What games did you play with your friends?" If a child is talking about their family, the active listening unit asks, "What did you do as a family?" In this way, the active listening unit can classify the topics of a child's conversation and provide an appropriate response.

[0038] The active listening unit can analyze the speed and tone of a child's speech and adjust the appropriate response speed. The active listening unit can analyze the speed of a child's speech using, for example, voice waveform analysis technology. For example, the active listening unit can analyze the speed of a child's speech and select an appropriate response speed. The active listening unit can also analyze the tone of a child's speech using pitch analysis technology. For example, the active listening unit can analyze the pitch of a child's voice and estimate the tone. Furthermore, the active listening unit can analyze the speed and tone of a child's speech using a voice analysis algorithm and adjust the appropriate response speed. For example, if a child is speaking quickly, the active listening unit can encourage the child by saying, "It's okay to speak slowly." If a child is speaking slowly, the active listening unit can reassure the child by saying, "It's okay to speak slowly." If a child is speaking excitedly, the active listening unit can speed up its response by saying, "That's great! Tell me more." This allows the active listening unit to adjust its response speed according to the speed and tone of a child's speech, enabling a more natural dialogue.

[0039] The listening unit can analyze background sounds while the child is talking and provide a response appropriate to the environment. The listening unit analyzes the background sounds using, for example, noise filtering technology. For example, the listening unit filters the background sounds while the child is talking and extracts environmental sounds. The listening unit can also analyze the background sounds using sound source separation technology. For example, the listening unit separates the background sounds from the child's talking and identifies the environmental sounds. The listening unit can also analyze the background sounds using a sound analysis algorithm and provide a response appropriate to the environment. For example, if the sound of a television can be heard in the background, the listening unit can ask, "What are you watching?" If outside sounds can be heard in the background, the listening unit can ask, "Are you playing outside?" If music can be heard in the background, the listening unit can ask, "What music are you listening to?" This allows the listening unit to provide a response appropriate to the background sounds, enabling a more appropriate response.

[0040] The listening unit can estimate a child's emotions and adjust the tone of its response based on the estimated child's emotions. The listening unit estimates a child's emotions using, for example, voice analysis technology. For example, the listening unit analyzes the tone and speed of the child's voice to estimate emotions. The listening unit can also estimate a child's emotions using facial expression analysis technology. For example, the listening unit captures the child's facial expressions with a camera and estimates emotions using a facial expression analysis algorithm. The listening unit can also estimate a child's emotions using text analysis technology. For example, the listening unit analyzes the text content of the child's speech to estimate emotions. This allows the listening unit to adjust the tone of its response based on the child's emotions, enabling a more appropriate response. For example, if a child speaks in a sad voice, the listening unit responds in a gentle tone, saying, "It's okay." If a child speaks excitedly, the listening unit responds in a bright tone, saying, "That's amazing!" If a child speaks anxiously, the listening unit responds in a calm tone, saying, "What's wrong?"

[0041] The listening unit can analyze the content of a child's speech and provide relevant educational advice. The listening unit, for example, uses natural language processing technology to analyze the content of a child's speech. For example, the listening unit can categorize the content of a child's speech by topic and select appropriate educational advice. The listening unit can also provide advice using an educational knowledge base. For example, the listening unit can provide relevant educational information based on the content of a child's speech. Furthermore, the listening unit can provide appropriate educational advice for a child's speech based on advice from educational experts. For example, if a child is talking about homework, the listening unit can ask, "Which subject is difficult?" and provide advice. If a child is talking about science, the listening unit can suggest, "It would be fun to try an experiment." If a child is talking about reading, the listening unit can advise, "I'll tell you what book would be good to read next." In this way, the listening unit can support children's learning by providing educational advice based on the child's speech.

[0042] The listening unit can analyze the content of a child's speech and suggest related games and activities. The listening unit analyzes the content of a child's speech using, for example, natural language processing technology. For example, the listening unit categorizes the content of a child's speech by topic and suggests appropriate games and activities. The listening unit can also make suggestions using a knowledge base of games and activities. For example, the listening unit suggests related games and activities based on the content of a child's speech. Furthermore, the listening unit can suggest appropriate games and activities based on the advice of educational experts. For example, if a child says they want to play outside, the listening unit might suggest, "How about playing in the park?" If a child says they want to draw a picture, the listening unit might suggest, "Let's draw a picture together." If a child says they want to play a game, the listening unit might ask, "What kind of game do you like?" and make a suggestion. In this way, the listening unit can draw a child's interest by suggesting games and activities based on the child's speech.

[0043] The listening unit can analyze the content of a child's conversation and extract information that can be shared by the entire family. The listening unit analyzes the content of a child's conversation using, for example, natural language processing technology. For example, the listening unit classifies the content of a child's conversation by topic and extracts information that can be shared by the entire family. The listening unit can also provide information to facilitate family communication. For example, the listening unit provides information that can be shared by the entire family based on the content of a child's conversation. The listening unit can also extract information about family events and plans and share it with the entire family. For example, if a child is talking about a family trip, the listening unit can respond by saying, "It's fun to go with the whole family." If a child is talking about a family event, the listening unit can suggest, "Let's all have fun together." If a child is talking about family meals, the listening unit can respond by saying, "It's fun to eat together." In this way, the listening unit extracts information that can be shared by the entire family, thereby smoothing family communication.

[0044] The coordination unit can estimate the child's emotions and adjust the timing of transmission to the voice device based on the estimated child's emotions. The coordination unit, for example, estimates the child's emotions using voice analysis technology. For example, the coordination unit analyzes the tone and speed of the child's voice to estimate the emotion. The coordination unit can also estimate the child's emotions using facial expression analysis technology. For example, the coordination unit captures the child's facial expressions with a camera and estimates the emotion using a facial expression analysis algorithm. The coordination unit can also estimate the child's emotions using text analysis technology. For example, the coordination unit performs text analysis of the content of the child's speech to estimate the emotion. This allows the coordination unit to adjust the transmission timing based on the child's emotions, enabling a more appropriate response. For example, if the child is speaking excitedly, the coordination unit immediately transmits to the voice device. On the other hand, if the child is speaking calmly, the coordination unit transmits to the voice device at an appropriate time. On the other hand, if the child is speaking sadly, the coordination unit carefully selects the right timing to transmit to the voice device.

[0045] The coordinating unit can analyze the communication quality with the audio device and select the optimal data transmission method. The coordinating unit analyzes the communication quality using, for example, packet loss analysis technology. For example, the coordinating unit analyzes packet loss in communication with the audio device and evaluates the communication quality. The coordinating unit can also analyze the communication quality using delay analysis technology. For example, the coordinating unit analyzes delay time in communication with the audio device and evaluates the communication quality. The coordinating unit can also analyze the communication quality using throughput analysis technology and select the optimal data transmission method. For example, if the communication quality is good, the coordinating unit transmits high-quality audio data. If the communication quality is unstable, the coordinating unit transmits compressed data. If the communication quality is poor, the coordinating unit prioritizes transmitting text data. In this way, the coordinating unit can select a data transmission method according to the communication quality, enabling stable communication.

[0046] The linking unit can monitor the battery status of the audio device and transmit data at the optimal timing. The linking unit monitors the battery status of the audio device using, for example, technology for monitoring remaining battery power. For example, the linking unit monitors the remaining battery power of the audio device in real time and adjusts the timing of data transmission. The linking unit can also monitor the battery status using technology for analyzing power consumption. For example, the linking unit analyzes the power consumption of the audio device and predicts the battery life. The linking unit can also monitor the battery status using technology for monitoring charging cycles and transmit data at the optimal timing. For example, when the battery is sufficient, the linking unit transmits data in real time. When the battery is low, the linking unit reduces data transmission. When the battery is almost empty, the linking unit suspends data transmission. In this way, the linking unit can extend the device's life by selecting the timing of data transmission according to the battery status.

[0047] The linking unit can analyze the location information of the audio device and select the optimal communication path. The linking unit, for example, analyzes the location information of the audio device using GPS data. For example, the linking unit acquires the location of the audio device from the GPS data and selects the optimal communication path. The linking unit can also analyze the location information of the audio device using Wi-Fi location information. For example, the linking unit identifies the location of the audio device based on the location information of a Wi-Fi access point. Furthermore, the linking unit can analyze the location information of the audio device using beacon technology and select the optimal communication path. For example, when the audio device is indoors, the linking unit prioritizes communication over Wi-Fi. When the audio device is outdoors, the linking unit prioritizes communication over mobile data. Furthermore, when the audio device is moving, the linking unit selects the optimal communication path in real time. As a result, the linking unit can select the optimal communication path based on the location information, enabling stable communication.

[0048] The collaboration unit can estimate the child's emotion and adjust the volume of the audio device based on the estimated emotion. The collaboration unit estimates the child's emotion using, for example, voice analysis technology. For example, the collaboration unit analyzes the tone and speed of the child's voice to estimate the emotion. The collaboration unit can also estimate the child's emotion using facial expression analysis technology. For example, the collaboration unit captures the child's facial expression with a camera and estimates the emotion using a facial expression analysis algorithm. The collaboration unit can also estimate the child's emotion using text analysis technology. For example, the collaboration unit performs text analysis on the content of the child's speech to estimate the emotion. This enables the collaboration unit to respond more appropriately by adjusting the volume based on the child's emotion. For example, if the child is speaking excitedly, the collaboration unit increases the volume of the audio device. Also, if the child is speaking calmly, the collaboration unit appropriately adjusts the volume of the audio device. Furthermore, if the child is speaking sadly, the collaboration unit decreases the volume of the audio device.

[0049] When linking with an audio device, the linking unit can select an optimal data format depending on the type of device. The linking unit selects the data format using, for example, an audio format selection technique. For example, the linking unit selects the optimal audio format depending on the type of audio device. The linking unit can also select a data format using a compression format selection technique. For example, the linking unit selects the optimal compression format depending on the type of audio device. The linking unit can also select a data format using a data protocol selection technique to perform optimal data transmission. For example, in the case of a smart speaker, the linking unit prioritizes sending audio data. In the case of a smartphone, the linking unit combines and sends text data and audio data. In the case of a smartwatch, the linking unit prioritizes sending concise text data. As a result, the linking unit can perform optimal data transmission by selecting a data format depending on the type of device.

[0050] When linking with an audio device, the linking unit can analyze the device's usage history and select the optimal linking method. The linking unit, for example, analyzes the device's usage history using a technology that analyzes usage frequency. For example, the linking unit analyzes the frequency of use of the audio device and selects the optimal linking method. The linking unit can also analyze the device's usage history using a technology that analyzes usage time. For example, the linking unit analyzes the usage time of the audio device and selects the optimal linking method. Furthermore, the linking unit can analyze the device's usage history using a technology that analyzes usage patterns and select the optimal linking method. For example, if the device is used frequently, the linking unit transmits data in real time. On the other hand, if the device is not used often, the linking unit transmits data sparingly. Furthermore, the linking unit selects the optimal data transmission timing based on the device's usage history. As a result, the linking unit selects the optimal linking method based on the device's usage history, enabling more efficient data transmission.

[0051] When linking with an audio device, the linking unit can transmit data by reflecting the user settings of the device. The linking unit, for example, transmits data using a technology that reflects a volume setting. For example, the linking unit transmits data by reflecting the volume setting of the audio device. The linking unit can also transmit data using a technology that reflects a notification setting. For example, the linking unit transmits data by reflecting the notification setting of the audio device. The linking unit can also transmit data using a technology that reflects a language setting, thereby optimally transmitting data. For example, if the user sets the volume of the audio device high, the linking unit transmits data at a high volume. Also, if the user turns off notifications for the audio device, the linking unit prioritizes transmitting text data. Furthermore, if the user changes the language setting of the audio device, the linking unit transmits data in that language. This allows the linking unit to transmit data based on the user settings of the device, enabling more personalized responses.

[0052] The consultation unit can estimate the parent's emotions and adjust the content of the feedback based on the estimated parent's emotions. The consultation unit, for example, estimates the parent's emotions using voice analysis technology. For example, the consultation unit analyzes the parent's tone and speed of voice to estimate the parent's emotions. The consultation unit can also estimate the parent's emotions using facial expression analysis technology. For example, the consultation unit captures the parent's facial expressions with a camera and estimates the parent's emotions using a facial expression analysis algorithm. The consultation unit can also estimate the parent's emotions using text analysis technology. For example, the consultation unit analyzes the text content of the parent's speech to estimate the parent's emotions. This enables the consultation unit to adjust the content of the feedback based on the parent's emotions, thereby enabling more appropriate support. For example, if the parent is feeling stressed, the consultation unit provides gentle feedback such as "It's okay, take a break." If the parent is relaxed, the consultation unit provides encouraging feedback such as "Keep up the good work." If the parent is feeling anxious, the consultation unit offers advice by asking, "Is there something you're worried about?"

[0053] The counseling unit can analyze the parent's past consultation history and provide optimal feedback. The counseling unit, for example, analyzes the parent's consultation history using technology that analyzes past consultation content. For example, the counseling unit analyzes the content of past consultations by the parent and provides optimal feedback. The counseling unit can also analyze the parent's consultation history using technology that analyzes consultation frequency. For example, the counseling unit analyzes how often the parent consults and provides optimal feedback. The counseling unit can also analyze the parent's consultation history using technology that analyzes consultation results and provide optimal feedback. For example, based on the content of the parent's past consultations, the counseling unit provides feedback such as "How was the advice we gave you last time?". Furthermore, based on the feedback the parent received in the past, the counseling unit suggests, "Why don't you try this this time?". Furthermore, based on the parent's past consultation history, the counseling unit confirms, "Was the problem you had last time resolved?" This enables the counseling unit to provide more appropriate support by providing feedback based on the parent's past consultation history.

[0054] The consultation unit can analyze the parent's daily rhythm and provide feedback at optimal timing. The consultation unit, for example, analyzes the parent's daily rhythm using technology that analyzes sleep patterns. For example, the consultation unit analyzes the parent's sleep pattern and selects the optimal timing for feedback. The consultation unit can also analyze the parent's daily rhythm using technology that analyzes activity time. For example, the consultation unit analyzes the parent's activity time and selects the optimal timing for feedback. The consultation unit can also analyze the parent's daily rhythm using technology that analyzes meal times and provide feedback at optimal timing. For example, if the parent is busy in the morning, the consultation unit can provide feedback such as "Take a short break at lunchtime." If the parent is relaxing in the evening, the consultation unit can provide feedback such as "Thank you for another day's hard work." Furthermore, the consultation unit can analyze the parent's daily rhythm and suggest "Take a short break at this time." This allows the consultation unit to provide feedback based on the parent's daily rhythm, enabling more appropriate support.

[0055] The consultation unit can analyze the content of the parent's feedback and accumulate information that will be useful for the next consultation. The consultation unit, for example, analyzes the content of the parent's feedback using technology that analyzes the type of feedback. For example, the consultation unit analyzes the type of feedback received by the parent and accumulates information that will be useful for the next consultation. The consultation unit can also analyze the content of the parent's feedback using technology that analyzes the frequency of feedback. For example, the consultation unit analyzes how often the parent receives feedback and accumulates information that will be useful for the next consultation. Furthermore, the consultation unit can analyze the content of the parent's feedback using technology that analyzes the effectiveness of feedback and accumulate information that will be useful for the next consultation. For example, if a parent says, "I would like to consult about my child's diet," the consultation unit refers to past feedback regarding diet. Also, if a parent says, "I would like to consult about my child's sleep," the consultation unit refers to past feedback regarding sleep. Furthermore, if a parent says, "I would like to consult about my child's studies," the consultation unit refers to past feedback regarding studies. In this way, the consultation unit can provide information that will be useful for the next consultation by accumulating the content of the feedback.

[0056] The consultation unit can estimate the parent's emotions and adjust the tone of the feedback based on the estimated parent's emotions. The consultation unit estimates the parent's emotions using, for example, voice analysis technology. For example, the consultation unit analyzes the tone and speed of the parent's voice to estimate the emotion. The consultation unit can also estimate the parent's emotions using facial expression analysis technology. For example, the consultation unit captures the parent's facial expression with a camera and estimates the emotion using a facial expression analysis algorithm. The consultation unit can also estimate the parent's emotions using text analysis technology. For example, the consultation unit analyzes the text content of the parent's speech to estimate the emotion. This allows the consultation unit to adjust the tone of the feedback based on the parent's emotions, enabling more appropriate support. For example, if the parent is feeling stressed, the consultation unit can give feedback in a gentle tone, such as "It's okay, take a break." If the parent is relaxed, the consultation unit can give feedback in a bright tone, such as "Keep up the good work." If the parent is feeling anxious, the consultation unit can give feedback in a calm tone, such as "Is there anything you're worried about?"

[0057] The counseling unit can analyze the content of the parent's consultation and provide advice from relevant experts. The counseling unit analyzes the content of the parent's consultation using, for example, natural language processing technology. For example, the counseling unit classifies the content of the parent's consultation by topic and provides advice from relevant experts. The counseling unit can also provide advice using a knowledge base of experts. For example, the counseling unit provides advice from relevant experts based on the content of the parent's consultation. Furthermore, the counseling unit can provide appropriate advice for the content of the parent's consultation based on the advice from the experts. For example, if a parent says, "I would like to consult about my child's diet," the counseling unit provides advice from a nutritionist. Also, if a parent says, "I would like to consult about my child's sleep," the counseling unit provides advice from a sleep expert. Furthermore, if a parent says, "I would like to consult about my child's studies," the counseling unit provides advice from an education expert. This enables the counseling unit to provide more appropriate support by providing expert advice.

[0058] The counseling department can analyze the content of the parent's consultation and introduce relevant communities and support groups. The counseling department may analyze the content of the parent's consultation using, for example, natural language processing technology. For example, the counseling department may classify the content of the parent's consultation by topic and introduce relevant communities and support groups. The counseling department may also make introductions using a knowledge base of communities and support groups. For example, the counseling department may introduce relevant communities and support groups based on the content of the parent's consultation. Furthermore, the counseling department may introduce appropriate communities and support groups for the content of the parent's consultation based on advice from experts. For example, if a parent says, "I would like to ask for advice about my child's diet," the counseling department may introduce communities related to diet. Also, if a parent says, "I would like to ask for advice about my child's sleep," the counseling department may introduce support groups related to sleep. Furthermore, if a parent says, "I would like to ask for advice about my child's studies," the counseling department may introduce communities related to studies. In this way, the counseling department can expand the parent's support network by introducing communities and support groups.

[0059] The consultation unit can analyze the content of the parent's consultation and extract information that can be shared by the entire family. The consultation unit analyzes the content of the parent's consultation using, for example, natural language processing technology. For example, the consultation unit classifies the content of the parent's consultation by topic and extracts information that can be shared by the entire family. The consultation unit can also provide information to facilitate family communication. For example, the consultation unit provides information that can be shared by the entire family based on the content of the parent's consultation. Furthermore, the consultation unit can extract information about family events and plans and share it with the entire family. For example, if a parent says, "I would like to consult about my child's diet," the consultation unit provides information about diet that can be shared by the entire family. Also, if a parent says, "I would like to consult about my child's sleep," the consultation unit provides information about sleep that can be shared by the entire family. Furthermore, if a parent says, "I would like to consult about my child's studies," the consultation unit provides information about studies that can be shared by the entire family. In this way, the consultation unit provides information that can be shared by the entire family, thereby smoothing family communication.

[0060] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0061] The listening section not only listens to what children say, but can also generate questions to draw out their interests and concerns. For example, if a child says, "I played at the park today," the listening section will ask, "What kind of games did you play?", digging deeper into what the child is saying. If a child says, "I made a new friend," the listening section will ask, "What's his / her name?", encouraging the child to continue talking. Furthermore, if a child says, "I drew a picture," the listening section will ask, "What kind of picture did you draw?", drawing out the child's creativity. In this way, the listening section not only listens to what children say, but also draws out their interests and concerns, enabling richer dialogue.

[0062] The communication module can analyze the content of a child's conversation and suggest appropriate actions to parents. For example, if a child says, "I had fun at school today," the communication module might suggest, "Try listening to your child talk more about school." If a child says, "I had a fight with a friend," the communication module might advise, "Listen carefully to how your child feels." If a child says, "My homework is difficult," the communication module might suggest, "Help your child with their homework." In this way, the communication module can support communication with children by suggesting appropriate actions to parents based on the content of their children's conversations.

[0063] The listening team can analyze the content of what a child is saying and provide relevant learning resources. For example, if a child says, "I want to know about dinosaurs," the listening team might suggest, "Let's read a book or watch a video about dinosaurs together." Or, if a child says, "I want to know about space," the listening team might suggest, "Let's watch a documentary about space." Or, if a child says, "I like drawing," the listening team might suggest, "Let's check out a website that teaches you how to draw." In this way, the listening team can support children's learning by providing relevant learning resources based on the content of what the child is saying.

[0064] The listening department can analyze the content of a child's conversation and suggest related games and activities. For example, if a child says, "I want to play outside," the listening department will suggest, "How about playing in the park?" If a child says, "I want to draw a picture," the listening department will suggest, "Let's draw a picture together." If a child says, "I want to play a game," the listening department will ask, "What kind of game do you like?" and make a suggestion. In this way, the listening department can draw a child's interest by suggesting games and activities based on the content of the child's conversation.

[0065] The communication module can analyze the content of a child's conversation and suggest appropriate actions to parents. For example, if a child says, "I had fun at school today," the communication module might suggest, "Try listening to your child talk more about school." If a child says, "I had a fight with a friend," the communication module might advise, "Listen carefully to how your child feels." If a child says, "My homework is difficult," the communication module might suggest, "Help your child with their homework." In this way, the communication module can support communication with children by suggesting appropriate actions to parents based on the content of their children's conversations.

[0066] The counseling department can analyze the parents' past consultation history and provide optimal feedback. For example, based on the content of the parents' past consultations, the counseling department can provide feedback such as, "How was the advice we gave you last time?". The counseling department can also refer to the feedback the parents received in the past and suggest, "Why don't you try this this time?". Furthermore, based on the parents' past consultation history, the counseling department can confirm, "Was the previous problem resolved?" This allows the counseling department to provide feedback based on past consultation history, enabling more appropriate support.

[0067] The listening section analyzes the content of a child's conversation and can extract information that can be shared by the entire family. For example, if a child is talking about a family trip, the listening section will respond by saying, "It's fun to go with the whole family." If a child is talking about a family event, the listening section will suggest, "Let's all have fun together." If a child is talking about family meals, the listening section will respond by saying, "It's fun to eat together." In this way, the listening section can extract information that can be shared by the entire family, which will facilitate smooth family communication.

[0068] The processing flow of the first embodiment will be briefly explained below.

[0069] Step 1: The listening team listens to what the children have to say. Children's stories include everyday conversations, worries, and emotional expressions. For example, if a child says, "I had fun at school today," the team responds by saying, "That's great! What did you enjoy?" Step 2: The communication unit sends the information listened to by the listening unit to an audio device. Audio devices include smart speakers and voice assistants. For example, parents can listen to their children's conversations through the audio device while doing housework. Step 3: The consultation department provides feedback to parents based on the information sent by the coordination department. The feedback can include voice messages, text messages, advice, etc. For example, if a parent feels that their child has not been in good spirits recently, the consultation department can provide advice such as, "That's worrying. Has anything special happened?"

[0070] (Example 2) An app according to an embodiment of the present invention is designed to enhance children's self-esteem. This app supports chat and voice communication and aims to be a valuable ally for parents who find it difficult to listen to their children's stories during busy days. By linking with a voice device, the app can monitor interactions with children in real time. It also serves as a confidant, providing gentle support like a mother would at home. For example, a user launches the app and begins interacting with their child. The app has a function for listening to the child's story and responding gently. For example, if a child says, "I had fun at school today," the app responds with, "That's great! What did you enjoy?" Next, the app links with a voice device to monitor interactions with the child in real time. For example, parents can listen to their children's stories through the voice device even while they're doing housework. Furthermore, the app can also serve as a confidant for parents. For example, if a parent feels their child has been feeling unwell lately, the app can offer advice such as, "That's worrying. Did something special happen?" This allows the app to increase mental space and smiles in families with children. This allows the app to provide support to increase children's self-esteem. For example, by making communication with children smoother, parents can reduce stress and enjoy spending time with their children more. In addition, by providing a voice for parents to talk to, the app allows parents to focus on raising their children with peace of mind, without feeling alone.

[0071] An app for enhancing a child's self-esteem according to an embodiment includes a listening unit, a linking unit, and a consultation unit. The listening unit listens to the child's stories. Examples of the child's stories include, but are not limited to, everyday conversations, worries, and emotional expressions. For example, when a child says, "I had fun at school today," the listening unit responds by saying, "That's great! What did you enjoy?" The linking unit transmits the information listened to by the listening unit to an audio device. Examples of the audio device include, but are not limited to, smart speakers and voice assistants. For example, the linking unit can listen to the child's stories through the audio device even while the parent is doing housework. The consultation unit provides feedback to the parent based on the information transmitted by the linking unit. Examples of feedback include, but are not limited to, voice messages, text messages, and advice. For example, when a parent feels that their child has been feeling unwell recently, the consultation unit can provide advice such as, "That's worrying. Did something special happen?" As a result, the app for increasing children's self-esteem according to the embodiment can increase children's self-esteem by listening to what the child says, transmitting the information to an audio device, and providing feedback to the parent.

[0072] The listening unit may include an analysis unit that analyzes what the child says. The analysis unit analyzes what the child says using, for example, natural language processing technology. For example, the analysis unit classifies the content of the child's speech by topic and selects an appropriate response. The analysis unit can also estimate the child's emotions using emotion analysis technology. For example, the analysis unit analyzes the tone and speed of the child's voice to estimate emotions. Furthermore, the analysis unit can extract important points from what the child says using topic modeling technology. For example, the analysis unit picks out particularly important information in what the child says and generates a response based on that. This enables the listening unit to provide a more appropriate response by analyzing what the child says.

[0073] The linking unit can link with the voice device. The linking unit links with the voice device using, for example, Bluetooth technology. For example, the linking unit connects to a smart speaker via Bluetooth and transmits what the child says to the voice device. The linking unit can also link with the voice device using Wi-Fi technology. For example, the linking unit connects to a voice assistant via Wi-Fi and transmits what the child says in real time. The linking unit can also link with the voice device using API linking. For example, the linking unit uses the API of the voice device to transmit what the child says to the device and provide appropriate feedback. In this way, by linking with the voice device, the linking unit can grasp interactions with the child in real time.

[0074] The counseling unit may include a providing unit that provides feedback to the guardian. The providing unit provides feedback to the guardian, for example, using a real-time notification function. For example, the providing unit sends a real-time notification to the guardian's smartphone to convey the content of the child's conversation. The providing unit may also provide feedback using a periodic report function. For example, the providing unit may send a report summarizing the content of the child's conversation to the guardian on a weekly or monthly basis. Furthermore, the providing unit may also provide feedback using a voice message function. For example, the providing unit may send a voice message to the guardian to convey the content of the child's conversation and advice. In this way, the counseling unit can support the guardian by providing feedback to the guardian.

[0075] The listening unit can respond gently to what the child is saying. For example, the listening unit can respond gently by adjusting the tone of voice. For example, the listening unit can respond in a gentle tone depending on what the child is saying. The listening unit can also respond gently by using clever language. For example, the listening unit can respond politely to what the child is saying. Furthermore, the listening unit can respond gently by adjusting the speed of its response. For example, the listening unit can wait until the child finishes speaking and then respond slowly. In this way, the listening unit can increase the child's self-esteem by responding gently to what the child is saying.

[0076] The coordination unit can grasp interactions with children in real time. The coordination unit can grasp such interactions in real time by, for example, increasing the frequency of data updates. For example, the coordination unit updates the content of what the child is saying every few seconds and conveys it to the parent in real time. The coordination unit can also grasp such interactions in real time by minimizing delay time. For example, the coordination unit uses a high-speed communication protocol to minimize communication delay. Furthermore, the coordination unit can grasp interactions with children in real time by synchronizing data in real time. For example, the coordination unit synchronizes the content of what the child is saying in real time and conveys it to the parent immediately. This allows the coordination unit to grasp interactions with children in real time and take appropriate action.

[0077] The counseling department can provide advice to parents. For example, the counseling department provides advice to parents in the form of questions. For example, if a parent feels that their child has been feeling unwell recently, the counseling department may ask, "That's worrying. Has anything special happened?" The counseling department can also provide advice to parents in the form of advice. For example, if a parent consults the counseling department about their child's fight with a friend at school, the counseling department may provide advice such as, "That's tough. First, listen carefully to what your child has to say." Furthermore, the counseling department can provide advice to parents in a dialogue format. For example, if a parent consults the counseling department about their child's inability to concentrate on their studies, the counseling department may provide advice through a dialogue such as, "That's troubling. What kind of situation could be causing this?" In this way, the counseling department can support parents by providing advice to them.

[0078] The listening unit can estimate a child's emotions and dig deeper into the content of the conversation based on the estimated child's emotions. The listening unit, for example, estimates a child's emotions using voice analysis technology. For example, the listening unit analyzes the tone and speed of the child's voice to estimate emotions. The listening unit can also estimate a child's emotions using facial expression analysis technology. For example, the listening unit captures the child's facial expressions with a camera and estimates emotions using a facial expression analysis algorithm. The listening unit can also estimate a child's emotions using text analysis technology. For example, the listening unit analyzes the text of the child's conversation to estimate emotions. This makes it easier for the listening unit to understand the child's feelings by digging deeper into the content of the conversation based on the child's emotions. For example, if a child sounds sad, the listening unit can ask, "What happened?" to find out more details. If a child sounds excited, the listening unit can encourage the child to continue talking by saying, "That's amazing! Tell me more." Furthermore, if a child speaks in an anxious tone, the listening team will ask, "Why do you feel that way?" to find out the cause.

[0079] The active listening unit can automatically classify the topics of a child's conversation and select an appropriate response. The active listening unit, for example, uses a clustering algorithm to classify the topics of a child's conversation. For example, the active listening unit clusters the content of a child's conversation and extracts related topics. The active listening unit can also classify the topics of a child's conversation using topic modeling technology. For example, the active listening unit extracts the topics of a child's conversation using LDA (Latent Dirichlet Allocation). The active listening unit can also classify the topics of a child's conversation using a topic classification algorithm and select an appropriate response. For example, if a child is talking about school, the active listening unit asks, "What happened at school?" If a child is talking about their friends, the active listening unit asks, "What games did you play with your friends?" If a child is talking about their family, the active listening unit asks, "What did you do as a family?" In this way, the active listening unit can classify the topics of a child's conversation and provide an appropriate response.

[0080] The active listening unit can analyze the speed and tone of a child's speech and adjust the appropriate response speed. The active listening unit can analyze the speed of a child's speech using, for example, voice waveform analysis technology. For example, the active listening unit can analyze the speed of a child's speech and select an appropriate response speed. The active listening unit can also analyze the tone of a child's speech using pitch analysis technology. For example, the active listening unit can analyze the pitch of a child's voice and estimate the tone. Furthermore, the active listening unit can analyze the speed and tone of a child's speech using a voice analysis algorithm and adjust the appropriate response speed. For example, if a child is speaking quickly, the active listening unit can encourage the child by saying, "It's okay to speak slowly." If a child is speaking slowly, the active listening unit can reassure the child by saying, "It's okay to speak slowly." If a child is speaking excitedly, the active listening unit can speed up its response by saying, "That's great! Tell me more." This allows the active listening unit to adjust its response speed according to the speed and tone of a child's speech, enabling a more natural dialogue.

[0081] The listening unit can analyze background sounds while the child is talking and provide a response appropriate to the environment. The listening unit analyzes the background sounds using, for example, noise filtering technology. For example, the listening unit filters the background sounds while the child is talking and extracts environmental sounds. The listening unit can also analyze the background sounds using sound source separation technology. For example, the listening unit separates the background sounds from the child's talking and identifies the environmental sounds. The listening unit can also analyze the background sounds using a sound analysis algorithm and provide a response appropriate to the environment. For example, if the sound of a television can be heard in the background, the listening unit can ask, "What are you watching?" If outside sounds can be heard in the background, the listening unit can ask, "Are you playing outside?" If music can be heard in the background, the listening unit can ask, "What music are you listening to?" This allows the listening unit to provide a response appropriate to the background sounds, enabling a more appropriate response.

[0082] The listening unit can estimate a child's emotions and adjust the tone of its response based on the estimated child's emotions. The listening unit estimates a child's emotions using, for example, voice analysis technology. For example, the listening unit analyzes the tone and speed of the child's voice to estimate emotions. The listening unit can also estimate a child's emotions using facial expression analysis technology. For example, the listening unit captures the child's facial expressions with a camera and estimates emotions using a facial expression analysis algorithm. The listening unit can also estimate a child's emotions using text analysis technology. For example, the listening unit analyzes the text content of the child's speech to estimate emotions. This allows the listening unit to adjust the tone of its response based on the child's emotions, enabling a more appropriate response. For example, if a child speaks in a sad voice, the listening unit responds in a gentle tone, saying, "It's okay." If a child speaks excitedly, the listening unit responds in a bright tone, saying, "That's amazing!" If a child speaks anxiously, the listening unit responds in a calm tone, saying, "What's wrong?"

[0083] The listening unit can analyze the content of a child's speech and provide relevant educational advice. The listening unit, for example, uses natural language processing technology to analyze the content of a child's speech. For example, the listening unit can categorize the content of a child's speech by topic and select appropriate educational advice. The listening unit can also provide advice using an educational knowledge base. For example, the listening unit can provide relevant educational information based on the content of a child's speech. Furthermore, the listening unit can provide appropriate educational advice for a child's speech based on advice from educational experts. For example, if a child is talking about homework, the listening unit can ask, "Which subject is difficult?" and provide advice. If a child is talking about science, the listening unit can suggest, "It would be fun to try an experiment." If a child is talking about reading, the listening unit can advise, "I'll tell you what book would be good to read next." In this way, the listening unit can support children's learning by providing educational advice based on the child's speech.

[0084] The listening unit can analyze the content of a child's speech and suggest related games and activities. The listening unit analyzes the content of a child's speech using, for example, natural language processing technology. For example, the listening unit categorizes the content of a child's speech by topic and suggests appropriate games and activities. The listening unit can also make suggestions using a knowledge base of games and activities. For example, the listening unit suggests related games and activities based on the content of a child's speech. Furthermore, the listening unit can suggest appropriate games and activities based on the advice of educational experts. For example, if a child says they want to play outside, the listening unit might suggest, "How about playing in the park?" If a child says they want to draw a picture, the listening unit might suggest, "Let's draw a picture together." If a child says they want to play a game, the listening unit might ask, "What kind of game do you like?" and make a suggestion. In this way, the listening unit can draw a child's interest by suggesting games and activities based on the child's speech.

[0085] The listening unit can analyze the content of a child's conversation and extract information that can be shared by the entire family. The listening unit analyzes the content of a child's conversation using, for example, natural language processing technology. For example, the listening unit classifies the content of a child's conversation by topic and extracts information that can be shared by the entire family. The listening unit can also provide information to facilitate family communication. For example, the listening unit provides information that can be shared by the entire family based on the content of a child's conversation. The listening unit can also extract information about family events and plans and share it with the entire family. For example, if a child is talking about a family trip, the listening unit can respond by saying, "It's fun to go with the whole family." If a child is talking about a family event, the listening unit can suggest, "Let's all have fun together." If a child is talking about family meals, the listening unit can respond by saying, "It's fun to eat together." In this way, the listening unit extracts information that can be shared by the entire family, thereby smoothing family communication.

[0086] The coordination unit can estimate the child's emotions and adjust the timing of transmission to the voice device based on the estimated child's emotions. The coordination unit, for example, estimates the child's emotions using voice analysis technology. For example, the coordination unit analyzes the tone and speed of the child's voice to estimate the emotion. The coordination unit can also estimate the child's emotions using facial expression analysis technology. For example, the coordination unit captures the child's facial expressions with a camera and estimates the emotion using a facial expression analysis algorithm. The coordination unit can also estimate the child's emotions using text analysis technology. For example, the coordination unit performs text analysis of the content of the child's speech to estimate the emotion. This allows the coordination unit to adjust the transmission timing based on the child's emotions, enabling a more appropriate response. For example, if the child is speaking excitedly, the coordination unit immediately transmits to the voice device. On the other hand, if the child is speaking calmly, the coordination unit transmits to the voice device at an appropriate time. On the other hand, if the child is speaking sadly, the coordination unit carefully selects the right timing to transmit to the voice device.

[0087] The coordinating unit can analyze the communication quality with the audio device and select the optimal data transmission method. The coordinating unit analyzes the communication quality using, for example, packet loss analysis technology. For example, the coordinating unit analyzes packet loss in communication with the audio device and evaluates the communication quality. The coordinating unit can also analyze the communication quality using delay analysis technology. For example, the coordinating unit analyzes delay time in communication with the audio device and evaluates the communication quality. The coordinating unit can also analyze the communication quality using throughput analysis technology and select the optimal data transmission method. For example, if the communication quality is good, the coordinating unit transmits high-quality audio data. If the communication quality is unstable, the coordinating unit transmits compressed data. If the communication quality is poor, the coordinating unit prioritizes transmitting text data. In this way, the coordinating unit can select a data transmission method according to the communication quality, enabling stable communication.

[0088] The linking unit can monitor the battery status of the audio device and transmit data at the optimal timing. The linking unit monitors the battery status of the audio device using, for example, technology for monitoring remaining battery power. For example, the linking unit monitors the remaining battery power of the audio device in real time and adjusts the timing of data transmission. The linking unit can also monitor the battery status using technology for analyzing power consumption. For example, the linking unit analyzes the power consumption of the audio device and predicts the battery life. The linking unit can also monitor the battery status using technology for monitoring charging cycles and transmit data at the optimal timing. For example, when the battery is sufficient, the linking unit transmits data in real time. When the battery is low, the linking unit reduces data transmission. When the battery is almost empty, the linking unit suspends data transmission. In this way, the linking unit can extend the device's life by selecting the timing of data transmission according to the battery status.

[0089] The linking unit can analyze the location information of the audio device and select the optimal communication path. The linking unit, for example, analyzes the location information of the audio device using GPS data. For example, the linking unit acquires the location of the audio device from the GPS data and selects the optimal communication path. The linking unit can also analyze the location information of the audio device using Wi-Fi location information. For example, the linking unit identifies the location of the audio device based on the location information of a Wi-Fi access point. Furthermore, the linking unit can analyze the location information of the audio device using beacon technology and select the optimal communication path. For example, when the audio device is indoors, the linking unit prioritizes communication over Wi-Fi. When the audio device is outdoors, the linking unit prioritizes communication over mobile data. Furthermore, when the audio device is moving, the linking unit selects the optimal communication path in real time. As a result, the linking unit can select the optimal communication path based on the location information, enabling stable communication.

[0090] The collaboration unit can estimate the child's emotion and adjust the volume of the audio device based on the estimated emotion. The collaboration unit estimates the child's emotion using, for example, voice analysis technology. For example, the collaboration unit analyzes the tone and speed of the child's voice to estimate the emotion. The collaboration unit can also estimate the child's emotion using facial expression analysis technology. For example, the collaboration unit captures the child's facial expression with a camera and estimates the emotion using a facial expression analysis algorithm. The collaboration unit can also estimate the child's emotion using text analysis technology. For example, the collaboration unit performs text analysis on the content of the child's speech to estimate the emotion. This enables the collaboration unit to respond more appropriately by adjusting the volume based on the child's emotion. For example, if the child is speaking excitedly, the collaboration unit increases the volume of the audio device. Also, if the child is speaking calmly, the collaboration unit appropriately adjusts the volume of the audio device. Furthermore, if the child is speaking sadly, the collaboration unit decreases the volume of the audio device.

[0091] When linking with an audio device, the linking unit can select an optimal data format depending on the type of device. The linking unit selects the data format using, for example, an audio format selection technique. For example, the linking unit selects the optimal audio format depending on the type of audio device. The linking unit can also select a data format using a compression format selection technique. For example, the linking unit selects the optimal compression format depending on the type of audio device. The linking unit can also select a data format using a data protocol selection technique to perform optimal data transmission. For example, in the case of a smart speaker, the linking unit prioritizes sending audio data. In the case of a smartphone, the linking unit combines and sends text data and audio data. In the case of a smartwatch, the linking unit prioritizes sending concise text data. As a result, the linking unit can perform optimal data transmission by selecting a data format depending on the type of device.

[0092] When linking with an audio device, the linking unit can analyze the device's usage history and select the optimal linking method. The linking unit, for example, analyzes the device's usage history using a technology that analyzes usage frequency. For example, the linking unit analyzes the frequency of use of the audio device and selects the optimal linking method. The linking unit can also analyze the device's usage history using a technology that analyzes usage time. For example, the linking unit analyzes the usage time of the audio device and selects the optimal linking method. Furthermore, the linking unit can analyze the device's usage history using a technology that analyzes usage patterns and select the optimal linking method. For example, if the device is used frequently, the linking unit transmits data in real time. On the other hand, if the device is not used often, the linking unit transmits data sparingly. Furthermore, the linking unit selects the optimal data transmission timing based on the device's usage history. As a result, the linking unit selects the optimal linking method based on the device's usage history, enabling more efficient data transmission.

[0093] When linking with an audio device, the linking unit can transmit data by reflecting the user settings of the device. The linking unit, for example, transmits data using a technology that reflects a volume setting. For example, the linking unit transmits data by reflecting the volume setting of the audio device. The linking unit can also transmit data using a technology that reflects a notification setting. For example, the linking unit transmits data by reflecting the notification setting of the audio device. The linking unit can also transmit data using a technology that reflects a language setting, thereby optimally transmitting data. For example, if the user sets the volume of the audio device high, the linking unit transmits data at a high volume. Also, if the user turns off notifications for the audio device, the linking unit prioritizes transmitting text data. Furthermore, if the user changes the language setting of the audio device, the linking unit transmits data in that language. This allows the linking unit to transmit data based on the user settings of the device, enabling more personalized responses.

[0094] The consultation unit can estimate the parent's emotions and adjust the content of the feedback based on the estimated parent's emotions. The consultation unit, for example, estimates the parent's emotions using voice analysis technology. For example, the consultation unit analyzes the parent's tone and speed of voice to estimate the parent's emotions. The consultation unit can also estimate the parent's emotions using facial expression analysis technology. For example, the consultation unit captures the parent's facial expressions with a camera and estimates the parent's emotions using a facial expression analysis algorithm. The consultation unit can also estimate the parent's emotions using text analysis technology. For example, the consultation unit analyzes the text content of the parent's speech to estimate the parent's emotions. This enables the consultation unit to adjust the content of the feedback based on the parent's emotions, thereby enabling more appropriate support. For example, if the parent is feeling stressed, the consultation unit provides gentle feedback such as "It's okay, take a break." If the parent is relaxed, the consultation unit provides encouraging feedback such as "Keep up the good work." If the parent is feeling anxious, the consultation unit offers advice by asking, "Is there something you're worried about?"

[0095] The counseling unit can analyze the parent's past consultation history and provide optimal feedback. The counseling unit, for example, analyzes the parent's consultation history using technology that analyzes past consultation content. For example, the counseling unit analyzes the content of past consultations by the parent and provides optimal feedback. The counseling unit can also analyze the parent's consultation history using technology that analyzes consultation frequency. For example, the counseling unit analyzes how often the parent consults and provides optimal feedback. The counseling unit can also analyze the parent's consultation history using technology that analyzes consultation results and provide optimal feedback. For example, based on the content of the parent's past consultations, the counseling unit provides feedback such as "How was the advice we gave you last time?". Furthermore, based on the feedback the parent received in the past, the counseling unit suggests, "Why don't you try this this time?". Furthermore, based on the parent's past consultation history, the counseling unit confirms, "Was the problem you had last time resolved?" This enables the counseling unit to provide more appropriate support by providing feedback based on the parent's past consultation history.

[0096] The consultation unit can analyze the parent's daily rhythm and provide feedback at optimal timing. The consultation unit, for example, analyzes the parent's daily rhythm using technology that analyzes sleep patterns. For example, the consultation unit analyzes the parent's sleep pattern and selects the optimal timing for feedback. The consultation unit can also analyze the parent's daily rhythm using technology that analyzes activity time. For example, the consultation unit analyzes the parent's activity time and selects the optimal timing for feedback. The consultation unit can also analyze the parent's daily rhythm using technology that analyzes meal times and provide feedback at optimal timing. For example, if the parent is busy in the morning, the consultation unit can provide feedback such as "Take a short break at lunchtime." If the parent is relaxing in the evening, the consultation unit can provide feedback such as "Thank you for another day's hard work." Furthermore, the consultation unit can analyze the parent's daily rhythm and suggest "Take a short break at this time." This allows the consultation unit to provide feedback based on the parent's daily rhythm, enabling more appropriate support.

[0097] The consultation unit can analyze the content of the parent's feedback and accumulate information that will be useful for the next consultation. The consultation unit, for example, analyzes the content of the parent's feedback using technology that analyzes the type of feedback. For example, the consultation unit analyzes the type of feedback received by the parent and accumulates information that will be useful for the next consultation. The consultation unit can also analyze the content of the parent's feedback using technology that analyzes the frequency of feedback. For example, the consultation unit analyzes how often the parent receives feedback and accumulates information that will be useful for the next consultation. Furthermore, the consultation unit can analyze the content of the parent's feedback using technology that analyzes the effectiveness of feedback and accumulate information that will be useful for the next consultation. For example, if a parent says, "I would like to consult about my child's diet," the consultation unit refers to past feedback regarding diet. Also, if a parent says, "I would like to consult about my child's sleep," the consultation unit refers to past feedback regarding sleep. Furthermore, if a parent says, "I would like to consult about my child's studies," the consultation unit refers to past feedback regarding studies. In this way, the consultation unit can provide information that will be useful for the next consultation by accumulating the content of the feedback.

[0098] The consultation unit can estimate the parent's emotions and adjust the tone of the feedback based on the estimated parent's emotions. The consultation unit estimates the parent's emotions using, for example, voice analysis technology. For example, the consultation unit analyzes the tone and speed of the parent's voice to estimate the emotion. The consultation unit can also estimate the parent's emotions using facial expression analysis technology. For example, the consultation unit captures the parent's facial expression with a camera and estimates the emotion using a facial expression analysis algorithm. The consultation unit can also estimate the parent's emotions using text analysis technology. For example, the consultation unit analyzes the text content of the parent's speech to estimate the emotion. This allows the consultation unit to adjust the tone of the feedback based on the parent's emotions, enabling more appropriate support. For example, if the parent is feeling stressed, the consultation unit can give feedback in a gentle tone, such as "It's okay, take a break." If the parent is relaxed, the consultation unit can give feedback in a bright tone, such as "Keep up the good work." If the parent is feeling anxious, the consultation unit can give feedback in a calm tone, such as "Is there anything you're worried about?"

[0099] The counseling unit can analyze the content of the parent's consultation and provide advice from relevant experts. The counseling unit analyzes the content of the parent's consultation using, for example, natural language processing technology. For example, the counseling unit classifies the content of the parent's consultation by topic and provides advice from relevant experts. The counseling unit can also provide advice using a knowledge base of experts. For example, the counseling unit provides advice from relevant experts based on the content of the parent's consultation. Furthermore, the counseling unit can provide appropriate advice for the content of the parent's consultation based on the advice from the experts. For example, if a parent says, "I would like to consult about my child's diet," the counseling unit provides advice from a nutritionist. Also, if a parent says, "I would like to consult about my child's sleep," the counseling unit provides advice from a sleep expert. Furthermore, if a parent says, "I would like to consult about my child's studies," the counseling unit provides advice from an education expert. This enables the counseling unit to provide more appropriate support by providing expert advice.

[0100] The counseling department can analyze the content of the parent's consultation and introduce relevant communities and support groups. The counseling department may analyze the content of the parent's consultation using, for example, natural language processing technology. For example, the counseling department may classify the content of the parent's consultation by topic and introduce relevant communities and support groups. The counseling department may also make introductions using a knowledge base of communities and support groups. For example, the counseling department may introduce relevant communities and support groups based on the content of the parent's consultation. Furthermore, the counseling department may introduce appropriate communities and support groups for the content of the parent's consultation based on advice from experts. For example, if a parent says, "I would like to ask for advice about my child's diet," the counseling department may introduce communities related to diet. Also, if a parent says, "I would like to ask for advice about my child's sleep," the counseling department may introduce support groups related to sleep. Furthermore, if a parent says, "I would like to ask for advice about my child's studies," the counseling department may introduce communities related to studies. In this way, the counseling department can expand the parent's support network by introducing communities and support groups.

[0101] The consultation unit can analyze the content of the parent's consultation and extract information that can be shared by the entire family. The consultation unit analyzes the content of the parent's consultation using, for example, natural language processing technology. For example, the consultation unit classifies the content of the parent's consultation by topic and extracts information that can be shared by the entire family. The consultation unit can also provide information to facilitate family communication. For example, the consultation unit provides information that can be shared by the entire family based on the content of the parent's consultation. Furthermore, the consultation unit can extract information about family events and plans and share it with the entire family. For example, if a parent says, "I would like to consult about my child's diet," the consultation unit provides information about diet that can be shared by the entire family. Also, if a parent says, "I would like to consult about my child's sleep," the consultation unit provides information about sleep that can be shared by the entire family. Furthermore, if a parent says, "I would like to consult about my child's studies," the consultation unit provides information about studies that can be shared by the entire family. In this way, the consultation unit provides information that can be shared by the entire family, thereby smoothing family communication. === Hard Collateral 1-1 === Each of the multiple elements including the above-mentioned listening unit, collaboration unit, and consultation unit is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the listening unit listens to what the child is saying using the microphone 38B of the smart device 14 and responds via the control unit 46A. The collaboration unit transmits the information heard by the listening unit to the audio device via the communication I / F 44 of the smart device 14. The consultation unit is realized by the specific processing unit 290 of the data processing device 12 and provides feedback to the parent based on the transmitted information. === Hard Collateral 1-2 === Each of the multiple elements including the above-mentioned listening unit, collaboration unit, and consultation unit is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the listening unit listens to what the child is saying using the microphone 238 of the smart glasses 214 and returns a response via the control unit 46A. The collaboration unit transmits the information heard by the listening unit to the audio device via the communication I / F 44 of the smart glasses 214. The consultation unit is realized by the specific processing unit 290 of the data processing device 12 and provides feedback to the parent based on the transmitted information. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned listening unit, collaboration unit, and consultation unit is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the listening unit listens to what the child is saying using the microphone 238 of the headset type terminal 314 and returns a response via the control unit 46A. The collaboration unit transmits the information heard by the listening unit to the audio device via the communication I / F 44 of the headset type terminal 314. The consultation unit is realized by the specific processing unit 290 of the data processing device 12 and provides feedback to the parent based on the transmitted information. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned listening unit, collaboration unit, and consultation unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the listening unit listens to what the child is saying using the microphone 238 of the robot 414 and returns a response via the control unit 46A. The collaboration unit transmits the information heard by the listening unit to the audio device via the communication I / F 44 of the robot 414. The consultation unit is realized by the specific processing unit 290 of the data processing device 12 and provides feedback to the parent based on the transmitted information.

[0102] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0103] The listening section not only listens to what children say, but can also generate questions to draw out their interests and concerns. For example, if a child says, "I played at the park today," the listening section will ask, "What kind of games did you play?", digging deeper into what the child is saying. If a child says, "I made a new friend," the listening section will ask, "What's his / her name?", encouraging the child to continue talking. Furthermore, if a child says, "I drew a picture," the listening section will ask, "What kind of picture did you draw?", drawing out the child's creativity. In this way, the listening section not only listens to what children say, but also draws out their interests and concerns, enabling richer dialogue.

[0104] The communication module can analyze the content of a child's conversation and suggest appropriate actions to parents. For example, if a child says, "I had fun at school today," the communication module might suggest, "Try listening to your child talk more about school." If a child says, "I had a fight with a friend," the communication module might advise, "Listen carefully to how your child feels." If a child says, "My homework is difficult," the communication module might suggest, "Help your child with their homework." In this way, the communication module can support communication with children by suggesting appropriate actions to parents based on the content of their children's conversations.

[0105] The counseling department can monitor parents' stress levels and make relaxation suggestions at appropriate times. For example, if a parent feels "tired lately," the counseling department can suggest "take a short break and relax." If a parent feels "you can't spend time with your child," the counseling department can advise "review your schedule to make time to spend together." Furthermore, if a parent feels "you're having trouble raising your child," the counseling department can suggest "consulting a specialist is one option." In this way, the counseling department can provide psychological support to parents by monitoring their stress levels and making relaxation suggestions at appropriate times.

[0106] The listening team can analyze the content of what a child is saying and provide relevant learning resources. For example, if a child says, "I want to know about dinosaurs," the listening team might suggest, "Let's read a book or watch a video about dinosaurs together." Or, if a child says, "I want to know about space," the listening team might suggest, "Let's watch a documentary about space." Or, if a child says, "I like drawing," the listening team might suggest, "Let's check out a website that teaches you how to draw." In this way, the listening team can support children's learning by providing relevant learning resources based on the content of what the child is saying.

[0107] The coordination unit can estimate a child's emotions and adjust the content of notifications sent to parents based on the estimated child's emotions. For example, if a child sounds sad, the coordination unit will notify parents, "It seems your child is sad. Please listen to him / her." If a child sounds excited, the coordination unit will notify parents, "It seems your child is excited. It seems like something fun happened." If a child sounds anxious, the coordination unit will notify parents, "It seems your child is anxious. Please reassure him / her." This allows the coordination unit to adjust the content of notifications sent to parents based on the child's emotions, enabling more appropriate responses.

[0108] The counseling department can estimate the parents' emotions and adjust the content of the feedback based on the estimated emotions of the parents. For example, if the parents are feeling stressed, the counseling department will provide gentle feedback such as "It's okay, take a break." If the parents are relaxed, the counseling department will provide encouraging feedback such as "Keep up the good work." Furthermore, if the parents are feeling anxious, the counseling department will offer advice such as "Is there anything you're worried about?" This allows the counseling department to provide more appropriate support by adjusting the content of the feedback based on the parents' emotions.

[0109] The listening department can analyze the content of a child's conversation and suggest related games and activities. For example, if a child says, "I want to play outside," the listening department will suggest, "How about playing in the park?" If a child says, "I want to draw a picture," the listening department will suggest, "Let's draw a picture together." If a child says, "I want to play a game," the listening department will ask, "What kind of game do you like?" and make a suggestion. In this way, the listening department can draw a child's interest by suggesting games and activities based on the content of the child's conversation.

[0110] The communication module can analyze the content of a child's conversation and suggest appropriate actions to parents. For example, if a child says, "I had fun at school today," the communication module might suggest, "Try listening to your child talk more about school." If a child says, "I had a fight with a friend," the communication module might advise, "Listen carefully to how your child feels." If a child says, "My homework is difficult," the communication module might suggest, "Help your child with their homework." In this way, the communication module can support communication with children by suggesting appropriate actions to parents based on the content of their children's conversations.

[0111] The counseling department can analyze the parents' past consultation history and provide optimal feedback. For example, based on the content of the parents' past consultations, the counseling department can provide feedback such as, "How was the advice we gave you last time?". The counseling department can also refer to the feedback the parents received in the past and suggest, "Why don't you try this this time?". Furthermore, based on the parents' past consultation history, the counseling department can confirm, "Was the previous problem resolved?" This allows the counseling department to provide feedback based on past consultation history, enabling more appropriate support.

[0112] The listening section analyzes the content of a child's conversation and can extract information that can be shared by the entire family. For example, if a child is talking about a family trip, the listening section will respond by saying, "It's fun to go with the whole family." If a child is talking about a family event, the listening section will suggest, "Let's all have fun together." If a child is talking about family meals, the listening section will respond by saying, "It's fun to eat together." In this way, the listening section can extract information that can be shared by the entire family, which will facilitate smooth family communication.

[0113] The processing flow of the second embodiment will be briefly explained below.

[0114] Step 1: The listening team listens to what the children have to say. Children's stories include everyday conversations, worries, and emotional expressions. For example, if a child says, "I had fun at school today," the team responds by saying, "That's great! What did you enjoy?" Step 2: The communication unit sends the information listened to by the listening unit to an audio device. Audio devices include smart speakers and voice assistants. For example, parents can listen to their children's conversations through the audio device while doing housework. Step 3: The consultation department provides feedback to parents based on the information sent by the coordination department. The feedback can include voice messages, text messages, advice, etc. For example, if a parent feels that their child has not been in good spirits recently, the consultation department can provide advice such as, "That's worrying. Has anything special happened?"

[0115] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0116] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0117] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0118] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0119] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0120] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0121] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0122] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0123] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0124] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0125] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0126] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0127] 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.

[0128] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0129] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0130] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0131] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0132] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0133] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0134] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0135] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0136] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0137] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0138] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0139] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0140] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0141] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0142] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0143] 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.

[0144] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0145] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0146] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0147] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0148] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0149] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0150] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0151] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0152] 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.

[0153] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0154] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0155] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0156] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0157] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0158] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0159] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0160] 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.

[0161] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0162] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0163] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0164] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0165] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0166] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0167] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0168] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0169] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0170] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0171] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0172] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0173] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0174] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0175] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0176] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0177] 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.

[0178] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0179] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0180] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0181] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0182] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0183] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0184] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0185] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0186] [Explanation of symbols]

[0187] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A listening club that listens to children's stories, a linking unit that transmits the information listened to by the listening unit to an audio device; a consultation unit that provides feedback to the parent / guardian based on the information transmitted by the cooperation unit; Equipped with A system characterized by:

2. The listening unit Equipped with an analysis unit that analyzes children's speech 2. The system of claim 1.

3. The linking unit is Linking with audio devices 2. The system of claim 1.

4. The consultation department: Equipped with a section that provides feedback from mothers 2. The system of claim 1.

5. The listening unit Respond calmly to what your child says 2. The system of claim 1.

6. The linking unit is Get real-time insight into your interactions with your child 2. The system of claim 1.

7. The consultation department: Give advice to moms 2. The system of claim 1.

8. The listening unit Estimate the child's emotions and dig deeper into the content of the conversation based on the estimated emotions.

2. The system of claim 1.

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