system

Abstract

A system is provided.SOLUTION: A system including means for collecting data from a microphone and a motion sensor attached to an animal, means for transmitting the data to cloud storage, means for collating the data with past accumulated data and analyzing the data by AI, means for generating a voice chat on the basis of an analysis result, means for providing the generated voice chat to a user, and means including an SNS function for sharing information with another user.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] In modern society, it is common for pets to live with us as family members, but it is not easy for owners to accurately understand their pets' emotions and desires. In particular, with the rise of nuclear families and single-person households, as well as the aging population, there is a growing need for better communication with pets. However, there is a problem of a lack of effective tools to understand dogs' feelings. [Means for solving the problem]

[0005] This invention provides a system that uses microphones and motion sensors attached to animals to collect animal sounds and behavior data and transmits that data to cloud storage. Furthermore, AI analyzes the data by comparing it with previously accumulated data and generates voice chats based on the analysis results. This voice chat is provided to users, allowing them to communicate as if they were having a conversation with their beloved dog. The system also includes a social networking function for sharing information with other users, promoting information exchange among dog lovers.

[0006] "Animals" refers to living creatures such as dogs kept as pets.

[0007] A "microphone" refers to a device that picks up animal sounds and outputs them as an analog signal.

[0008] "Motion sensor" refers to a device that detects animal movement and generates movement data.

[0009] "Data" refers to information collected from microphones and motion sensors, including information about sounds and movements.

[0010] "Cloud storage" refers to storage devices on remote servers for storing and managing data over the Internet.

[0011] "Digital signal" refers to a signal that is an analog signal converted into digital form.

[0012] "AI (artificial intelligence)" refers to algorithms and systems that analyze collected data and infer the emotions and desires of animals.

[0013] "Analysis" refers to the process of interpreting collected data and deriving meaningful information.

[0014] "Voice chat" refers to voice messages that express the emotions and desires of animals, generated based on the analyzed results.

[0015] "User" refers to a person who uses the system to communicate with animals.

[0016] "SNS function" refers to an online platform that promotes information sharing and communication between users. [Brief explanation of the drawings]

[0017] [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. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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, a 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), and an APU (Accelerated Processing Unit).

[0021] 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.

[0022] 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.

[0023] 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), Bluetooth (registered trademark), etc.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0029] 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.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention provides a system for communicating with animals by generating voice chat using a microphone and a motion sensor attached to the animal. This system is composed of the following means.

[0039] Data collection and transmission methods

[0040] Device:

[0041] A microphone and motion sensor attached to the animal's collar collects vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into a digital signal in real time and temporarily stored in the device's memory. The device then transmits this data to a server at regular intervals.

[0042] Data analysis and voice chat generation methods

[0043] server:

[0044] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The AI ​​model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[0045] A means for providing voice chat to users

[0046] User:

[0047] Users launch a dedicated app on their device and connect to the server. The app downloads voice chat data from the server and provides voice chat to users. The voice chat data is played back using the device's speaker, allowing users to enjoy interacting with animals.

[0048] SNS function means

[0049] server:

[0050] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[0051] User:

[0052] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[0053] Specific examples

[0054] Example 1: Data collection and transmission

[0055] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then sends it to the server in a batch process.

[0056] Example 2: Voice chat generation

[0057] The server retrieves the collected data from cloud storage, and the AI ​​model analyzes that "the dog is excited." As a result of the analysis, it generates the text "I feel like playing," and the voice synthesis system creates a voice chat saying "Let's play!" The user plays the voice chat in the app and understands the dog's feelings.

[0058] Example 3: Social networking features

[0059] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments to communicate with each other.

[0060] The processing flow will be explained below.

[0061] Program processing flow

[0062] Data collection and transmission methods

[0063] Device:

[0064] Step 1:

[0065] Microphones and motion sensors capture animal sounds and movements in real time.

[0066] Step 2:

[0067] Convert the captured analog signal into a digital signal.

[0068] Step 3:

[0069] The converted digital signal is temporarily stored in the terminal's memory.

[0070] Step 4:

[0071] At regular intervals, the terminal processes a batch of digital data in its memory and sends it to the server.

[0072] Data analysis and voice chat generation methods

[0073] server:

[0074] Step 1:

[0075] The server receives the data sent from the terminal.

[0076] Step 2:

[0077] The received data is temporarily stored in local storage.

[0078] Step 3:

[0079] Periodically, the server uploads the temporarily stored data to cloud storage.

[0080] Step 4:

[0081] Get the latest data from cloud storage.

[0082] Step 5:

[0083] An AI model analyzes the collected data and infers the animal's emotions and desires.

[0084] Step 6:

[0085] Based on the analysis results, text for voice chat is generated.

[0086] Step 7:

[0087] The generated text is input into a speech synthesis system to generate a voice chat.

[0088] Step 8:

[0089] The generated voice chat is stored in the server, and preparations for providing it to the user are completed.

[0090] A means for providing voice chat to users

[0091] User:

[0092] Step 1:

[0093] The user launches the dedicated app.

[0094] Step 2:

[0095] The app will connect to the server and download the latest voice chat data.

[0096] Step 3:

[0097] The downloaded voice chat data is displayed within the app and a play button is provided.

[0098] Step 4:

[0099] When the user presses the play button, the app will play the voice chat using the device's speaker.

[0100] SNS function means

[0101] User:

[0102] Step 1:

[0103] A user creates a new post in the app and enters text and images.

[0104] Step 2:

[0105] When the user presses the post button, the post data is sent from the terminal to the server.

[0106] server:

[0107] Step 1:

[0108] The server receives the posted data sent by the user.

[0109] Step 2:

[0110] Save the received post data in the database.

[0111] Step 3:

[0112] Send push notifications to let other users know that you have posted something new.

[0113] User (other users):

[0114] Step 1:

[0115] Other users receive notifications of new posts.

[0116] Step 2:

[0117] Other users open the app and see your new posts.

[0118] Step 3:

[0119] Other users leave comments and start communicating with the poster.

[0120] Example 1

[0121] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0122] Currently, communication between humans and animals is primarily visual and tactile, making it difficult to accurately understand animals' emotions and desires. In particular, because animals cannot verbally express what they are feeling, owners often misunderstand their animals' condition. In addition, there are limited ways for owners with similar interests to share information, making it difficult to form a community.

[0123] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0124] In this invention, the server includes a means for acquiring data from a cloud storage device and analyzing the data using a generative AI model, a means for generating voice conversation data based on the analysis results, and a means for storing the voice conversation data generated using a voice synthesizer on the server. This makes it possible to accurately predict an animal's emotions and desires, verbalize them, and provide them to the owner. This also enables smooth information sharing and communication with other pet owners using the system.

[0125] An "audio collection device" is a device that collects animal sounds and converts them into digital signals.

[0126] A "motion detection device" is a device that detects animal movements and collects that data.

[0127] An "internal storage device" is a storage medium for temporarily storing collected data.

[0128] A "server" is a computer system that receives, stores, and processes data sent from a terminal.

[0129] "Cloud storage" is a remote storage medium for storing and managing data over the Internet.

[0130] A "generative AI model" is an artificial intelligence model that analyzes collected data and infers an animal's emotions and desires based on the results.

[0131] "Speech conversation data" is data obtained by converting text generated based on the analysis results into speech.

[0132] A "voice synthesizer" is a device for converting text data into voice data.

[0133] A "dedicated application" is software that a user uses to communicate with a server and to download and play back voice conversation data.

[0134] A "terminal device" is a device that a user uses to launch a dedicated application.

[0135] The "communication function" is a function for sharing information with other users and communicating with each other.

[0136] The present invention is a system that uses a voice collection device and a motion detection device attached to an animal to collect data, analyze the data, and infer the animal's emotions and desires. This system also includes a function to generate voice conversation data based on the analysis results and provide it to the user. It also includes a communication function to share information between users.

[0137] Data collection equipment

[0138] Device:

[0139] An audio collection device (microphone) and a motion detection device (motion sensor) collect animal sounds and movement data in real time and convert them into digital signals.

[0140] The converted digital data is temporarily stored in an internal storage device.

[0141] At regular intervals (for example, every 5 minutes), the collected data is sent to the server.

[0142] Server-side processing

[0143] server:

[0144] Receives data sent from the device and temporarily stores it in local storage.

[0145] The data is periodically uploaded to a cloud storage device.

[0146] Data is retrieved from cloud storage and voice and movement data is analyzed using a generative AI model.

[0147] Through analysis, the animal's emotions and desires are inferred, and text data for voice conversations is generated based on the results.

[0148] A voice synthesizer is used to convert text data into voice data, and the generated voice conversation data is stored on a server.

[0149] User-Facing Features

[0150] User:

[0151] A dedicated application is started on the terminal device and connected to the server.

[0152] By downloading voice conversation data from the server and playing it back through the speaker of the terminal device, the user can understand the emotions and desires of the animal.

[0153] Users can also share information and communicate with other pet owners through a dedicated application.

[0154] Specific examples

[0155] Examples of data collection and transmission:

[0156] When a dog barks, the sound collection device captures the sound, and the motion detection device captures the dog's running data. The data is converted into digital signals and sent to a server every five minutes.

[0157] Example of voice chat generation:

[0158] The server uses a generative AI model to analyze the data retrieved from cloud storage. As a result of the analysis, it is inferred that "the dog is excited" and the text "I want to play" is generated. The speech synthesizer then generates voice conversation data saying "Let's play!" and saves it on the server.

[0159] Examples of social media features:

[0160] User A posts "What happened on today's walk" through a dedicated application and sends it to the server. The server saves this post in a database and notifies other users. Other users view it and post comments such as "My dog ​​also met another dog for the first time on a walk!"

[0161] Prompt Sentence Examples

[0162] "Please analyze the audio data of the dog barking, infer what the dog is feeling, and generate a voice chat. At the same time, please include a function that allows other users to leave comments in response."

[0163] This system makes it possible to accurately understand the emotions and desires of animals, and also facilitates smooth communication between users.

[0164] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0165] Step 1:

[0166] Data collection and conversion (terminal)

[0167] A sound collection device (microphone) attached to the animal's collar picks up the animal's sounds, and a motion detection device (motion sensor) detects the animal's movements.

[0168] (Input): Animal sounds and movements

[0169] (Data processing): Converting collected data into digital signals

[0170] (Output): Digitally converted voice and motion data

[0171] Step 2:

[0172] Temporary data storage (device)

[0173] The terminal temporarily stores the converted digital signal in its internal memory.

[0174] (Input): Digitally encoded voice data and movement data

[0175] (Data storage): Save data to the internal storage device

[0176] (Output): Temporarily stored digital data

[0177] Step 3:

[0178] Data transmission (terminal)

[0179] The device sends the temporarily stored data to the server at regular intervals (e.g., every 5 minutes).

[0180] (Input): Temporarily stored digital data

[0181] (Data transmission): Sends data to the server at regular intervals

[0182] (Output): Data sent to the server

[0183] Step 4:

[0184] Receiving and temporarily storing data (server)

[0185] The server receives the voice data and motion data sent from the terminal and temporarily stores them in local storage.

[0186] (Input): Digital data sent from the terminal

[0187] (Data storage): Temporarily save data to local storage

[0188] (Output): Temporarily saved data

[0189] Step 5:

[0190] Upload to the cloud (server)

[0191] The server uploads the temporarily stored data to a storage device on the cloud at a fixed frequency.

[0192] (Input): Data temporarily saved in local storage

[0193] (Data transmission): Upload data to a cloud storage device

[0194] (Output): Data stored on the cloud

[0195] Step 6:

[0196] Data analysis (server)

[0197] The server retrieves the latest data from cloud storage and analyzes the audio and motion data using generative AI models.

[0198] (Input): Data retrieved from the cloud

[0199] (Data analysis): Analyzing animal emotions and desires using generative AI models

[0200] (Output): Analysis results (animal emotions and desires)

[0201] Step 7:

[0202] Voice chat generation (server)

[0203] Based on the analysis results, text data for voice conversation is generated.

[0204] A speech synthesizer is used to convert the text data into speech data.

[0205] (Input): Text data as analysis results

[0206] (Data generation): Generate voice conversation data

[0207] (Output): Generated voice conversation data

[0208] Step 8:

[0209] Save voice chat (server)

[0210] The generated voice conversation data is stored on the server.

[0211] (Input): Generated voice conversation data

[0212] (Data storage): Save data to the server

[0213] (Output): Saved voice conversation data

[0214] Step 9:

[0215] App launch and connection (user)

[0216] The user starts the dedicated application on the terminal device and connects to the server.

[0217] (Input): User application launch

[0218] (Action): Connect to the server

[0219] (Output): Server connection status

[0220] Step 10:

[0221] Download and play voice chat (user)

[0222] The user downloads voice conversation data from the server and plays it back through the speaker of the terminal device.

[0223] (Input): Voice conversation data stored on the server

[0224] (Data download and playback): Download and play data

[0225] (Output): The audio conversation the user hears

[0226] Step 11:

[0227] Use of SNS functions (users)

[0228] Users can share information and communicate with other pet owners through a dedicated application.

[0229] (Input): User post

[0230] (Information sharing and interaction): Sharing information and exchanging comments with other users

[0231] (Output): Submitted posts, comments, and feedback from other users

[0232] (Application example 1)

[0233] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0234] In order to enhance communication with animals, conventional methods have had difficulty in fully analyzing information obtained from sounds and movements and effectively providing it to users. Also, when enjoying interactions with animals in physical stores such as pet shops and animal cafes, there was a lack of means for visitors to understand the animals' emotions and desires in real time, making it difficult to communicate effectively.

[0235] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0236] In this invention, the server includes a means for collecting data from a microphone and a motion sensor attached to the animal, a means for transmitting the data to cloud storage, and a means for comparing the data with past accumulated data and analyzing the data using a generative AI model, thereby enabling users to experience interactions with animals in real time and provide generated voice chats.

[0237] A "microphone" is a device worn by an animal to collect audio data.

[0238] A "motion sensor" is a device for detecting and collecting animal movement data.

[0239] "Cloud storage" is a data storage system via the Internet that stores collected data and uses it for analysis.

[0240] A "generative AI model" is an algorithm that analyzes collected data and infers an animal's emotions and desires.

[0241] "Voice chat" refers to voice messages generated based on the analysis results for communication with users.

[0242] "SNS function" refers to a social networking service function that allows users to share information and communicate with other users.

[0243] A "user terminal" is a device that is installed in a physical store where animals are present, allowing users to experience interactions with the animals in real time.

[0244] "Real-time" is a concept that indicates that data is collected and processed instantaneously, providing results without delay.

[0245] "Audio data" is data that has been converted into digital form from sounds made by animals (such as cries).

[0246] "Movement data" is data that is detected when an animal moves (walking, jumping, standing still, etc.) and converted into digital format.

[0247] "Interaction" refers to the act or phenomenon in which the user and the animal influence each other.

[0248] The present invention is a system for generating voice chats using a microphone and motion sensor attached to an animal to enable communication with the animal, and this system is implemented as follows.

[0249] Data collection and transmission methods

[0250] Device:

[0251] A microphone and motion sensor attached to the animal's collar collects vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into a digital signal in real time and temporarily stored in the device's memory. The device then transmits this data to a server at regular intervals.

[0252] Data analysis and voice chat generation methods

[0253] server:

[0254] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The generative AI model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[0255] A means for providing voice chat to users

[0256] User:

[0257] Users launch a dedicated app on a device installed in the store and connect to the server. The app has the function of downloading voice chat data from the server and providing voice chat to users. The voice chat data is played back using the device's speaker, allowing users to enjoy interacting with the animals.

[0258] SNS function means

[0259] server:

[0260] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[0261] User:

[0262] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[0263] Specific examples

[0264] As a concrete example, a user visits a pet shop and tries to interact with a cat. The voice chat generated by this app plays back a voice saying, "This cat is relaxed." By inputting the following prompt sentences into the generative AI model, the voice chat generation becomes more efficient:

[0265] Prompt Sentence Examples

[0266] "Analyze the cat's meows to determine if it is relaxed, and generate a voice chat message that says, 'This cat is relaxed.'"

[0267] In this way, the system of the present invention can greatly improve communication with animals.

[0268] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0269] Step 1:

[0270] Data collection

[0271] Terminal: A microphone and motion sensor attached to the animal's collar collects animal sounds and movement data in real time.

[0272] Input: Animal sounds and movements.

[0273] Output: Audio and motion data converted into digital format.

[0274] Specific operation: The microphone collects voice data, and the motion sensor collects movement data and converts it into a digital signal.

[0275] Step 2:

[0276] Data transmission

[0277] Terminal: Collected digital data is temporarily stored in the terminal's memory and sent to the server at regular intervals.

[0278] Input: Audio and motion data in digital form.

[0279] Output: The data sent to the server.

[0280] Specific operation: The terminal sends data to the server at regular batch processing intervals.

[0281] Step 3:

[0282] Data reception and storage

[0283] Server: Receives data sent from the device, temporarily stores it in local storage, and periodically uploads it to cloud storage.

[0284] Input: Data sent from the device to the server.

[0285] Output: Data uploaded to cloud storage.

[0286] Specific operation: Save the data to local storage and then upload it to cloud storage.

[0287] Step 4:

[0288] Data analysis

[0289] Server: Based on the data retrieved from cloud storage, the generative AI model analyzes the data and infers the animal's emotions and desires.

[0290] Input: Data retrieved from cloud storage.

[0291] Output: Analysis results showing the animal's emotions and desires.

[0292] Specific behavior: The generative AI model analyzes audio and behavior data to infer the animal's emotions and desires.

[0293] Step 5:

[0294] Voice chat generation

[0295] Server: Generates text for voice chat based on the analysis results and converts the text into speech using a speech synthesis system.

[0296] Input: Analysis results indicating animal emotions and desires.

[0297] Output: The generated voice chat.

[0298] Specific operation: Based on the analysis results of the generative AI model, text is generated and voice chat is created using a speech synthesis system.

[0299] Step 6:

[0300] Voice chat playback

[0301] User: Launches a dedicated app on a device installed in a physical store, downloads voice chat data from the server, and plays it back.

[0302] Input: Voice chat data downloaded from the server.

[0303] Output: The audio chat that is played to the user.

[0304] Specific operation: The user plays the voice chat in real time through the device speaker.

[0305] Step 7:

[0306] Social networking features

[0307] User: Use the function to communicate with other users through a dedicated app.

[0308] Input: User submitted data and comment data.

[0309] Output: Updates that other users will be notified about.

[0310] What happens: Your post or comment is sent to the server and other users are notified.

[0311] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0312] The present invention is a system that uses a microphone and motion sensors attached to an animal to generate voice chat and communicate with the animal. This system also combines an emotion engine that recognizes the user's emotions to provide a more interactive experience. The present invention is composed of the following means.

[0313] Data collection and transmission methods

[0314] Device:

[0315] Microphones and motion sensors attached to the animal's collar collect vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into digital signals in real time and temporarily stored in the device's memory. The data is then batch-processed and sent to a server at regular intervals.

[0316] Data analysis and voice chat generation methods

[0317] server:

[0318] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The AI ​​model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[0319] A method for recognizing user emotions using an emotion engine

[0320] server:

[0321] The emotion engine recognizes emotions by analyzing the user's voice and facial expression data. For example, the emotion recognition algorithm analyzes the user's voice when speaking into the app and facial expression data captured by the camera to determine the user's emotional state.

[0322] A means for providing voice chat to users

[0323] User:

[0324] Users launch a dedicated app on their device and connect to the server. The app downloads voice chat data from the server and provides the user with voice chat. The voice chat data is played back using the device's speaker, allowing the user to enjoy interacting with the animals. Furthermore, the content of the generated voice chat is dynamically adjusted based on the user's emotions recognized by the emotion engine.

[0325] SNS function means

[0326] server:

[0327] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[0328] User:

[0329] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[0330] Specific examples

[0331] Example 1: Data collection and transmission

[0332] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then sends it to the server in a batch process.

[0333] Example 2: Voice chat generation

[0334] The server retrieves the collected data from cloud storage, and the AI ​​model analyzes that "the dog is excited." As a result of the analysis, it generates the text "I feel like playing," and the voice synthesis system creates a voice chat saying "Let's play!" The user plays the voice chat in the app and understands the dog's feelings.

[0335] Example 3: Dynamic voice chat with emotion engine

[0336] The emotion engine analyzes the user's voice and facial expression data and recognizes that the user is happy. When this happens, the server adds a message to the generated voice chat that matches the user's emotion, such as "Let's play together!" The user receives this message in the app, allowing for deeper interaction.

[0337] Example 4: SNS function

[0338] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments to communicate with each other.

[0339] The processing flow will be explained below.

[0340] Program processing flow

[0341] Data collection and transmission methods

[0342] Device:

[0343] Step 1:

[0344] Microphones and motion sensors capture animal sounds and movements in real time.

[0345] Step 2:

[0346] Convert the captured analog signal into a digital signal.

[0347] Step 3:

[0348] The converted digital signal is temporarily stored in the terminal's memory.

[0349] Step 4:

[0350] At regular intervals, the terminal processes a batch of digital data temporarily stored in memory and transmits it to the server.

[0351] Data analysis and voice chat generation methods

[0352] server:

[0353] Step 1:

[0354] The server receives the data sent from the terminal.

[0355] Step 2:

[0356] The received data is temporarily stored in local storage.

[0357] Step 3:

[0358] Periodically, the server uploads the temporarily stored data to cloud storage.

[0359] Step 4:

[0360] Get the latest data from cloud storage.

[0361] Step 5:

[0362] An AI model analyzes the collected data and infers the animal's emotions and desires.

[0363] Step 6:

[0364] Based on the analysis results, text for voice chat is generated.

[0365] Step 7:

[0366] The generated text is input into a speech synthesis system to generate a voice chat.

[0367] Step 8:

[0368] The generated voice chat is stored in the server, and preparations for providing it to the user are completed.

[0369] A method for recognizing user emotions using an emotion engine

[0370] server:

[0371] Step 1:

[0372] Collect user voice and facial expression data from input devices (microphones, cameras, etc.) for emotion recognition.

[0373] Step 2:

[0374] Emotion recognition algorithms analyze collected voice and facial expression data to determine the user's emotional state.

[0375] Step 3:

[0376] To dynamically adjust the content of a voice chat based on a user's emotional state.

[0377] A means for providing voice chat to users

[0378] User:

[0379] Step 1:

[0380] The user launches the dedicated app.

[0381] Step 2:

[0382] The app will connect to the server and download the latest voice chat data.

[0383] Step 3:

[0384] The downloaded voice chat data is displayed within the app and a play button is provided.

[0385] Step 4:

[0386] When the user presses the play button, the app will play the voice chat using the device's speaker.

[0387] SNS function means

[0388] User:

[0389] Step 1:

[0390] A user creates a new post in the app and enters text and images.

[0391] Step 2:

[0392] When the user presses the post button, the post data is sent from the terminal to the server.

[0393] server:

[0394] Step 1:

[0395] The server receives the posted data sent by the user.

[0396] Step 2:

[0397] Save the received post data in the database.

[0398] Step 3:

[0399] Send push notifications to let other users know that you have posted something new.

[0400] User (other users):

[0401] Step 1:

[0402] Other users receive notifications of new posts.

[0403] Step 2:

[0404] Other users open the app and see your new posts.

[0405] Step 3:

[0406] Other users leave comments and start communicating with the poster.

[0407] Specific examples

[0408] Example 1: Data collection and transmission

[0409] Step 1:

[0410] The device uses a microphone to capture audio data of the dog barking.

[0411] Step 2:

[0412] The captured audio data is converted into a digital signal in real time.

[0413] Step 3:

[0414] The converted digital signal is temporarily stored in the terminal's memory.

[0415] Step 4:

[0416] Send audio data to the server in batch processing.

[0417] Example 2: Voice chat generation

[0418] Step 1:

[0419] The server retrieves the collected data from the cloud storage.

[0420] Step 2:

[0421] The AI ​​model analyzes that the dog is in an excited state.

[0422] Step 3:

[0423] Based on the analysis results, the text "I feel like playing" is generated.

[0424] Step 4:

[0425] The generated text is converted into a voice chat message such as "Let's play!" using a speech synthesis system.

[0426] Step 5:

[0427] Users can understand their dog's feelings by playing back audio chats through the app.

[0428] Example 3: Dynamic voice chat with emotion engine

[0429] Step 1:

[0430] The server's emotion engine collects and analyzes the user's voice and facial expression data.

[0431] Step 2:

[0432] The emotion engine recognizes when the user is happy.

[0433] Step 3:

[0434] The server generates a voice chat that includes the additional message "Let's play together!"

[0435] Step 4:

[0436] The user receives this message in the app and enjoys deeper interaction.

[0437] Example 4: SNS function

[0438] Step 1:

[0439] User A posts "What happened on today's walk" on the app.

[0440] Step 2:

[0441] The posted data is sent to the server and stored in a database.

[0442] Step 3:

[0443] The server sends notifications of new posts to other users.

[0444] Step 4:

[0445] Other users receive notifications and view your posts.

[0446] Step 5:

[0447] Other users can post comments and communicate with each other.

[0448] Example 2

[0449] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0450] In modern times, communication between animals and humans is extremely important, but there is a lack of effective means to understand animal behavior and emotions. There are also technical challenges to properly infer animal emotions from their behavior and vocalizations, enabling more accurate and meaningful communication. Furthermore, there is a need for an effective way to share information about animals with other users.

[0451] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0452] In this invention, the server includes a means for collecting data from the voice input device and the motion detection device attached to the animal, a means for transmitting the data to storage on a communication network, and a means for comparing the data with previously stored data and analyzing it using artificial intelligence. This allows for accurate understanding of the animal's behavior and emotions in real time and for generating voice conversations directed at the user, enabling richer communication. Furthermore, by combining an information sharing function for sharing information with other users, a system is provided that allows for the widespread sharing of information and experiences about animals.

[0453] An "audio input device" is a device for collecting animal sounds, and includes a microphone and the like.

[0454] A "motion detection device" is a sensor for detecting animal movements, and includes an acceleration sensor, a gyro sensor, and the like.

[0455] "Data collection means" refers to a function that automatically collects animal sound and movement data.

[0456] "Storage on a communication network" refers to a data storage area that can be accessed via the Internet, etc., and includes cloud storage.

[0457] "Data transmission means" refers to a function for transmitting collected data to a remote system such as a server.

[0458] "Artificial intelligence analysis methods" refers to technologies that use algorithms and machine learning models to analyze collected data and infer animal behavior and emotions.

[0459] "Voice conversation generation means" refers to the function of generating text based on the analysis results and converting it into speech using speech synthesis technology.

[0460] "User provision means" refers to a function for providing the generated voice conversation to the user through a voice output device.

[0461] "Information sharing function" refers to the social networking service (SNS) function for sharing information between users.

[0462] "Past accumulated data" refers to data on animal sounds and movements that have been collected and stored to date, and is a data set that will be used for analysis.

[0463] The present invention is a system that uses a voice input device and a motion detection device attached to an animal to collect, analyze, and provide animal voice and motion data to users, with the aim of realizing interactive communication with animals.

[0464] Data collection methods

[0465] Device:

[0466] The audio input device (microphone) and motion detection devices (accelerometer, gyro sensor) attached to the animal's collar collect the animal's sounds and movement data in real time. This data is instantly converted into digital signals and temporarily stored in the device's memory.

[0467] Data transmission method

[0468] Device:

[0469] The collected data is batch processed at regular intervals and sent to storage (cloud storage) on the communication network. The TCP / IP protocol is used for communication to ensure secure data transfer.

[0470] Data storage method

[0471] server:

[0472] Receives data sent from the device and temporarily stores it in local storage. The received data is periodically uploaded to cloud storage and safely stored. For example, AWS S3 is used as cloud storage.

[0473] Data Analysis Methods

[0474] server:

[0475] The latest data is retrieved from cloud storage and analyzed using a generative AI model. The AI ​​uses voice recognition and motion analysis algorithms to infer the animal's emotions and desires. The analysis results are generated as text data to understand the animal's behavior and emotions.

[0476] A means of generating voice chat

[0477] server:

[0478] Based on the analysis results, a text for the voice conversation is generated, and the text is converted into speech using a speech synthesis system (e.g., speech synthesis software). The generated speech is stored in the server and later provided to the user.

[0479] Means of user emotion recognition

[0480] server:

[0481] The app uses an emotion engine to analyze the user's voice and facial expression data captured by the camera. It uses voice processing software and facial recognition algorithms to determine the user's emotions, allowing it to dynamically adjust the content of voice chats.

[0482] Means of providing voice chat

[0483] User:

[0484] Users launch the app and download the voice chat data from the server. The downloaded voice chat data is then played through the device's speaker, allowing users to enjoy interacting with the animals.

[0485] SNS function means

[0486] server:

[0487] It receives post data and comment data from users and stores them in a database. It also has the function of sending notifications to other users when there are new posts or comments.

[0488] User:

[0489] Users can communicate with other users through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[0490] Specific examples

[0491] Example 1: Data collection and transmission

[0492] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then transmits the data to a server in batch processing.

[0493] Example 2: Voice chat generation

[0494] The server retrieves the collected data from cloud storage, and the generative AI model analyzes it to determine that the dog is excited. As a result, it generates the text "I want to play," and the voice synthesis system creates a voice chat saying "Let's play!" The user can play the voice chat in the app and understand the dog's feelings.

[0495] Example 3: Dynamic voice chat with emotion engine

[0496] The emotion engine analyzes the user's voice and facial expression data and recognizes that the user is happy. When this happens, the server adds a message to the generated voice chat that matches the user's emotion, such as "Let's play together!" The user receives this message in the app, allowing for deeper interaction.

[0497] Example 4: SNS function

[0498] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments, thereby communicating with each other.

[0499] Prompt Sentence Examples

[0500] 1. "I want to improve the accuracy of an AI model that analyzes why a dog barks."

[0501] 2. "Please suggest ways to improve the emotion engine to accurately recognize whether a user is laughing or not."

[0502] 3. "What are the criteria for selecting an effective speech synthesis system?"

[0503] 4. "Please give us some ideas for new features to encourage social media communication with other dog lovers."

[0504] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0505] Step 1: Data collection

[0506] Device:

[0507] An audio input device (microphone) and motion detection devices (accelerometer, gyro sensor) attached to the animal's collar collect sounds and movement data.

[0508] Input: Animal sounds and movements

[0509] Data processing and calculation: Audio data is collected as an analog signal by a microphone and converted into a digital signal. Movement data is measured by an acceleration sensor and a gyro sensor and converted into digital movement data.

[0510] Output: Digitized voice and motion data

[0511] Step 2: Send data

[0512] Device:

[0513] The collected voice data and movement data are batch processed at regular intervals and sent to a server via a communication network.

[0514] Input: Digitized voice and motion data

[0515] Data processing and calculation: The data is batch processed (a certain amount of data is processed in a batch), and then sent to the server using a communication protocol (e.g. TCP / IP).

[0516] Output: Data sent to the server

[0517] Step 3: Save data

[0518] server:

[0519] Receives data sent from the device and temporarily stores it in local storage, then periodically uploads the received data to cloud storage.

[0520] Input: Data received from the terminal

[0521] Data processing and calculation: The received data is temporarily stored in local storage and then periodically uploaded to cloud storage (e.g., AWS S3).

[0522] Output: Data stored in cloud storage

[0523] Step 4: Data analysis

[0524] server:

[0525] The latest data is retrieved from cloud storage and analyzed using a generative AI model.

[0526] Input: Data retrieved from cloud storage

[0527] Data Processing and Computation: Using speech recognition and motion analysis algorithms to infer animal emotions and behaviors, a generative AI model analyzes the data and classifies the animal's emotional state.

[0528] Output: Text data as the analysis result (e.g., "The dog is excited")

[0529] Step 5: Create a voice chat

[0530] server:

[0531] Based on the analysis results, text for voice conversation is generated and converted into speech using a speech synthesis system.

[0532] Input: Text data as analysis results

[0533] Data processing and calculation: Text data is input into a speech synthesis system to generate natural-sounding voice chat (e.g., "Let's play!"). For speech synthesis, TTS (Text-To-Speech) technology is used, for example.

[0534] Output: Generated audio data

[0535] Step 6: Recognizing User Emotions

[0536] server:

[0537] The emotion engine analyzes the user's voice and facial expression data to determine their emotions.

[0538] Input: User's voice data and facial expression data

[0539] Data Processing and Computation: Using voice processing software and facial recognition algorithms to analyze the user's emotional state and classify the user's emotions.

[0540] Output: User's emotional state

[0541] Step 7: Provide voice chat

[0542] User:

[0543] Users launch a dedicated app and download voice chat data from the server. The app then plays the downloaded voice chat data.

[0544] Input: Generated audio data

[0545] Data processing and calculation: The app receives the audio data from the server and plays it through the speaker.

[0546] Output: Voice chat provided to the user

[0547] Step 8: Social Media Functionality

[0548] server:

[0549] It receives post data and comment data from users and stores them in a database. It also has the function of sending notifications to other users when there are new posts or comments.

[0550] Input: User posted data and comment data

[0551] Data processing and calculation: The received data is stored in a database. When there is a new post or comment, the notification function will notify other users.

[0552] Output: Notified post and comment information

[0553] User:

[0554] Users can use the app to communicate with other users, create and send posts and comments, and receive feedback from other users.

[0555] Input: Feedback from other users

[0556] Data processing and calculation: Read comments from other users and reply as necessary.

[0557] Output: Communication results with other users

[0558] (Application example 2)

[0559] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0560] When pet owners are away from home, there is a lack of means to properly recognize their pet's hunger state and respond promptly. Furthermore, there is a lack of means to enhance communication between pets and owners.

[0561] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the animal's emotions and automatically ordering food delivery if it determines that the animal is hungry, means for collecting data from a microphone and motion sensor attached to the animal, and means for comparing the data with past accumulated data and analyzing it using AI. This makes it possible to remotely and appropriately grasp the pet's hunger state and quickly provide food. It also enhances interactive communication with the user.

[0562] An "animal-worn microphone" is a device used to collect animal audio data.

[0563] A "motion sensor" is a sensor that detects and collects animal movement data.

[0564] "Means for sending data to cloud storage" refers to a system for sending collected data to cloud storage via the Internet.

[0565] "Means of analysis using AI" refers to a system that uses artificial intelligence to analyze collected data and infer the condition of animals.

[0566] The "means for generating voice chat" is a means for converting the animal's intentions into text based on the analysis results, and then converting the text into voice.

[0567] The "means for providing voice chat to users" is a system that provides the generated voice chat to the user's terminal.

[0568] "Means including SNS functions" are functions that allow users to share information and communicate with other users.

[0569] "Means for analyzing an animal's emotions and automatically ordering food delivery if it is determined to be hungry" is a system that analyzes an animal's emotional data and, if it is determined to be hungry, automatically uses a food delivery service to order food.

[0570] "Means of comparing with previously accumulated data" refers to a means of comparing and analyzing data collected in the past with newly collected data.

[0571] This invention uses microphones and motion sensors attached to the animals to collect audio and movement data. The collected data is sent to cloud storage and compared with previously stored data. An AI model then analyzes the data to infer the animal's emotional state.

[0572] If the emotional state of the pet is estimated to be hungry, the server automatically orders food delivery. Specifically, a pet-specific application is installed on the user's device, and voice chat is provided to the user through this application. Information can also be shared with other users via social networking functions.

[0573] The hardware requires a microphone and motion sensors attached to the animal's collar, while the software includes an emotion engine for AI analysis, a voice recognition system to convert voice data into text, and a motion sensor device to detect movement data. It also requires access to cloud storage and food delivery APIs.

[0574] The server performs the following processing based on the collected data.

[0575] 1. Data collection and transmission:

[0576] The microphone collects animal sound data, and the motion sensor detects animal movement data. This data is converted into digital signals in real time, temporarily stored, and then sent to cloud storage at regular intervals.

[0577] 2. Data analysis and voice chat generation:

[0578] The AI ​​model analyzes the data retrieved from cloud storage and infers the animal's emotional state. Based on the analysis results, it generates text for voice chat and converts the text into speech using a speech synthesis system. The generated voice chat is stored on a server.

[0579] 3. Automated food delivery ordering:

[0580] If the animal's emotion is determined to be hungry, the server automatically issues a food delivery order, sending the necessary information including the user ID and pet ID, and ordering food.

[0581] 4. Providing voice chat to users:

[0582] Users can receive voice chats through the app to understand their pet's condition, and the app also has a social networking function that allows users to share information with other users.

[0583] For example, if audio data of a dog barking is collected and it corresponds to a state of "hunger," AI analysis will determine that "food delivery should be ordered." When the user checks the app, they will receive a notification saying, "Your pet seems hungry. Food delivery has been ordered," along with feedback via voice chat.

[0584] An example of a prompt is as follows:

[0585] "The sound of a dog barking has been collected. This audio and behavioral data is analyzed to infer that the animal is hungry. Food delivery will be ordered within the next hour."

[0586] In this way, even when the owner is not present, the animal's condition can be properly managed remotely and any necessary measures can be taken promptly.

[0587] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0588] Step 1:

[0589] A microphone and motion sensor attached to the animal's collar collects audio and movement data in real time. The microphone captures the animal's sounds, and the motion sensor detects the animal's movements. These data are converted into digital signals and temporarily stored in memory. The input is the animal's audio and movement data, and the output is a digital signal.

[0590] Step 2:

[0591] The device transmits the temporarily stored data to the server at regular intervals. The transmitted data includes the animal's voice data and movement data. The input is the digital signal in the memory, and the output is the data transmitted to the server.

[0592] Step 3:

[0593] The server temporarily stores the received data in local storage and periodically uploads it to cloud storage. This process ensures data availability and redundancy. The input is the transmitted data, and the output is the data stored in cloud storage.

[0594] Step 4:

[0595] The server retrieves the latest data from the cloud storage and the AI ​​model analyzes it. The AI ​​model analyzes the animal's voice and movement data to infer the animal's emotions and desires. The input is the cloud storage data and the output is the animal's emotional state.

[0596] Step 5:

[0597] The server generates text for voice chat based on the analysis results, and converts the text into speech using a speech synthesis system. The input is the emotional state of the animal, and the output is the generated voice chat.

[0598] Step 6:

[0599] The server sends the generated voice chat to the user's device, and the user receives the voice chat through a dedicated app. The input is the generated voice chat, and the output is the voice chat sent to the user's device.

[0600] Step 7:

[0601] If the server determines that the animal's emotion is hungry, it automatically orders food delivery. The input is the animal's emotional state, and the output is the food delivery order.

[0602] Step 8:

[0603] Users can understand their pet's condition through the voice chat they receive and take necessary measures promptly. Users can also share information with other users using the app's social networking function. The input is the user's emotional state and feedback, and the output is enhanced communication.

[0604] This allows you to properly manage your pet's condition remotely and take any necessary action quickly.

[0605] 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.

[0606] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0607] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0608] [Second embodiment]

[0609] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0610] 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.

[0611] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0612] 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.

[0613] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0614] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0615] 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.

[0616] 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.

[0617] 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 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.

[0618] 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.

[0619] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0620] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0621] The present invention provides a system for communicating with animals by generating voice chat using a microphone and a motion sensor attached to the animal. This system is composed of the following means.

[0622] Data collection and transmission methods

[0623] Device:

[0624] A microphone and motion sensor attached to the animal's collar collects vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into a digital signal in real time and temporarily stored in the device's memory. The device then transmits this data to a server at regular intervals.

[0625] Data analysis and voice chat generation methods

[0626] server:

[0627] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The AI ​​model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[0628] A means for providing voice chat to users

[0629] User:

[0630] Users launch a dedicated app on their device and connect to the server. The app downloads voice chat data from the server and provides voice chat to users. The voice chat data is played back using the device's speaker, allowing users to enjoy interacting with animals.

[0631] SNS function means

[0632] server:

[0633] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[0634] User:

[0635] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[0636] Specific examples

[0637] Example 1: Data collection and transmission

[0638] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then sends it to the server in a batch process.

[0639] Example 2: Voice chat generation

[0640] The server retrieves the collected data from cloud storage, and the AI ​​model analyzes that "the dog is excited." As a result of the analysis, it generates the text "I feel like playing," and the voice synthesis system creates a voice chat saying "Let's play!" The user plays the voice chat in the app and understands the dog's feelings.

[0641] Example 3: Social networking features

[0642] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments to communicate with each other.

[0643] The processing flow will be explained below.

[0644] Program processing flow

[0645] Data collection and transmission methods

[0646] Device:

[0647] Step 1:

[0648] Microphones and motion sensors capture animal sounds and movements in real time.

[0649] Step 2:

[0650] Convert the captured analog signal into a digital signal.

[0651] Step 3:

[0652] The converted digital signal is temporarily stored in the terminal's memory.

[0653] Step 4:

[0654] At regular intervals, the terminal processes a batch of digital data in its memory and sends it to the server.

[0655] Data analysis and voice chat generation methods

[0656] server:

[0657] Step 1:

[0658] The server receives the data sent from the terminal.

[0659] Step 2:

[0660] The received data is temporarily stored in local storage.

[0661] Step 3:

[0662] Periodically, the server uploads the temporarily stored data to cloud storage.

[0663] Step 4:

[0664] Get the latest data from cloud storage.

[0665] Step 5:

[0666] An AI model analyzes the collected data and infers the animal's emotions and desires.

[0667] Step 6:

[0668] Based on the analysis results, text for voice chat is generated.

[0669] Step 7:

[0670] The generated text is input into a speech synthesis system to generate a voice chat.

[0671] Step 8:

[0672] The generated voice chat is stored in the server, and preparations for providing it to the user are completed.

[0673] A means for providing voice chat to users

[0674] User:

[0675] Step 1:

[0676] The user launches the dedicated app.

[0677] Step 2:

[0678] The app will connect to the server and download the latest voice chat data.

[0679] Step 3:

[0680] The downloaded voice chat data is displayed within the app and a play button is provided.

[0681] Step 4:

[0682] When the user presses the play button, the app will play the voice chat using the device's speaker.

[0683] SNS function means

[0684] User:

[0685] Step 1:

[0686] A user creates a new post in the app and enters text and images.

[0687] Step 2:

[0688] When the user presses the post button, the post data is sent from the terminal to the server.

[0689] server:

[0690] Step 1:

[0691] The server receives the posted data sent by the user.

[0692] Step 2:

[0693] Save the received post data in the database.

[0694] Step 3:

[0695] Send push notifications to let other users know that you have posted something new.

[0696] User (other users):

[0697] Step 1:

[0698] Other users receive notifications of new posts.

[0699] Step 2:

[0700] Other users open the app and see your new posts.

[0701] Step 3:

[0702] Other users leave comments and start communicating with the poster.

[0703] Example 1

[0704] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0705] Currently, communication between humans and animals is primarily visual and tactile, making it difficult to accurately understand animals' emotions and desires. In particular, because animals cannot verbally express what they are feeling, owners often misunderstand their animals' condition. In addition, there are limited ways for owners with similar interests to share information, making it difficult to form a community.

[0706] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0707] In this invention, the server includes a means for acquiring data from a cloud storage device and analyzing the data using a generative AI model, a means for generating voice conversation data based on the analysis results, and a means for storing the voice conversation data generated using a voice synthesizer on the server. This makes it possible to accurately predict an animal's emotions and desires, verbalize them, and provide them to the owner. This also enables smooth information sharing and communication with other pet owners using the system.

[0708] An "audio collection device" is a device that collects animal sounds and converts them into digital signals.

[0709] A "motion detection device" is a device that detects animal movements and collects that data.

[0710] An "internal storage device" is a storage medium for temporarily storing collected data.

[0711] A "server" is a computer system that receives, stores, and processes data sent from a terminal.

[0712] "Cloud storage" is a remote storage medium for storing and managing data over the Internet.

[0713] A "generative AI model" is an artificial intelligence model that analyzes collected data and infers an animal's emotions and desires based on the results.

[0714] "Speech conversation data" is data obtained by converting text generated based on the analysis results into speech.

[0715] A "voice synthesizer" is a device for converting text data into voice data.

[0716] A "dedicated application" is software that a user uses to communicate with a server and to download and play back voice conversation data.

[0717] A "terminal device" is a device that a user uses to launch a dedicated application.

[0718] The "communication function" is a function for sharing information with other users and communicating with each other.

[0719] The present invention is a system that uses a voice collection device and a motion detection device attached to an animal to collect data, analyze the data, and infer the animal's emotions and desires. This system also includes a function to generate voice conversation data based on the analysis results and provide it to the user. It also includes a communication function to share information between users.

[0720] Data collection equipment

[0721] Device:

[0722] An audio collection device (microphone) and a motion detection device (motion sensor) collect animal sounds and movement data in real time and convert them into digital signals.

[0723] The converted digital data is temporarily stored in an internal storage device.

[0724] At regular intervals (for example, every 5 minutes), the collected data is sent to the server.

[0725] Server-side processing

[0726] server:

[0727] Receives data sent from the device and temporarily stores it in local storage.

[0728] The data is periodically uploaded to a cloud storage device.

[0729] Data is retrieved from cloud storage and voice and movement data is analyzed using a generative AI model.

[0730] Through analysis, the animal's emotions and desires are inferred, and text data for voice conversations is generated based on the results.

[0731] A voice synthesizer is used to convert text data into voice data, and the generated voice conversation data is stored on a server.

[0732] User-Facing Features

[0733] User:

[0734] A dedicated application is started on the terminal device and connected to the server.

[0735] By downloading voice conversation data from the server and playing it back through the speaker of the terminal device, the user can understand the emotions and desires of the animal.

[0736] Users can also share information and communicate with other pet owners through a dedicated application.

[0737] Specific examples

[0738] Examples of data collection and transmission:

[0739] When a dog barks, the sound collection device captures the sound, and the motion detection device captures the dog's running data. The data is converted into digital signals and sent to a server every five minutes.

[0740] Example of voice chat generation:

[0741] The server uses a generative AI model to analyze the data retrieved from cloud storage. As a result of the analysis, it is inferred that "the dog is excited" and the text "I want to play" is generated. The speech synthesizer then generates voice conversation data saying "Let's play!" and saves it on the server.

[0742] Examples of social media features:

[0743] User A posts "What happened on today's walk" through a dedicated application and sends it to the server. The server saves this post in a database and notifies other users. Other users view it and post comments such as "My dog ​​also met another dog for the first time on a walk!"

[0744] Prompt Sentence Examples

[0745] "Please analyze the audio data of the dog barking, infer what the dog is feeling, and generate a voice chat. At the same time, please include a function that allows other users to leave comments in response."

[0746] This system makes it possible to accurately understand the emotions and desires of animals, and also facilitates smooth communication between users.

[0747] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0748] Step 1:

[0749] Data collection and conversion (terminal)

[0750] A sound collection device (microphone) attached to the animal's collar picks up the animal's sounds, and a motion detection device (motion sensor) detects the animal's movements.

[0751] (Input): Animal sounds and movements

[0752] (Data processing): Converting collected data into digital signals

[0753] (Output): Digitally converted voice and motion data

[0754] Step 2:

[0755] Temporary data storage (device)

[0756] The terminal temporarily stores the converted digital signal in its internal memory.

[0757] (Input): Digitally encoded voice data and movement data

[0758] (Data storage): Save data to the internal storage device

[0759] (Output): Temporarily stored digital data

[0760] Step 3:

[0761] Data transmission (terminal)

[0762] The device sends the temporarily stored data to the server at regular intervals (e.g., every 5 minutes).

[0763] (Input): Temporarily stored digital data

[0764] (Data transmission): Sends data to the server at regular intervals

[0765] (Output): Data sent to the server

[0766] Step 4:

[0767] Receiving and temporarily storing data (server)

[0768] The server receives the voice data and motion data sent from the terminal and temporarily stores them in local storage.

[0769] (Input): Digital data sent from the terminal

[0770] (Data storage): Temporarily save data to local storage

[0771] (Output): Temporarily saved data

[0772] Step 5:

[0773] Upload to the cloud (server)

[0774] The server uploads the temporarily stored data to a storage device on the cloud at a fixed frequency.

[0775] (Input): Data temporarily saved in local storage

[0776] (Data transmission): Upload data to a cloud storage device

[0777] (Output): Data stored on the cloud

[0778] Step 6:

[0779] Data analysis (server)

[0780] The server retrieves the latest data from cloud storage and analyzes the audio and motion data using generative AI models.

[0781] (Input): Data retrieved from the cloud

[0782] (Data analysis): Analyzing animal emotions and desires using generative AI models

[0783] (Output): Analysis results (animal emotions and desires)

[0784] Step 7:

[0785] Voice chat generation (server)

[0786] Based on the analysis results, text data for voice conversation is generated.

[0787] A speech synthesizer is used to convert the text data into speech data.

[0788] (Input): Text data as analysis results

[0789] (Data generation): Generate voice conversation data

[0790] (Output): Generated voice conversation data

[0791] Step 8:

[0792] Save voice chat (server)

[0793] The generated voice conversation data is stored on the server.

[0794] (Input): Generated voice conversation data

[0795] (Data storage): Save data to the server

[0796] (Output): Saved voice conversation data

[0797] Step 9:

[0798] App launch and connection (user)

[0799] The user starts the dedicated application on the terminal device and connects to the server.

[0800] (Input): User application launch

[0801] (Action): Connect to the server

[0802] (Output): Server connection status

[0803] Step 10:

[0804] Download and play voice chat (user)

[0805] The user downloads voice conversation data from the server and plays it back through the speaker of the terminal device.

[0806] (Input): Voice conversation data stored on the server

[0807] (Data download and playback): Download and play data

[0808] (Output): The audio conversation the user hears

[0809] Step 11:

[0810] Use of SNS functions (users)

[0811] Users can share information and communicate with other pet owners through a dedicated application.

[0812] (Input): User post

[0813] (Information sharing and interaction): Sharing information and exchanging comments with other users

[0814] (Output): Submitted posts, comments, and feedback from other users

[0815] (Application example 1)

[0816] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0817] In order to enhance communication with animals, conventional methods have had difficulty in fully analyzing information obtained from sounds and movements and effectively providing it to users. Also, when enjoying interactions with animals in physical stores such as pet shops and animal cafes, there was a lack of means for visitors to understand the animals' emotions and desires in real time, making it difficult to communicate effectively.

[0818] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0819] In this invention, the server includes a means for collecting data from a microphone and a motion sensor attached to the animal, a means for transmitting the data to cloud storage, and a means for comparing the data with past accumulated data and analyzing the data using a generative AI model, thereby enabling users to experience interactions with animals in real time and provide generated voice chats.

[0820] A "microphone" is a device worn by an animal to collect audio data.

[0821] A "motion sensor" is a device for detecting and collecting animal movement data.

[0822] "Cloud storage" is a data storage system via the Internet that stores collected data and uses it for analysis.

[0823] A "generative AI model" is an algorithm that analyzes collected data and infers an animal's emotions and desires.

[0824] "Voice chat" refers to voice messages generated based on the analysis results for communication with users.

[0825] "SNS function" refers to a social networking service function that allows users to share information and communicate with other users.

[0826] A "user terminal" is a device that is installed in a physical store where animals are present, allowing users to experience interactions with the animals in real time.

[0827] "Real-time" is a concept that indicates that data is collected and processed instantaneously, providing results without delay.

[0828] "Audio data" is data that has been converted into digital form from sounds made by animals (such as cries).

[0829] "Movement data" is data that is detected when an animal moves (walking, jumping, standing still, etc.) and converted into digital format.

[0830] "Interaction" refers to the act or phenomenon in which the user and the animal influence each other.

[0831] The present invention is a system for generating voice chats using a microphone and motion sensor attached to an animal to enable communication with the animal, and this system is implemented as follows.

[0832] Data collection and transmission methods

[0833] Device:

[0834] A microphone and motion sensor attached to the animal's collar collects vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into a digital signal in real time and temporarily stored in the device's memory. The device then transmits this data to a server at regular intervals.

[0835] Data analysis and voice chat generation methods

[0836] server:

[0837] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The generative AI model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[0838] A means for providing voice chat to users

[0839] User:

[0840] Users launch a dedicated app on a device installed in the store and connect to the server. The app has the function of downloading voice chat data from the server and providing voice chat to users. The voice chat data is played back using the device's speaker, allowing users to enjoy interacting with the animals.

[0841] SNS function means

[0842] server:

[0843] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[0844] User:

[0845] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[0846] Specific examples

[0847] As a concrete example, a user visits a pet shop and tries to interact with a cat. The voice chat generated by this app plays back a voice saying, "This cat is relaxed." By inputting the following prompt sentences into the generative AI model, the voice chat generation becomes more efficient:

[0848] Prompt Sentence Examples

[0849] "Analyze the cat's meows to determine if it is relaxed, and generate a voice chat message that says, 'This cat is relaxed.'"

[0850] In this way, the system of the present invention can greatly improve communication with animals.

[0851] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0852] Step 1:

[0853] Data collection

[0854] Terminal: A microphone and motion sensor attached to the animal's collar collects animal sounds and movement data in real time.

[0855] Input: Animal sounds and movements.

[0856] Output: Audio and motion data converted into digital format.

[0857] Specific operation: The microphone collects voice data, and the motion sensor collects movement data and converts it into a digital signal.

[0858] Step 2:

[0859] Data transmission

[0860] Terminal: Collected digital data is temporarily stored in the terminal's memory and sent to the server at regular intervals.

[0861] Input: Audio and motion data in digital form.

[0862] Output: The data sent to the server.

[0863] Specific operation: The terminal sends data to the server at regular batch processing intervals.

[0864] Step 3:

[0865] Data reception and storage

[0866] Server: Receives data sent from the device, temporarily stores it in local storage, and periodically uploads it to cloud storage.

[0867] Input: Data sent from the device to the server.

[0868] Output: Data uploaded to cloud storage.

[0869] Specific operation: Save the data to local storage and then upload it to cloud storage.

[0870] Step 4:

[0871] Data analysis

[0872] Server: Based on the data retrieved from cloud storage, the generative AI model analyzes the data and infers the animal's emotions and desires.

[0873] Input: Data retrieved from cloud storage.

[0874] Output: Analysis results showing the animal's emotions and desires.

[0875] Specific behavior: The generative AI model analyzes audio and behavior data to infer the animal's emotions and desires.

[0876] Step 5:

[0877] Voice chat generation

[0878] Server: Generates text for voice chat based on the analysis results and converts the text into speech using a speech synthesis system.

[0879] Input: Analysis results indicating animal emotions and desires.

[0880] Output: The generated voice chat.

[0881] Specific operation: Based on the analysis results of the generative AI model, text is generated and voice chat is created using a speech synthesis system.

[0882] Step 6:

[0883] Voice chat playback

[0884] User: Launches a dedicated app on a device installed in a physical store, downloads voice chat data from the server, and plays it back.

[0885] Input: Voice chat data downloaded from the server.

[0886] Output: The audio chat that is played to the user.

[0887] Specific operation: The user plays the voice chat in real time through the device speaker.

[0888] Step 7:

[0889] Social networking features

[0890] User: Use the function to communicate with other users through a dedicated app.

[0891] Input: User submitted data and comment data.

[0892] Output: Updates that other users will be notified about.

[0893] What happens: Your post or comment is sent to the server and other users are notified.

[0894] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0895] The present invention is a system that uses a microphone and motion sensors attached to an animal to generate voice chat and communicate with the animal. This system also combines an emotion engine that recognizes the user's emotions to provide a more interactive experience. The present invention is composed of the following means.

[0896] Data collection and transmission methods

[0897] Device:

[0898] Microphones and motion sensors attached to the animal's collar collect vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into digital signals in real time and temporarily stored in the device's memory. The data is then batch-processed and sent to a server at regular intervals.

[0899] Data analysis and voice chat generation methods

[0900] server:

[0901] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The AI ​​model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[0902] A method for recognizing user emotions using an emotion engine

[0903] server:

[0904] The emotion engine recognizes emotions by analyzing the user's voice and facial expression data. For example, the emotion recognition algorithm analyzes the user's voice when speaking into the app and facial expression data captured by the camera to determine the user's emotional state.

[0905] A means for providing voice chat to users

[0906] User:

[0907] Users launch a dedicated app on their device and connect to the server. The app downloads voice chat data from the server and provides the user with voice chat. The voice chat data is played back using the device's speaker, allowing the user to enjoy interacting with the animals. Furthermore, the content of the generated voice chat is dynamically adjusted based on the user's emotions recognized by the emotion engine.

[0908] SNS function means

[0909] server:

[0910] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[0911] User:

[0912] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[0913] Specific examples

[0914] Example 1: Data collection and transmission

[0915] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then sends it to the server in a batch process.

[0916] Example 2: Voice chat generation

[0917] The server retrieves the collected data from cloud storage, and the AI ​​model analyzes that "the dog is excited." As a result of the analysis, it generates the text "I feel like playing," and the voice synthesis system creates a voice chat saying "Let's play!" The user plays the voice chat in the app and understands the dog's feelings.

[0918] Example 3: Dynamic voice chat with emotion engine

[0919] The emotion engine analyzes the user's voice and facial expression data and recognizes that the user is happy. When this happens, the server adds a message to the generated voice chat that matches the user's emotion, such as "Let's play together!" The user receives this message in the app, allowing for deeper interaction.

[0920] Example 4: SNS function

[0921] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments to communicate with each other.

[0922] The processing flow will be explained below.

[0923] Program processing flow

[0924] Data collection and transmission methods

[0925] Device:

[0926] Step 1:

[0927] Microphones and motion sensors capture animal sounds and movements in real time.

[0928] Step 2:

[0929] Convert the captured analog signal into a digital signal.

[0930] Step 3:

[0931] The converted digital signal is temporarily stored in the terminal's memory.

[0932] Step 4:

[0933] At regular intervals, the terminal processes a batch of digital data temporarily stored in memory and transmits it to the server.

[0934] Data analysis and voice chat generation methods

[0935] server:

[0936] Step 1:

[0937] The server receives the data sent from the terminal.

[0938] Step 2:

[0939] The received data is temporarily stored in local storage.

[0940] Step 3:

[0941] Periodically, the server uploads the temporarily stored data to cloud storage.

[0942] Step 4:

[0943] Get the latest data from cloud storage.

[0944] Step 5:

[0945] An AI model analyzes the collected data and infers the animal's emotions and desires.

[0946] Step 6:

[0947] Based on the analysis results, text for voice chat is generated.

[0948] Step 7:

[0949] The generated text is input into a speech synthesis system to generate a voice chat.

[0950] Step 8:

[0951] The generated voice chat is stored in the server, and preparations for providing it to the user are completed.

[0952] A method for recognizing user emotions using an emotion engine

[0953] server:

[0954] Step 1:

[0955] Collect user voice and facial expression data from input devices (microphones, cameras, etc.) for emotion recognition.

[0956] Step 2:

[0957] Emotion recognition algorithms analyze collected voice and facial expression data to determine the user's emotional state.

[0958] Step 3:

[0959] To dynamically adjust the content of a voice chat based on a user's emotional state.

[0960] A means for providing voice chat to users

[0961] User:

[0962] Step 1:

[0963] The user launches the dedicated app.

[0964] Step 2:

[0965] The app will connect to the server and download the latest voice chat data.

[0966] Step 3:

[0967] The downloaded voice chat data is displayed within the app and a play button is provided.

[0968] Step 4:

[0969] When the user presses the play button, the app will play the voice chat using the device's speaker.

[0970] SNS function means

[0971] User:

[0972] Step 1:

[0973] A user creates a new post in the app and enters text and images.

[0974] Step 2:

[0975] When the user presses the post button, the post data is sent from the terminal to the server.

[0976] server:

[0977] Step 1:

[0978] The server receives the posted data sent by the user.

[0979] Step 2:

[0980] Save the received post data in the database.

[0981] Step 3:

[0982] Send push notifications to let other users know that you have posted something new.

[0983] User (other users):

[0984] Step 1:

[0985] Other users receive notifications of new posts.

[0986] Step 2:

[0987] Other users open the app and see your new posts.

[0988] Step 3:

[0989] Other users leave comments and start communicating with the poster.

[0990] Specific examples

[0991] Example 1: Data collection and transmission

[0992] Step 1:

[0993] The device uses a microphone to capture audio data of the dog barking.

[0994] Step 2:

[0995] The captured audio data is converted into a digital signal in real time.

[0996] Step 3:

[0997] The converted digital signal is temporarily stored in the terminal's memory.

[0998] Step 4:

[0999] Send audio data to the server in batch processing.

[1000] Example 2: Voice chat generation

[1001] Step 1:

[1002] The server retrieves the collected data from the cloud storage.

[1003] Step 2:

[1004] The AI ​​model analyzes that the dog is in an excited state.

[1005] Step 3:

[1006] Based on the analysis results, the text "I feel like playing" is generated.

[1007] Step 4:

[1008] The generated text is converted into a voice chat message such as "Let's play!" using a speech synthesis system.

[1009] Step 5:

[1010] Users can understand their dog's feelings by playing back audio chats through the app.

[1011] Example 3: Dynamic voice chat with emotion engine

[1012] Step 1:

[1013] The server's emotion engine collects and analyzes the user's voice and facial expression data.

[1014] Step 2:

[1015] The emotion engine recognizes when the user is happy.

[1016] Step 3:

[1017] The server generates a voice chat that includes the additional message "Let's play together!"

[1018] Step 4:

[1019] The user receives this message in the app and enjoys deeper interaction.

[1020] Example 4: SNS function

[1021] Step 1:

[1022] User A posts "What happened on today's walk" on the app.

[1023] Step 2:

[1024] The posted data is sent to the server and stored in a database.

[1025] Step 3:

[1026] The server sends notifications of new posts to other users.

[1027] Step 4:

[1028] Other users receive notifications and view your posts.

[1029] Step 5:

[1030] Other users can post comments and communicate with each other.

[1031] Example 2

[1032] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1033] In modern times, communication between animals and humans is extremely important, but there is a lack of effective means to understand animal behavior and emotions. There are also technical challenges to properly infer animal emotions from their behavior and vocalizations, enabling more accurate and meaningful communication. Furthermore, there is a need for an effective way to share information about animals with other users.

[1034] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1035] In this invention, the server includes a means for collecting data from the voice input device and the motion detection device attached to the animal, a means for transmitting the data to storage on a communication network, and a means for comparing the data with previously stored data and analyzing it using artificial intelligence. This allows for accurate understanding of the animal's behavior and emotions in real time and for generating voice conversations directed at the user, enabling richer communication. Furthermore, by combining an information sharing function for sharing information with other users, a system is provided that allows for the widespread sharing of information and experiences about animals.

[1036] An "audio input device" is a device for collecting animal sounds, and includes a microphone and the like.

[1037] A "motion detection device" is a sensor for detecting animal movements, and includes an acceleration sensor, a gyro sensor, and the like.

[1038] "Data collection means" refers to a function that automatically collects animal sound and movement data.

[1039] "Storage on a communication network" refers to a data storage area that can be accessed via the Internet, etc., and includes cloud storage.

[1040] "Data transmission means" refers to a function for transmitting collected data to a remote system such as a server.

[1041] "Artificial intelligence analysis methods" refers to technologies that use algorithms and machine learning models to analyze collected data and infer animal behavior and emotions.

[1042] "Voice conversation generation means" refers to the function of generating text based on the analysis results and converting it into speech using speech synthesis technology.

[1043] "User provision means" refers to a function for providing the generated voice conversation to the user through a voice output device.

[1044] "Information sharing function" refers to the social networking service (SNS) function for sharing information between users.

[1045] "Past accumulated data" refers to data on animal sounds and movements that have been collected and stored to date, and is a data set that will be used for analysis.

[1046] The present invention is a system that uses a voice input device and a motion detection device attached to an animal to collect, analyze, and provide animal voice and motion data to users, with the aim of realizing interactive communication with animals.

[1047] Data collection methods

[1048] Device:

[1049] The audio input device (microphone) and motion detection devices (accelerometer, gyro sensor) attached to the animal's collar collect the animal's sounds and movement data in real time. This data is instantly converted into digital signals and temporarily stored in the device's memory.

[1050] Data transmission method

[1051] Device:

[1052] The collected data is batch processed at regular intervals and sent to storage (cloud storage) on the communication network. The TCP / IP protocol is used for communication to ensure secure data transfer.

[1053] Data storage method

[1054] server:

[1055] Receives data sent from the device and temporarily stores it in local storage. The received data is periodically uploaded to cloud storage and safely stored. For example, AWS S3 is used as cloud storage.

[1056] Data Analysis Methods

[1057] server:

[1058] The latest data is retrieved from cloud storage and analyzed using a generative AI model. The AI ​​uses voice recognition and motion analysis algorithms to infer the animal's emotions and desires. The analysis results are generated as text data to understand the animal's behavior and emotions.

[1059] A means of generating voice chat

[1060] server:

[1061] Based on the analysis results, a text for the voice conversation is generated, and the text is converted into speech using a speech synthesis system (e.g., speech synthesis software). The generated speech is stored in the server and later provided to the user.

[1062] Means of user emotion recognition

[1063] server:

[1064] The app uses an emotion engine to analyze the user's voice and facial expression data captured by the camera. It uses voice processing software and facial recognition algorithms to determine the user's emotions, allowing it to dynamically adjust the content of voice chats.

[1065] Means of providing voice chat

[1066] User:

[1067] Users launch the app and download the voice chat data from the server. The downloaded voice chat data is then played through the device's speaker, allowing users to enjoy interacting with the animals.

[1068] SNS function means

[1069] server:

[1070] It receives post data and comment data from users and stores them in a database. It also has the function of sending notifications to other users when there are new posts or comments.

[1071] User:

[1072] Users can communicate with other users through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[1073] Specific examples

[1074] Example 1: Data collection and transmission

[1075] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then transmits the data to a server in batch processing.

[1076] Example 2: Voice chat generation

[1077] The server retrieves the collected data from cloud storage, and the generative AI model analyzes it to determine that the dog is excited. As a result, it generates the text "I want to play," and the voice synthesis system creates a voice chat saying "Let's play!" The user can play the voice chat in the app and understand the dog's feelings.

[1078] Example 3: Dynamic voice chat with emotion engine

[1079] The emotion engine analyzes the user's voice and facial expression data and recognizes that the user is happy. When this happens, the server adds a message to the generated voice chat that matches the user's emotion, such as "Let's play together!" The user receives this message in the app, allowing for deeper interaction.

[1080] Example 4: SNS function

[1081] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments, thereby communicating with each other.

[1082] Prompt Sentence Examples

[1083] 1. "I want to improve the accuracy of an AI model that analyzes why a dog barks."

[1084] 2. "Please suggest ways to improve the emotion engine to accurately recognize whether a user is laughing or not."

[1085] 3. "What are the criteria for selecting an effective speech synthesis system?"

[1086] 4. "Please give us some ideas for new features to encourage social media communication with other dog lovers."

[1087] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1088] Step 1: Data collection

[1089] Device:

[1090] An audio input device (microphone) and motion detection devices (accelerometer, gyro sensor) attached to the animal's collar collect sounds and movement data.

[1091] Input: Animal sounds and movements

[1092] Data processing and calculation: Audio data is collected as an analog signal by a microphone and converted into a digital signal. Movement data is measured by an acceleration sensor and a gyro sensor and converted into digital movement data.

[1093] Output: Digitized voice and motion data

[1094] Step 2: Send data

[1095] Device:

[1096] The collected voice data and movement data are batch processed at regular intervals and sent to a server via a communication network.

[1097] Input: Digitized voice and motion data

[1098] Data processing and calculation: The data is batch processed (a certain amount of data is processed in a batch), and then sent to the server using a communication protocol (e.g. TCP / IP).

[1099] Output: Data sent to the server

[1100] Step 3: Save data

[1101] server:

[1102] Receives data sent from the device and temporarily stores it in local storage, then periodically uploads the received data to cloud storage.

[1103] Input: Data received from the terminal

[1104] Data processing and calculation: The received data is temporarily stored in local storage and then periodically uploaded to cloud storage (e.g., AWS S3).

[1105] Output: Data stored in cloud storage

[1106] Step 4: Data analysis

[1107] server:

[1108] The latest data is retrieved from cloud storage and analyzed using a generative AI model.

[1109] Input: Data retrieved from cloud storage

[1110] Data Processing and Computation: Using speech recognition and motion analysis algorithms to infer animal emotions and behaviors, a generative AI model analyzes the data and classifies the animal's emotional state.

[1111] Output: Text data as the analysis result (e.g., "The dog is excited")

[1112] Step 5: Create a voice chat

[1113] server:

[1114] Based on the analysis results, text for voice conversation is generated and converted into speech using a speech synthesis system.

[1115] Input: Text data as analysis results

[1116] Data processing and calculation: Text data is input into a speech synthesis system to generate natural-sounding voice chat (e.g., "Let's play!"). For speech synthesis, TTS (Text-To-Speech) technology is used, for example.

[1117] Output: Generated audio data

[1118] Step 6: Recognizing User Emotions

[1119] server:

[1120] The emotion engine analyzes the user's voice and facial expression data to determine their emotions.

[1121] Input: User's voice data and facial expression data

[1122] Data Processing and Computation: Using voice processing software and facial recognition algorithms to analyze the user's emotional state and classify the user's emotions.

[1123] Output: User's emotional state

[1124] Step 7: Provide voice chat

[1125] User:

[1126] Users launch a dedicated app and download voice chat data from the server. The app then plays the downloaded voice chat data.

[1127] Input: Generated audio data

[1128] Data processing and calculation: The app receives the audio data from the server and plays it through the speaker.

[1129] Output: Voice chat provided to the user

[1130] Step 8: Social Media Functionality

[1131] server:

[1132] It receives post data and comment data from users and stores them in a database. It also has the function of sending notifications to other users when there are new posts or comments.

[1133] Input: User posted data and comment data

[1134] Data processing and calculation: The received data is stored in a database. When there is a new post or comment, the notification function will notify other users.

[1135] Output: Notified post and comment information

[1136] User:

[1137] Users can use the app to communicate with other users, create and send posts and comments, and receive feedback from other users.

[1138] Input: Feedback from other users

[1139] Data processing and calculation: Read comments from other users and reply as necessary.

[1140] Output: Communication results with other users

[1141] (Application example 2)

[1142] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1143] When pet owners are away from home, there is a lack of means to properly recognize their pet's hunger state and respond promptly. Furthermore, there is a lack of means to enhance communication between pets and owners.

[1144] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the animal's emotions and automatically ordering food delivery if it determines that the animal is hungry, means for collecting data from a microphone and motion sensor attached to the animal, and means for comparing the data with past accumulated data and analyzing it using AI. This makes it possible to remotely and appropriately grasp the pet's hunger state and quickly provide food. It also enhances interactive communication with the user.

[1145] An "animal-worn microphone" is a device used to collect animal audio data.

[1146] A "motion sensor" is a sensor that detects and collects animal movement data.

[1147] "Means for sending data to cloud storage" refers to a system for sending collected data to cloud storage via the Internet.

[1148] "Means of analysis using AI" refers to a system that uses artificial intelligence to analyze collected data and infer the condition of animals.

[1149] The "means for generating voice chat" is a means for converting the animal's intentions into text based on the analysis results, and then converting the text into voice.

[1150] The "means for providing voice chat to users" is a system that provides the generated voice chat to the user's terminal.

[1151] "Means including SNS functions" are functions that allow users to share information and communicate with other users.

[1152] "Means for analyzing an animal's emotions and automatically ordering food delivery if it is determined to be hungry" is a system that analyzes an animal's emotional data and, if it is determined to be hungry, automatically uses a food delivery service to order food.

[1153] "Means of comparing with previously accumulated data" refers to a means of comparing and analyzing data collected in the past with newly collected data.

[1154] This invention uses microphones and motion sensors attached to the animals to collect audio and movement data. The collected data is sent to cloud storage and compared with previously stored data. An AI model then analyzes the data to infer the animal's emotional state.

[1155] If the emotional state of the pet is estimated to be hungry, the server automatically orders food delivery. Specifically, a pet-specific application is installed on the user's device, and voice chat is provided to the user through this application. Information can also be shared with other users via social networking functions.

[1156] The hardware requires a microphone and motion sensors attached to the animal's collar, while the software includes an emotion engine for AI analysis, a voice recognition system to convert voice data into text, and a motion sensor device to detect movement data. It also requires access to cloud storage and food delivery APIs.

[1157] The server performs the following processing based on the collected data.

[1158] 1. Data collection and transmission:

[1159] The microphone collects animal sound data, and the motion sensor detects animal movement data. This data is converted into digital signals in real time, temporarily stored, and then sent to cloud storage at regular intervals.

[1160] 2. Data analysis and voice chat generation:

[1161] The AI ​​model analyzes the data retrieved from cloud storage and infers the animal's emotional state. Based on the analysis results, it generates text for voice chat and converts the text into speech using a speech synthesis system. The generated voice chat is stored on a server.

[1162] 3. Automated food delivery ordering:

[1163] If the animal's emotion is determined to be hungry, the server automatically issues a food delivery order, sending the necessary information including the user ID and pet ID, and ordering food.

[1164] 4. Providing voice chat to users:

[1165] Users can receive voice chats through the app to understand their pet's condition, and the app also has a social networking function that allows users to share information with other users.

[1166] For example, if audio data of a dog barking is collected and it corresponds to a state of "hunger," AI analysis will determine that "food delivery should be ordered." When the user checks the app, they will receive a notification saying, "Your pet seems hungry. Food delivery has been ordered," along with feedback via voice chat.

[1167] An example of a prompt is as follows:

[1168] "The sound of a dog barking has been collected. This audio and behavioral data is analyzed to infer that the animal is hungry. Food delivery will be ordered within the next hour."

[1169] In this way, even when the owner is not present, the animal's condition can be properly managed remotely and any necessary measures can be taken promptly.

[1170] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1171] Step 1:

[1172] A microphone and motion sensor attached to the animal's collar collects audio and movement data in real time. The microphone captures the animal's sounds, and the motion sensor detects the animal's movements. These data are converted into digital signals and temporarily stored in memory. The input is the animal's audio and movement data, and the output is a digital signal.

[1173] Step 2:

[1174] The device transmits the temporarily stored data to the server at regular intervals. The transmitted data includes the animal's voice data and movement data. The input is the digital signal in the memory, and the output is the data transmitted to the server.

[1175] Step 3:

[1176] The server temporarily stores the received data in local storage and periodically uploads it to cloud storage. This process ensures data availability and redundancy. The input is the transmitted data, and the output is the data stored in cloud storage.

[1177] Step 4:

[1178] The server retrieves the latest data from the cloud storage and the AI ​​model analyzes it. The AI ​​model analyzes the animal's voice and movement data to infer the animal's emotions and desires. The input is the cloud storage data and the output is the animal's emotional state.

[1179] Step 5:

[1180] The server generates text for voice chat based on the analysis results, and converts the text into speech using a speech synthesis system. The input is the emotional state of the animal, and the output is the generated voice chat.

[1181] Step 6:

[1182] The server sends the generated voice chat to the user's device, and the user receives the voice chat through a dedicated app. The input is the generated voice chat, and the output is the voice chat sent to the user's device.

[1183] Step 7:

[1184] If the server determines that the animal's emotion is hungry, it automatically orders food delivery. The input is the animal's emotional state, and the output is the food delivery order.

[1185] Step 8:

[1186] Users can understand their pet's condition through the voice chat they receive and take necessary measures promptly. Users can also share information with other users using the app's social networking function. The input is the user's emotional state and feedback, and the output is enhanced communication.

[1187] This allows you to properly manage your pet's condition remotely and take any necessary action quickly.

[1188] 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.

[1189] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1190] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1191] [Third embodiment]

[1192] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1193] 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.

[1194] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[1195] 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.

[1196] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1197] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1198] 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.

[1199] 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.

[1200] 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 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.

[1201] 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.

[1202] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1203] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1204] The present invention provides a system for communicating with animals by generating voice chat using a microphone and a motion sensor attached to the animal. This system is composed of the following means.

[1205] Data collection and transmission methods

[1206] Device:

[1207] A microphone and motion sensor attached to the animal's collar collects vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into a digital signal in real time and temporarily stored in the device's memory. The device then transmits this data to a server at regular intervals.

[1208] Data analysis and voice chat generation methods

[1209] server:

[1210] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The AI ​​model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[1211] A means for providing voice chat to users

[1212] User:

[1213] Users launch a dedicated app on their device and connect to the server. The app downloads voice chat data from the server and provides voice chat to users. The voice chat data is played back using the device's speaker, allowing users to enjoy interacting with animals.

[1214] SNS function means

[1215] server:

[1216] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[1217] User:

[1218] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[1219] Specific examples

[1220] Example 1: Data collection and transmission

[1221] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then sends it to the server in a batch process.

[1222] Example 2: Voice chat generation

[1223] The server retrieves the collected data from cloud storage, and the AI ​​model analyzes that "the dog is excited." As a result of the analysis, it generates the text "I feel like playing," and the voice synthesis system creates a voice chat saying "Let's play!" The user plays the voice chat in the app and understands the dog's feelings.

[1224] Example 3: Social networking features

[1225] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments to communicate with each other.

[1226] The processing flow will be explained below.

[1227] Program processing flow

[1228] Data collection and transmission methods

[1229] Device:

[1230] Step 1:

[1231] Microphones and motion sensors capture animal sounds and movements in real time.

[1232] Step 2:

[1233] Convert the captured analog signal into a digital signal.

[1234] Step 3:

[1235] The converted digital signal is temporarily stored in the terminal's memory.

[1236] Step 4:

[1237] At regular intervals, the terminal processes a batch of digital data in its memory and sends it to the server.

[1238] Data analysis and voice chat generation methods

[1239] server:

[1240] Step 1:

[1241] The server receives the data sent from the terminal.

[1242] Step 2:

[1243] The received data is temporarily stored in local storage.

[1244] Step 3:

[1245] Periodically, the server uploads the temporarily stored data to cloud storage.

[1246] Step 4:

[1247] Get the latest data from cloud storage.

[1248] Step 5:

[1249] An AI model analyzes the collected data and infers the animal's emotions and desires.

[1250] Step 6:

[1251] Based on the analysis results, text for voice chat is generated.

[1252] Step 7:

[1253] The generated text is input into a speech synthesis system to generate a voice chat.

[1254] Step 8:

[1255] The generated voice chat is stored in the server, and preparations for providing it to the user are completed.

[1256] A means for providing voice chat to users

[1257] User:

[1258] Step 1:

[1259] The user launches the dedicated app.

[1260] Step 2:

[1261] The app will connect to the server and download the latest voice chat data.

[1262] Step 3:

[1263] The downloaded voice chat data is displayed within the app and a play button is provided.

[1264] Step 4:

[1265] When the user presses the play button, the app will play the voice chat using the device's speaker.

[1266] SNS function means

[1267] User:

[1268] Step 1:

[1269] A user creates a new post in the app and enters text and images.

[1270] Step 2:

[1271] When the user presses the post button, the post data is sent from the terminal to the server.

[1272] server:

[1273] Step 1:

[1274] The server receives the posted data sent by the user.

[1275] Step 2:

[1276] Save the received post data in the database.

[1277] Step 3:

[1278] Send push notifications to let other users know that you have posted something new.

[1279] User (other users):

[1280] Step 1:

[1281] Other users receive notifications of new posts.

[1282] Step 2:

[1283] Other users open the app and see your new posts.

[1284] Step 3:

[1285] Other users leave comments and start communicating with the poster.

[1286] Example 1

[1287] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1288] Currently, communication between humans and animals is primarily visual and tactile, making it difficult to accurately understand animals' emotions and desires. In particular, because animals cannot verbally express what they are feeling, owners often misunderstand their animals' condition. In addition, there are limited ways for owners with similar interests to share information, making it difficult to form a community.

[1289] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1290] In this invention, the server includes a means for acquiring data from a cloud storage device and analyzing the data using a generative AI model, a means for generating voice conversation data based on the analysis results, and a means for storing the voice conversation data generated using a voice synthesizer on the server. This makes it possible to accurately predict an animal's emotions and desires, verbalize them, and provide them to the owner. This also enables smooth information sharing and communication with other pet owners using the system.

[1291] An "audio collection device" is a device that collects animal sounds and converts them into digital signals.

[1292] A "motion detection device" is a device that detects animal movements and collects that data.

[1293] An "internal storage device" is a storage medium for temporarily storing collected data.

[1294] A "server" is a computer system that receives, stores, and processes data sent from a terminal.

[1295] "Cloud storage" is a remote storage medium for storing and managing data over the Internet.

[1296] A "generative AI model" is an artificial intelligence model that analyzes collected data and infers an animal's emotions and desires based on the results.

[1297] "Speech conversation data" is data obtained by converting text generated based on the analysis results into speech.

[1298] A "voice synthesizer" is a device for converting text data into voice data.

[1299] A "dedicated application" is software that a user uses to communicate with a server and to download and play back voice conversation data.

[1300] A "terminal device" is a device that a user uses to launch a dedicated application.

[1301] The "communication function" is a function for sharing information with other users and communicating with each other.

[1302] The present invention is a system that uses a voice collection device and a motion detection device attached to an animal to collect data, analyze the data, and infer the animal's emotions and desires. This system also includes a function to generate voice conversation data based on the analysis results and provide it to the user. It also includes a communication function to share information between users.

[1303] Data collection equipment

[1304] Device:

[1305] An audio collection device (microphone) and a motion detection device (motion sensor) collect animal sounds and movement data in real time and convert them into digital signals.

[1306] The converted digital data is temporarily stored in an internal storage device.

[1307] At regular intervals (for example, every 5 minutes), the collected data is sent to the server.

[1308] Server-side processing

[1309] server:

[1310] Receives data sent from the device and temporarily stores it in local storage.

[1311] The data is periodically uploaded to a cloud storage device.

[1312] Data is retrieved from cloud storage and voice and movement data is analyzed using a generative AI model.

[1313] Through analysis, the animal's emotions and desires are inferred, and text data for voice conversations is generated based on the results.

[1314] A voice synthesizer is used to convert text data into voice data, and the generated voice conversation data is stored on a server.

[1315] User-Facing Features

[1316] User:

[1317] A dedicated application is started on the terminal device and connected to the server.

[1318] By downloading voice conversation data from the server and playing it back through the speaker of the terminal device, the user can understand the emotions and desires of the animal.

[1319] Users can also share information and communicate with other pet owners through a dedicated application.

[1320] Specific examples

[1321] Examples of data collection and transmission:

[1322] When a dog barks, the sound collection device captures the sound, and the motion detection device captures the dog's running data. The data is converted into digital signals and sent to a server every five minutes.

[1323] Example of voice chat generation:

[1324] The server uses a generative AI model to analyze the data retrieved from cloud storage. As a result of the analysis, it is inferred that "the dog is excited" and the text "I want to play" is generated. The speech synthesizer then generates voice conversation data saying "Let's play!" and saves it on the server.

[1325] Examples of social media features:

[1326] User A posts "What happened on today's walk" through a dedicated application and sends it to the server. The server saves this post in a database and notifies other users. Other users view it and post comments such as "My dog ​​also met another dog for the first time on a walk!"

[1327] Prompt Sentence Examples

[1328] "Please analyze the audio data of the dog barking, infer what the dog is feeling, and generate a voice chat. At the same time, please include a function that allows other users to leave comments in response."

[1329] This system makes it possible to accurately understand the emotions and desires of animals, and also facilitates smooth communication between users.

[1330] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1331] Step 1:

[1332] Data collection and conversion (terminal)

[1333] A sound collection device (microphone) attached to the animal's collar picks up the animal's sounds, and a motion detection device (motion sensor) detects the animal's movements.

[1334] (Input): Animal sounds and movements

[1335] (Data processing): Converting collected data into digital signals

[1336] (Output): Digitally converted voice and motion data

[1337] Step 2:

[1338] Temporary data storage (device)

[1339] The terminal temporarily stores the converted digital signal in its internal memory.

[1340] (Input): Digitally encoded voice data and movement data

[1341] (Data storage): Save data to the internal storage device

[1342] (Output): Temporarily stored digital data

[1343] Step 3:

[1344] Data transmission (terminal)

[1345] The device sends the temporarily stored data to the server at regular intervals (e.g., every 5 minutes).

[1346] (Input): Temporarily stored digital data

[1347] (Data transmission): Sends data to the server at regular intervals

[1348] (Output): Data sent to the server

[1349] Step 4:

[1350] Receiving and temporarily storing data (server)

[1351] The server receives the voice data and motion data sent from the terminal and temporarily stores them in local storage.

[1352] (Input): Digital data sent from the terminal

[1353] (Data storage): Temporarily save data to local storage

[1354] (Output): Temporarily saved data

[1355] Step 5:

[1356] Upload to the cloud (server)

[1357] The server uploads the temporarily stored data to a storage device on the cloud at a fixed frequency.

[1358] (Input): Data temporarily saved in local storage

[1359] (Data transmission): Upload data to a cloud storage device

[1360] (Output): Data stored on the cloud

[1361] Step 6:

[1362] Data analysis (server)

[1363] The server retrieves the latest data from cloud storage and analyzes the audio and motion data using generative AI models.

[1364] (Input): Data retrieved from the cloud

[1365] (Data analysis): Analyzing animal emotions and desires using generative AI models

[1366] (Output): Analysis results (animal emotions and desires)

[1367] Step 7:

[1368] Voice chat generation (server)

[1369] Based on the analysis results, text data for voice conversation is generated.

[1370] A speech synthesizer is used to convert the text data into speech data.

[1371] (Input): Text data as analysis results

[1372] (Data generation): Generate voice conversation data

[1373] (Output): Generated voice conversation data

[1374] Step 8:

[1375] Save voice chat (server)

[1376] The generated voice conversation data is stored on the server.

[1377] (Input): Generated voice conversation data

[1378] (Data storage): Save data to the server

[1379] (Output): Saved voice conversation data

[1380] Step 9:

[1381] App launch and connection (user)

[1382] The user starts the dedicated application on the terminal device and connects to the server.

[1383] (Input): User application launch

[1384] (Action): Connect to the server

[1385] (Output): Server connection status

[1386] Step 10:

[1387] Download and play voice chat (user)

[1388] The user downloads voice conversation data from the server and plays it back through the speaker of the terminal device.

[1389] (Input): Voice conversation data stored on the server

[1390] (Data download and playback): Download and play data

[1391] (Output): The audio conversation the user hears

[1392] Step 11:

[1393] Use of SNS functions (users)

[1394] Users can share information and communicate with other pet owners through a dedicated application.

[1395] (Input): User post

[1396] (Information sharing and interaction): Sharing information and exchanging comments with other users

[1397] (Output): Submitted posts, comments, and feedback from other users

[1398] (Application example 1)

[1399] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1400] In order to enhance communication with animals, conventional methods have had difficulty in fully analyzing information obtained from sounds and movements and effectively providing it to users. Also, when enjoying interactions with animals in physical stores such as pet shops and animal cafes, there was a lack of means for visitors to understand the animals' emotions and desires in real time, making it difficult to communicate effectively.

[1401] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1402] In this invention, the server includes a means for collecting data from a microphone and a motion sensor attached to the animal, a means for transmitting the data to cloud storage, and a means for comparing the data with past accumulated data and analyzing the data using a generative AI model, thereby enabling users to experience interactions with animals in real time and provide generated voice chats.

[1403] A "microphone" is a device worn by an animal to collect audio data.

[1404] A "motion sensor" is a device for detecting and collecting animal movement data.

[1405] "Cloud storage" is a data storage system via the Internet that stores collected data and uses it for analysis.

[1406] A "generative AI model" is an algorithm that analyzes collected data and infers an animal's emotions and desires.

[1407] "Voice chat" refers to voice messages generated based on the analysis results for communication with users.

[1408] "SNS function" refers to a social networking service function that allows users to share information and communicate with other users.

[1409] A "user terminal" is a device that is installed in a physical store where animals are present, allowing users to experience interactions with the animals in real time.

[1410] "Real-time" is a concept that indicates that data is collected and processed instantaneously, providing results without delay.

[1411] "Audio data" is data that has been converted into digital form from sounds made by animals (such as cries).

[1412] "Movement data" is data that is detected when an animal moves (walking, jumping, standing still, etc.) and converted into digital format.

[1413] "Interaction" refers to the act or phenomenon in which the user and the animal influence each other.

[1414] The present invention is a system for generating voice chats using a microphone and motion sensor attached to an animal to enable communication with the animal, and this system is implemented as follows.

[1415] Data collection and transmission methods

[1416] Device:

[1417] A microphone and motion sensor attached to the animal's collar collects vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into a digital signal in real time and temporarily stored in the device's memory. The device then transmits this data to a server at regular intervals.

[1418] Data analysis and voice chat generation methods

[1419] server:

[1420] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The generative AI model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[1421] A means for providing voice chat to users

[1422] User:

[1423] Users launch a dedicated app on a device installed in the store and connect to the server. The app has the function of downloading voice chat data from the server and providing voice chat to users. The voice chat data is played back using the device's speaker, allowing users to enjoy interacting with the animals.

[1424] SNS function means

[1425] server:

[1426] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[1427] User:

[1428] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[1429] Specific examples

[1430] As a concrete example, a user visits a pet shop and tries to interact with a cat. The voice chat generated by this app plays back a voice saying, "This cat is relaxed." By inputting the following prompt sentences into the generative AI model, the voice chat generation becomes more efficient:

[1431] Prompt Sentence Examples

[1432] "Analyze the cat's meows to determine if it is relaxed, and generate a voice chat message that says, 'This cat is relaxed.'"

[1433] In this way, the system of the present invention can greatly improve communication with animals.

[1434] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1435] Step 1:

[1436] Data collection

[1437] Terminal: A microphone and motion sensor attached to the animal's collar collects animal sounds and movement data in real time.

[1438] Input: Animal sounds and movements.

[1439] Output: Audio and motion data converted into digital format.

[1440] Specific operation: The microphone collects voice data, and the motion sensor collects movement data and converts it into a digital signal.

[1441] Step 2:

[1442] Data transmission

[1443] Terminal: Collected digital data is temporarily stored in the terminal's memory and sent to the server at regular intervals.

[1444] Input: Audio and motion data in digital form.

[1445] Output: The data sent to the server.

[1446] Specific operation: The terminal sends data to the server at regular batch processing intervals.

[1447] Step 3:

[1448] Data reception and storage

[1449] Server: Receives data sent from the device, temporarily stores it in local storage, and periodically uploads it to cloud storage.

[1450] Input: Data sent from the device to the server.

[1451] Output: Data uploaded to cloud storage.

[1452] Specific operation: Save the data to local storage and then upload it to cloud storage.

[1453] Step 4:

[1454] Data analysis

[1455] Server: Based on the data retrieved from cloud storage, the generative AI model analyzes the data and infers the animal's emotions and desires.

[1456] Input: Data retrieved from cloud storage.

[1457] Output: Analysis results showing the animal's emotions and desires.

[1458] Specific behavior: The generative AI model analyzes audio and behavior data to infer the animal's emotions and desires.

[1459] Step 5:

[1460] Voice chat generation

[1461] Server: Generates text for voice chat based on the analysis results and converts the text into speech using a speech synthesis system.

[1462] Input: Analysis results indicating animal emotions and desires.

[1463] Output: The generated voice chat.

[1464] Specific operation: Based on the analysis results of the generative AI model, text is generated and voice chat is created using a speech synthesis system.

[1465] Step 6:

[1466] Voice chat playback

[1467] User: Launches a dedicated app on a device installed in a physical store, downloads voice chat data from the server, and plays it back.

[1468] Input: Voice chat data downloaded from the server.

[1469] Output: The audio chat that is played to the user.

[1470] Specific operation: The user plays the voice chat in real time through the device speaker.

[1471] Step 7:

[1472] Social networking features

[1473] User: Use the function to communicate with other users through a dedicated app.

[1474] Input: User submitted data and comment data.

[1475] Output: Updates that other users will be notified about.

[1476] What happens: Your post or comment is sent to the server and other users are notified.

[1477] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1478] The present invention is a system that uses a microphone and motion sensors attached to an animal to generate voice chat and communicate with the animal. This system also combines an emotion engine that recognizes the user's emotions to provide a more interactive experience. The present invention is composed of the following means.

[1479] Data collection and transmission methods

[1480] Device:

[1481] Microphones and motion sensors attached to the animal's collar collect vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into digital signals in real time and temporarily stored in the device's memory. The data is then batch-processed and sent to a server at regular intervals.

[1482] Data analysis and voice chat generation methods

[1483] server:

[1484] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The AI ​​model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[1485] A method for recognizing user emotions using an emotion engine

[1486] server:

[1487] The emotion engine recognizes emotions by analyzing the user's voice and facial expression data. For example, the emotion recognition algorithm analyzes the user's voice when speaking into the app and facial expression data captured by the camera to determine the user's emotional state.

[1488] A means for providing voice chat to users

[1489] User:

[1490] Users launch a dedicated app on their device and connect to the server. The app downloads voice chat data from the server and provides the user with voice chat. The voice chat data is played back using the device's speaker, allowing the user to enjoy interacting with the animals. Furthermore, the content of the generated voice chat is dynamically adjusted based on the user's emotions recognized by the emotion engine.

[1491] SNS function means

[1492] server:

[1493] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[1494] User:

[1495] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[1496] Specific examples

[1497] Example 1: Data collection and transmission

[1498] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then sends it to the server in a batch process.

[1499] Example 2: Voice chat generation

[1500] The server retrieves the collected data from cloud storage, and the AI ​​model analyzes that "the dog is excited." As a result of the analysis, it generates the text "I feel like playing," and the voice synthesis system creates a voice chat saying "Let's play!" The user plays the voice chat in the app and understands the dog's feelings.

[1501] Example 3: Dynamic voice chat with emotion engine

[1502] The emotion engine analyzes the user's voice and facial expression data and recognizes that the user is happy. When this happens, the server adds a message to the generated voice chat that matches the user's emotion, such as "Let's play together!" The user receives this message in the app, allowing for deeper interaction.

[1503] Example 4: SNS function

[1504] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments to communicate with each other.

[1505] The processing flow will be explained below.

[1506] Program processing flow

[1507] Data collection and transmission methods

[1508] Device:

[1509] Step 1:

[1510] Microphones and motion sensors capture animal sounds and movements in real time.

[1511] Step 2:

[1512] Convert the captured analog signal into a digital signal.

[1513] Step 3:

[1514] The converted digital signal is temporarily stored in the terminal's memory.

[1515] Step 4:

[1516] At regular intervals, the terminal processes a batch of digital data temporarily stored in memory and transmits it to the server.

[1517] Data analysis and voice chat generation methods

[1518] server:

[1519] Step 1:

[1520] The server receives the data sent from the terminal.

[1521] Step 2:

[1522] The received data is temporarily stored in local storage.

[1523] Step 3:

[1524] Periodically, the server uploads the temporarily stored data to cloud storage.

[1525] Step 4:

[1526] Get the latest data from cloud storage.

[1527] Step 5:

[1528] An AI model analyzes the collected data and infers the animal's emotions and desires.

[1529] Step 6:

[1530] Based on the analysis results, text for voice chat is generated.

[1531] Step 7:

[1532] The generated text is input into a speech synthesis system to generate a voice chat.

[1533] Step 8:

[1534] The generated voice chat is stored in the server, and preparations for providing it to the user are completed.

[1535] A method for recognizing user emotions using an emotion engine

[1536] server:

[1537] Step 1:

[1538] Collect user voice and facial expression data from input devices (microphones, cameras, etc.) for emotion recognition.

[1539] Step 2:

[1540] Emotion recognition algorithms analyze collected voice and facial expression data to determine the user's emotional state.

[1541] Step 3:

[1542] To dynamically adjust the content of a voice chat based on a user's emotional state.

[1543] A means for providing voice chat to users

[1544] User:

[1545] Step 1:

[1546] The user launches the dedicated app.

[1547] Step 2:

[1548] The app will connect to the server and download the latest voice chat data.

[1549] Step 3:

[1550] The downloaded voice chat data is displayed within the app and a play button is provided.

[1551] Step 4:

[1552] When the user presses the play button, the app will play the voice chat using the device's speaker.

[1553] SNS function means

[1554] User:

[1555] Step 1:

[1556] A user creates a new post in the app and enters text and images.

[1557] Step 2:

[1558] When the user presses the post button, the post data is sent from the terminal to the server.

[1559] server:

[1560] Step 1:

[1561] The server receives the posted data sent by the user.

[1562] Step 2:

[1563] Save the received post data in the database.

[1564] Step 3:

[1565] Send push notifications to let other users know that you have posted something new.

[1566] User (other users):

[1567] Step 1:

[1568] Other users receive notifications of new posts.

[1569] Step 2:

[1570] Other users open the app and see your new posts.

[1571] Step 3:

[1572] Other users leave comments and start communicating with the poster.

[1573] Specific examples

[1574] Example 1: Data collection and transmission

[1575] Step 1:

[1576] The device uses a microphone to capture audio data of the dog barking.

[1577] Step 2:

[1578] The captured audio data is converted into a digital signal in real time.

[1579] Step 3:

[1580] The converted digital signal is temporarily stored in the terminal's memory.

[1581] Step 4:

[1582] Send audio data to the server in batch processing.

[1583] Example 2: Voice chat generation

[1584] Step 1:

[1585] The server retrieves the collected data from the cloud storage.

[1586] Step 2:

[1587] The AI ​​model analyzes that the dog is in an excited state.

[1588] Step 3:

[1589] Based on the analysis results, the text "I feel like playing" is generated.

[1590] Step 4:

[1591] The generated text is converted into a voice chat message such as "Let's play!" using a speech synthesis system.

[1592] Step 5:

[1593] Users can understand their dog's feelings by playing back audio chats through the app.

[1594] Example 3: Dynamic voice chat with emotion engine

[1595] Step 1:

[1596] The server's emotion engine collects and analyzes the user's voice and facial expression data.

[1597] Step 2:

[1598] The emotion engine recognizes when the user is happy.

[1599] Step 3:

[1600] The server generates a voice chat that includes the additional message "Let's play together!"

[1601] Step 4:

[1602] The user receives this message in the app and enjoys deeper interaction.

[1603] Example 4: SNS function

[1604] Step 1:

[1605] User A posts "What happened on today's walk" on the app.

[1606] Step 2:

[1607] The posted data is sent to the server and stored in a database.

[1608] Step 3:

[1609] The server sends notifications of new posts to other users.

[1610] Step 4:

[1611] Other users receive notifications and view your posts.

[1612] Step 5:

[1613] Other users can post comments and communicate with each other.

[1614] Example 2

[1615] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1616] In modern times, communication between animals and humans is extremely important, but there is a lack of effective means to understand animal behavior and emotions. There are also technical challenges to properly infer animal emotions from their behavior and vocalizations, enabling more accurate and meaningful communication. Furthermore, there is a need for an effective way to share information about animals with other users.

[1617] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1618] In this invention, the server includes a means for collecting data from the voice input device and the motion detection device attached to the animal, a means for transmitting the data to storage on a communication network, and a means for comparing the data with previously stored data and analyzing it using artificial intelligence. This allows for accurate understanding of the animal's behavior and emotions in real time and for generating voice conversations directed at the user, enabling richer communication. Furthermore, by combining an information sharing function for sharing information with other users, a system is provided that allows for the widespread sharing of information and experiences about animals.

[1619] An "audio input device" is a device for collecting animal sounds, and includes a microphone and the like.

[1620] A "motion detection device" is a sensor for detecting animal movements, and includes an acceleration sensor, a gyro sensor, and the like.

[1621] "Data collection means" refers to a function that automatically collects animal sound and movement data.

[1622] "Storage on a communication network" refers to a data storage area that can be accessed via the Internet, etc., and includes cloud storage.

[1623] "Data transmission means" refers to a function for transmitting collected data to a remote system such as a server.

[1624] "Artificial intelligence analysis methods" refers to technologies that use algorithms and machine learning models to analyze collected data and infer animal behavior and emotions.

[1625] "Voice conversation generation means" refers to the function of generating text based on the analysis results and converting it into speech using speech synthesis technology.

[1626] "User provision means" refers to a function for providing the generated voice conversation to the user through a voice output device.

[1627] "Information sharing function" refers to the social networking service (SNS) function for sharing information between users.

[1628] "Past accumulated data" refers to data on animal sounds and movements that have been collected and stored to date, and is a data set that will be used for analysis.

[1629] The present invention is a system that uses a voice input device and a motion detection device attached to an animal to collect, analyze, and provide animal voice and motion data to users, with the aim of realizing interactive communication with animals.

[1630] Data collection methods

[1631] Device:

[1632] The audio input device (microphone) and motion detection devices (accelerometer, gyro sensor) attached to the animal's collar collect the animal's sounds and movement data in real time. This data is instantly converted into digital signals and temporarily stored in the device's memory.

[1633] Data transmission method

[1634] Device:

[1635] The collected data is batch processed at regular intervals and sent to storage (cloud storage) on the communication network. The TCP / IP protocol is used for communication to ensure secure data transfer.

[1636] Data storage method

[1637] server:

[1638] Receives data sent from the device and temporarily stores it in local storage. The received data is periodically uploaded to cloud storage and safely stored. For example, AWS S3 is used as cloud storage.

[1639] Data Analysis Methods

[1640] server:

[1641] The latest data is retrieved from cloud storage and analyzed using a generative AI model. The AI ​​uses voice recognition and motion analysis algorithms to infer the animal's emotions and desires. The analysis results are generated as text data to understand the animal's behavior and emotions.

[1642] A means of generating voice chat

[1643] server:

[1644] Based on the analysis results, a text for the voice conversation is generated, and the text is converted into speech using a speech synthesis system (e.g., speech synthesis software). The generated speech is stored in the server and later provided to the user.

[1645] Means of user emotion recognition

[1646] server:

[1647] The app uses an emotion engine to analyze the user's voice and facial expression data captured by the camera. It uses voice processing software and facial recognition algorithms to determine the user's emotions, allowing it to dynamically adjust the content of voice chats.

[1648] Means of providing voice chat

[1649] User:

[1650] Users launch the app and download the voice chat data from the server. The downloaded voice chat data is then played through the device's speaker, allowing users to enjoy interacting with the animals.

[1651] SNS function means

[1652] server:

[1653] It receives post data and comment data from users and stores them in a database. It also has the function of sending notifications to other users when there are new posts or comments.

[1654] User:

[1655] Users can communicate with other users through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[1656] Specific examples

[1657] Example 1: Data collection and transmission

[1658] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then transmits the data to a server in batch processing.

[1659] Example 2: Voice chat generation

[1660] The server retrieves the collected data from cloud storage, and the generative AI model analyzes it to determine that the dog is excited. As a result, it generates the text "I want to play," and the voice synthesis system creates a voice chat saying "Let's play!" The user can play the voice chat in the app and understand the dog's feelings.

[1661] Example 3: Dynamic voice chat with emotion engine

[1662] The emotion engine analyzes the user's voice and facial expression data and recognizes that the user is happy. When this happens, the server adds a message to the generated voice chat that matches the user's emotion, such as "Let's play together!" The user receives this message in the app, allowing for deeper interaction.

[1663] Example 4: SNS function

[1664] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments, thereby communicating with each other.

[1665] Prompt Sentence Examples

[1666] 1. "I want to improve the accuracy of an AI model that analyzes why a dog barks."

[1667] 2. "Please suggest ways to improve the emotion engine to accurately recognize whether a user is laughing or not."

[1668] 3. "What are the criteria for selecting an effective speech synthesis system?"

[1669] 4. "Please give us some ideas for new features to encourage social media communication with other dog lovers."

[1670] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1671] Step 1: Data collection

[1672] Device:

[1673] An audio input device (microphone) and motion detection devices (accelerometer, gyro sensor) attached to the animal's collar collect sounds and movement data.

[1674] Input: Animal sounds and movements

[1675] Data processing and calculation: Audio data is collected as an analog signal by a microphone and converted into a digital signal. Movement data is measured by an acceleration sensor and a gyro sensor and converted into digital movement data.

[1676] Output: Digitized voice and motion data

[1677] Step 2: Send data

[1678] Device:

[1679] The collected voice data and movement data are batch processed at regular intervals and sent to a server via a communication network.

[1680] Input: Digitized voice and motion data

[1681] Data processing and calculation: The data is batch processed (a certain amount of data is processed in a batch), and then sent to the server using a communication protocol (e.g. TCP / IP).

[1682] Output: Data sent to the server

[1683] Step 3: Save data

[1684] server:

[1685] Receives data sent from the device and temporarily stores it in local storage, then periodically uploads the received data to cloud storage.

[1686] Input: Data received from the terminal

[1687] Data processing and calculation: The received data is temporarily stored in local storage and then periodically uploaded to cloud storage (e.g., AWS S3).

[1688] Output: Data stored in cloud storage

[1689] Step 4: Data analysis

[1690] server:

[1691] The latest data is retrieved from cloud storage and analyzed using a generative AI model.

[1692] Input: Data retrieved from cloud storage

[1693] Data Processing and Computation: Using speech recognition and motion analysis algorithms to infer animal emotions and behaviors, a generative AI model analyzes the data and classifies the animal's emotional state.

[1694] Output: Text data as the analysis result (e.g., "The dog is excited")

[1695] Step 5: Create a voice chat

[1696] server:

[1697] Based on the analysis results, text for voice conversation is generated and converted into speech using a speech synthesis system.

[1698] Input: Text data as analysis results

[1699] Data processing and calculation: Text data is input into a speech synthesis system to generate natural-sounding voice chat (e.g., "Let's play!"). For speech synthesis, TTS (Text-To-Speech) technology is used, for example.

[1700] Output: Generated audio data

[1701] Step 6: Recognizing User Emotions

[1702] server:

[1703] The emotion engine analyzes the user's voice and facial expression data to determine their emotions.

[1704] Input: User's voice data and facial expression data

[1705] Data Processing and Computation: Using voice processing software and facial recognition algorithms to analyze the user's emotional state and classify the user's emotions.

[1706] Output: User's emotional state

[1707] Step 7: Provide voice chat

[1708] User:

[1709] Users launch a dedicated app and download voice chat data from the server. The app then plays the downloaded voice chat data.

[1710] Input: Generated audio data

[1711] Data processing and calculation: The app receives the audio data from the server and plays it through the speaker.

[1712] Output: Voice chat provided to the user

[1713] Step 8: Social Media Functionality

[1714] server:

[1715] It receives post data and comment data from users and stores them in a database. It also has the function of sending notifications to other users when there are new posts or comments.

[1716] Input: User posted data and comment data

[1717] Data processing and calculation: The received data is stored in a database. When there is a new post or comment, the notification function will notify other users.

[1718] Output: Notified post and comment information

[1719] User:

[1720] Users can use the app to communicate with other users, create and send posts and comments, and receive feedback from other users.

[1721] Input: Feedback from other users

[1722] Data processing and calculation: Read comments from other users and reply as necessary.

[1723] Output: Communication results with other users

[1724] (Application example 2)

[1725] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1726] When pet owners are away from home, there is a lack of means to properly recognize their pet's hunger state and respond promptly. Furthermore, there is a lack of means to enhance communication between pets and owners.

[1727] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the animal's emotions and automatically ordering food delivery if it determines that the animal is hungry, means for collecting data from a microphone and motion sensor attached to the animal, and means for comparing the data with past accumulated data and analyzing it using AI. This makes it possible to remotely and appropriately grasp the pet's hunger state and quickly provide food. It also enhances interactive communication with the user.

[1728] An "animal-worn microphone" is a device used to collect animal audio data.

[1729] A "motion sensor" is a sensor that detects and collects animal movement data.

[1730] "Means for sending data to cloud storage" refers to a system for sending collected data to cloud storage via the Internet.

[1731] "Means of analysis using AI" refers to a system that uses artificial intelligence to analyze collected data and infer the condition of animals.

[1732] The "means for generating voice chat" is a means for converting the animal's intentions into text based on the analysis results, and then converting the text into voice.

[1733] The "means for providing voice chat to users" is a system that provides the generated voice chat to the user's terminal.

[1734] "Means including SNS functions" are functions that allow users to share information and communicate with other users.

[1735] "Means for analyzing an animal's emotions and automatically ordering food delivery if it is determined to be hungry" is a system that analyzes an animal's emotional data and, if it is determined to be hungry, automatically uses a food delivery service to order food.

[1736] "Means of comparing with previously accumulated data" refers to a means of comparing and analyzing data collected in the past with newly collected data.

[1737] This invention uses microphones and motion sensors attached to the animals to collect audio and movement data. The collected data is sent to cloud storage and compared with previously stored data. An AI model then analyzes the data to infer the animal's emotional state.

[1738] If the emotional state of the pet is estimated to be hungry, the server automatically orders food delivery. Specifically, a pet-specific application is installed on the user's device, and voice chat is provided to the user through this application. Information can also be shared with other users via social networking functions.

[1739] The hardware requires a microphone and motion sensors attached to the animal's collar, while the software includes an emotion engine for AI analysis, a voice recognition system to convert voice data into text, and a motion sensor device to detect movement data. It also requires access to cloud storage and food delivery APIs.

[1740] The server performs the following processing based on the collected data.

[1741] 1. Data collection and transmission:

[1742] The microphone collects animal sound data, and the motion sensor detects animal movement data. This data is converted into digital signals in real time, temporarily stored, and then sent to cloud storage at regular intervals.

[1743] 2. Data analysis and voice chat generation:

[1744] The AI ​​model analyzes the data retrieved from cloud storage and infers the animal's emotional state. Based on the analysis results, it generates text for voice chat and converts the text into speech using a speech synthesis system. The generated voice chat is stored on a server.

[1745] 3. Automated food delivery ordering:

[1746] If the animal's emotion is determined to be hungry, the server automatically issues a food delivery order, sending the necessary information including the user ID and pet ID, and ordering food.

[1747] 4. Providing voice chat to users:

[1748] Users can receive voice chats through the app to understand their pet's condition, and the app also has a social networking function that allows users to share information with other users.

[1749] For example, if audio data of a dog barking is collected and it corresponds to a state of "hunger," AI analysis will determine that "food delivery should be ordered." When the user checks the app, they will receive a notification saying, "Your pet seems hungry. Food delivery has been ordered," along with feedback via voice chat.

[1750] An example of a prompt is as follows:

[1751] "The sound of a dog barking has been collected. This audio and behavioral data is analyzed to infer that the animal is hungry. Food delivery will be ordered within the next hour."

[1752] In this way, even when the owner is not present, the animal's condition can be properly managed remotely and any necessary measures can be taken promptly.

[1753] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1754] Step 1:

[1755] A microphone and motion sensor attached to the animal's collar collects audio and movement data in real time. The microphone captures the animal's sounds, and the motion sensor detects the animal's movements. These data are converted into digital signals and temporarily stored in memory. The input is the animal's audio and movement data, and the output is a digital signal.

[1756] Step 2:

[1757] The device transmits the temporarily stored data to the server at regular intervals. The transmitted data includes the animal's voice data and movement data. The input is the digital signal in the memory, and the output is the data transmitted to the server.

[1758] Step 3:

[1759] The server temporarily stores the received data in local storage and periodically uploads it to cloud storage. This process ensures data availability and redundancy. The input is the transmitted data, and the output is the data stored in cloud storage.

[1760] Step 4:

[1761] The server retrieves the latest data from the cloud storage and the AI ​​model analyzes it. The AI ​​model analyzes the animal's voice and movement data to infer the animal's emotions and desires. The input is the cloud storage data and the output is the animal's emotional state.

[1762] Step 5:

[1763] The server generates text for voice chat based on the analysis results, and converts the text into speech using a speech synthesis system. The input is the emotional state of the animal, and the output is the generated voice chat.

[1764] Step 6:

[1765] The server sends the generated voice chat to the user's device, and the user receives the voice chat through a dedicated app. The input is the generated voice chat, and the output is the voice chat sent to the user's device.

[1766] Step 7:

[1767] If the server determines that the animal's emotion is hungry, it automatically orders food delivery. The input is the animal's emotional state, and the output is the food delivery order.

[1768] Step 8:

[1769] Users can understand their pet's condition through the voice chat they receive and take necessary measures promptly. Users can also share information with other users using the app's social networking function. The input is the user's emotional state and feedback, and the output is enhanced communication.

[1770] This allows you to properly manage your pet's condition remotely and take any necessary action quickly.

[1771] 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.

[1772] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1773] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1774] [Fourth embodiment]

[1775] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1776] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1777] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[1778] 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.

[1779] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1780] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1781] 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.

[1782] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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.

[1783] 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.

[1784] 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 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.

[1785] 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.

[1786] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1787] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1788] The present invention provides a system for communicating with animals by generating voice chat using a microphone and a motion sensor attached to the animal. This system is composed of the following means.

[1789] Data collection and transmission methods

[1790] Device:

[1791] A microphone and motion sensor attached to the animal's collar collects vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into a digital signal in real time and temporarily stored in the device's memory. The device then transmits this data to a server at regular intervals.

[1792] Data analysis and voice chat generation methods

[1793] server:

[1794] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The AI ​​model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[1795] A means for providing voice chat to users

[1796] User:

[1797] Users launch a dedicated app on their device and connect to the server. The app downloads voice chat data from the server and provides voice chat to users. The voice chat data is played back using the device's speaker, allowing users to enjoy interacting with animals.

[1798] SNS function means

[1799] server:

[1800] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[1801] User:

[1802] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[1803] Specific examples

[1804] Example 1: Data collection and transmission

[1805] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then sends it to the server in a batch process.

[1806] Example 2: Voice chat generation

[1807] The server retrieves the collected data from cloud storage, and the AI ​​model analyzes that "the dog is excited." As a result of the analysis, it generates the text "I feel like playing," and the voice synthesis system creates a voice chat saying "Let's play!" The user plays the voice chat in the app and understands the dog's feelings.

[1808] Example 3: Social networking features

[1809] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments to communicate with each other.

[1810] The processing flow will be explained below.

[1811] Program processing flow

[1812] Data collection and transmission methods

[1813] Device:

[1814] Step 1:

[1815] Microphones and motion sensors capture animal sounds and movements in real time.

[1816] Step 2:

[1817] Convert the captured analog signal into a digital signal.

[1818] Step 3:

[1819] The converted digital signal is temporarily stored in the terminal's memory.

[1820] Step 4:

[1821] At regular intervals, the terminal processes a batch of digital data in its memory and sends it to the server.

[1822] Data analysis and voice chat generation methods

[1823] server:

[1824] Step 1:

[1825] The server receives the data sent from the terminal.

[1826] Step 2:

[1827] The received data is temporarily stored in local storage.

[1828] Step 3:

[1829] Periodically, the server uploads the temporarily stored data to cloud storage.

[1830] Step 4:

[1831] Get the latest data from cloud storage.

[1832] Step 5:

[1833] An AI model analyzes the collected data and infers the animal's emotions and desires.

[1834] Step 6:

[1835] Based on the analysis results, text for voice chat is generated.

[1836] Step 7:

[1837] The generated text is input into a speech synthesis system to generate a voice chat.

[1838] Step 8:

[1839] The generated voice chat is stored in the server, and preparations for providing it to the user are completed.

[1840] A means for providing voice chat to users

[1841] User:

[1842] Step 1:

[1843] The user launches the dedicated app.

[1844] Step 2:

[1845] The app will connect to the server and download the latest voice chat data.

[1846] Step 3:

[1847] The downloaded voice chat data is displayed within the app and a play button is provided.

[1848] Step 4:

[1849] When the user presses the play button, the app will play the voice chat using the device's speaker.

[1850] SNS function means

[1851] User:

[1852] Step 1:

[1853] A user creates a new post in the app and enters text and images.

[1854] Step 2:

[1855] When the user presses the post button, the post data is sent from the terminal to the server.

[1856] server:

[1857] Step 1:

[1858] The server receives the posted data sent by the user.

[1859] Step 2:

[1860] Save the received post data in the database.

[1861] Step 3:

[1862] Send push notifications to let other users know that you have posted something new.

[1863] User (other users):

[1864] Step 1:

[1865] Other users receive notifications of new posts.

[1866] Step 2:

[1867] Other users open the app and see your new posts.

[1868] Step 3:

[1869] Other users leave comments and start communicating with the poster.

[1870] Example 1

[1871] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1872] Currently, communication between humans and animals is primarily visual and tactile, making it difficult to accurately understand animals' emotions and desires. In particular, because animals cannot verbally express what they are feeling, owners often misunderstand their animals' condition. In addition, there are limited ways for owners with similar interests to share information, making it difficult to form a community.

[1873] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1874] In this invention, the server includes a means for acquiring data from a cloud storage device and analyzing the data using a generative AI model, a means for generating voice conversation data based on the analysis results, and a means for storing the voice conversation data generated using a voice synthesizer on the server. This makes it possible to accurately predict an animal's emotions and desires, verbalize them, and provide them to the owner. This also enables smooth information sharing and communication with other pet owners using the system.

[1875] An "audio collection device" is a device that collects animal sounds and converts them into digital signals.

[1876] A "motion detection device" is a device that detects animal movements and collects that data.

[1877] An "internal storage device" is a storage medium for temporarily storing collected data.

[1878] A "server" is a computer system that receives, stores, and processes data sent from a terminal.

[1879] "Cloud storage" is a remote storage medium for storing and managing data over the Internet.

[1880] A "generative AI model" is an artificial intelligence model that analyzes collected data and infers an animal's emotions and desires based on the results.

[1881] "Speech conversation data" is data obtained by converting text generated based on the analysis results into speech.

[1882] A "voice synthesizer" is a device for converting text data into voice data.

[1883] A "dedicated application" is software that a user uses to communicate with a server and to download and play back voice conversation data.

[1884] A "terminal device" is a device that a user uses to launch a dedicated application.

[1885] The "communication function" is a function for sharing information with other users and communicating with each other.

[1886] The present invention is a system that uses a voice collection device and a motion detection device attached to an animal to collect data, analyze the data, and infer the animal's emotions and desires. This system also includes a function to generate voice conversation data based on the analysis results and provide it to the user. It also includes a communication function to share information between users.

[1887] Data collection equipment

[1888] Device:

[1889] An audio collection device (microphone) and a motion detection device (motion sensor) collect animal sounds and movement data in real time and convert them into digital signals.

[1890] The converted digital data is temporarily stored in an internal storage device.

[1891] At regular intervals (for example, every 5 minutes), the collected data is sent to the server.

[1892] Server-side processing

[1893] server:

[1894] Receives data sent from the device and temporarily stores it in local storage.

[1895] The data is periodically uploaded to a cloud storage device.

[1896] Data is retrieved from cloud storage and voice and movement data is analyzed using a generative AI model.

[1897] Through analysis, the animal's emotions and desires are inferred, and text data for voice conversations is generated based on the results.

[1898] A voice synthesizer is used to convert text data into voice data, and the generated voice conversation data is stored on a server.

[1899] User-Facing Features

[1900] User:

[1901] A dedicated application is started on the terminal device and connected to the server.

[1902] By downloading voice conversation data from the server and playing it back through the speaker of the terminal device, the user can understand the emotions and desires of the animal.

[1903] Users can also share information and communicate with other pet owners through a dedicated application.

[1904] Specific examples

[1905] Examples of data collection and transmission:

[1906] When a dog barks, the sound collection device captures the sound, and the motion detection device captures the dog's running data. The data is converted into digital signals and sent to a server every five minutes.

[1907] Example of voice chat generation:

[1908] The server uses a generative AI model to analyze the data retrieved from cloud storage. As a result of the analysis, it is inferred that "the dog is excited" and the text "I want to play" is generated. The speech synthesizer then generates voice conversation data saying "Let's play!" and saves it on the server.

[1909] Examples of social media features:

[1910] User A posts "What happened on today's walk" through a dedicated application and sends it to the server. The server saves this post in a database and notifies other users. Other users view it and post comments such as "My dog ​​also met another dog for the first time on a walk!"

[1911] Prompt Sentence Examples

[1912] "Please analyze the audio data of the dog barking, infer what the dog is feeling, and generate a voice chat. At the same time, please include a function that allows other users to leave comments in response."

[1913] This system makes it possible to accurately understand the emotions and desires of animals, and also facilitates smooth communication between users.

[1914] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1915] Step 1:

[1916] Data collection and conversion (terminal)

[1917] A sound collection device (microphone) attached to the animal's collar picks up the animal's sounds, and a motion detection device (motion sensor) detects the animal's movements.

[1918] (Input): Animal sounds and movements

[1919] (Data processing): Converting collected data into digital signals

[1920] (Output): Digitally converted voice and motion data

[1921] Step 2:

[1922] Temporary data storage (device)

[1923] The terminal temporarily stores the converted digital signal in its internal memory.

[1924] (Input): Digitally encoded voice data and movement data

[1925] (Data storage): Save data to the internal storage device

[1926] (Output): Temporarily stored digital data

[1927] Step 3:

[1928] Data transmission (terminal)

[1929] The device sends the temporarily stored data to the server at regular intervals (e.g., every 5 minutes).

[1930] (Input): Temporarily stored digital data

[1931] (Data transmission): Sends data to the server at regular intervals

[1932] (Output): Data sent to the server

[1933] Step 4:

[1934] Receiving and temporarily storing data (server)

[1935] The server receives the voice data and motion data sent from the terminal and temporarily stores them in local storage.

[1936] (Input): Digital data sent from the terminal

[1937] (Data storage): Temporarily save data to local storage

[1938] (Output): Temporarily saved data

[1939] Step 5:

[1940] Upload to the cloud (server)

[1941] The server uploads the temporarily stored data to a storage device on the cloud at a fixed frequency.

[1942] (Input): Data temporarily saved in local storage

[1943] (Data transmission): Upload data to a cloud storage device

[1944] (Output): Data stored on the cloud

[1945] Step 6:

[1946] Data analysis (server)

[1947] The server retrieves the latest data from cloud storage and analyzes the audio and motion data using generative AI models.

[1948] (Input): Data retrieved from the cloud

[1949] (Data analysis): Analyzing animal emotions and desires using generative AI models

[1950] (Output): Analysis results (animal emotions and desires)

[1951] Step 7:

[1952] Voice chat generation (server)

[1953] Based on the analysis results, text data for voice conversation is generated.

[1954] A speech synthesizer is used to convert the text data into speech data.

[1955] (Input): Text data as analysis results

[1956] (Data generation): Generate voice conversation data

[1957] (Output): Generated voice conversation data

[1958] Step 8:

[1959] Save voice chat (server)

[1960] The generated voice conversation data is stored on the server.

[1961] (Input): Generated voice conversation data

[1962] (Data storage): Save data to the server

[1963] (Output): Saved voice conversation data

[1964] Step 9:

[1965] App launch and connection (user)

[1966] The user starts the dedicated application on the terminal device and connects to the server.

[1967] (Input): User application launch

[1968] (Action): Connect to the server

[1969] (Output): Server connection status

[1970] Step 10:

[1971] Download and play voice chat (user)

[1972] The user downloads voice conversation data from the server and plays it back through the speaker of the terminal device.

[1973] (Input): Voice conversation data stored on the server

[1974] (Data download and playback): Download and play data

[1975] (Output): The audio conversation the user hears

[1976] Step 11:

[1977] Use of SNS functions (users)

[1978] Users can share information and communicate with other pet owners through a dedicated application.

[1979] (Input): User post

[1980] (Information sharing and interaction): Sharing information and exchanging comments with other users

[1981] (Output): Submitted posts, comments, and feedback from other users

[1982] (Application example 1)

[1983] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1984] In order to enhance communication with animals, conventional methods have had difficulty in fully analyzing information obtained from sounds and movements and effectively providing it to users. Also, when enjoying interactions with animals in physical stores such as pet shops and animal cafes, there was a lack of means for visitors to understand the animals' emotions and desires in real time, making it difficult to communicate effectively.

[1985] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1986] In this invention, the server includes a means for collecting data from a microphone and a motion sensor attached to the animal, a means for transmitting the data to cloud storage, and a means for comparing the data with past accumulated data and analyzing the data using a generative AI model, thereby enabling users to experience interactions with animals in real time and provide generated voice chats.

[1987] A "microphone" is a device worn by an animal to collect audio data.

[1988] A "motion sensor" is a device for detecting and collecting animal movement data.

[1989] "Cloud storage" is a data storage system via the Internet that stores collected data and uses it for analysis.

[1990] A "generative AI model" is an algorithm that analyzes collected data and infers an animal's emotions and desires.

[1991] "Voice chat" refers to voice messages generated based on the analysis results for communication with users.

[1992] "SNS function" refers to a social networking service function that allows users to share information and communicate with other users.

[1993] A "user terminal" is a device that is installed in a physical store where animals are present, allowing users to experience interactions with the animals in real time.

[1994] "Real-time" is a concept that indicates that data is collected and processed instantaneously, providing results without delay.

[1995] "Audio data" is data that has been converted into digital form from sounds made by animals (such as cries).

[1996] "Movement data" is data that is detected when an animal moves (walking, jumping, standing still, etc.) and converted into digital format.

[1997] "Interaction" refers to the act or phenomenon in which the user and the animal influence each other.

[1998] The present invention is a system for generating voice chats using a microphone and motion sensor attached to an animal to enable communication with the animal, and this system is implemented as follows.

[1999] Data collection and transmission methods

[2000] Device:

[2001] A microphone and motion sensor attached to the animal's collar collects vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into a digital signal in real time and temporarily stored in the device's memory. The device then transmits this data to a server at regular intervals.

[2002] Data analysis and voice chat generation methods

[2003] server:

[2004] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The generative AI model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[2005] A means for providing voice chat to users

[2006] User:

[2007] Users launch a dedicated app on a device installed in the store and connect to the server. The app has the function of downloading voice chat data from the server and providing voice chat to users. The voice chat data is played back using the device's speaker, allowing users to enjoy interacting with the animals.

[2008] SNS function means

[2009] server:

[2010] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[2011] User:

[2012] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[2013] Specific examples

[2014] As a concrete example, a user visits a pet shop and tries to interact with a cat. The voice chat generated by this app plays back a voice saying, "This cat is relaxed." By inputting the following prompt sentences into the generative AI model, the voice chat generation becomes more efficient:

[2015] Prompt Sentence Examples

[2016] "Analyze the cat's meows to determine if it is relaxed, and generate a voice chat message that says, 'This cat is relaxed.'"

[2017] In this way, the system of the present invention can greatly improve communication with animals.

[2018] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2019] Step 1:

[2020] Data collection

[2021] Terminal: A microphone and motion sensor attached to the animal's collar collects animal sounds and movement data in real time.

[2022] Input: Animal sounds and movements.

[2023] Output: Audio and motion data converted into digital format.

[2024] Specific operation: The microphone collects voice data, and the motion sensor collects movement data and converts it into a digital signal.

[2025] Step 2:

[2026] Data transmission

[2027] Terminal: Collected digital data is temporarily stored in the terminal's memory and sent to the server at regular intervals.

[2028] Input: Audio and motion data in digital form.

[2029] Output: The data sent to the server.

[2030] Specific operation: The terminal sends data to the server at regular batch processing intervals.

[2031] Step 3:

[2032] Data reception and storage

[2033] Server: Receives data sent from the device, temporarily stores it in local storage, and periodically uploads it to cloud storage.

[2034] Input: Data sent from the device to the server.

[2035] Output: Data uploaded to cloud storage.

[2036] Specific operation: Save the data to local storage and then upload it to cloud storage.

[2037] Step 4:

[2038] Data analysis

[2039] Server: Based on the data retrieved from cloud storage, the generative AI model analyzes the data and infers the animal's emotions and desires.

[2040] Input: Data retrieved from cloud storage.

[2041] Output: Analysis results showing the animal's emotions and desires.

[2042] Specific behavior: The generative AI model analyzes audio and behavior data to infer the animal's emotions and desires.

[2043] Step 5:

[2044] Voice chat generation

[2045] Server: Generates text for voice chat based on the analysis results and converts the text into speech using a speech synthesis system.

[2046] Input: Analysis results indicating animal emotions and desires.

[2047] Output: The generated voice chat.

[2048] Specific operation: Based on the analysis results of the generative AI model, text is generated and voice chat is created using a speech synthesis system.

[2049] Step 6:

[2050] Voice chat playback

[2051] User: Launches a dedicated app on a device installed in a physical store, downloads voice chat data from the server, and plays it back.

[2052] Input: Voice chat data downloaded from the server.

[2053] Output: The audio chat that is played to the user.

[2054] Specific operation: The user plays the voice chat in real time through the device speaker.

[2055] Step 7:

[2056] Social networking features

[2057] User: Use the function to communicate with other users through a dedicated app.

[2058] Input: User submitted data and comment data.

[2059] Output: Updates that other users will be notified about.

[2060] What happens: Your post or comment is sent to the server and other users are notified.

[2061] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2062] The present invention is a system that uses a microphone and motion sensors attached to an animal to generate voice chat and communicate with the animal. This system also combines an emotion engine that recognizes the user's emotions to provide a more interactive experience. The present invention is composed of the following means.

[2063] Data collection and transmission methods

[2064] Device:

[2065] Microphones and motion sensors attached to the animal's collar collect vocalizations and movement data. The microphone picks up sound, and the motion sensor detects movement. This data is converted into digital signals in real time and temporarily stored in the device's memory. The data is then batch-processed and sent to a server at regular intervals.

[2066] Data analysis and voice chat generation methods

[2067] server:

[2068] The server receives data sent from the device and temporarily stores it in local storage. This data is periodically uploaded to cloud storage. The AI ​​model analyzes the latest data retrieved from cloud storage. The AI ​​uses the voice and movement data to infer the animal's emotions and desires, and generates text for voice chat based on the analysis results. The text is then converted into speech using a speech synthesis system, and the generated voice chat is stored on the server.

[2069] A method for recognizing user emotions using an emotion engine

[2070] server:

[2071] The emotion engine recognizes emotions by analyzing the user's voice and facial expression data. For example, the emotion recognition algorithm analyzes the user's voice when speaking into the app and facial expression data captured by the camera to determine the user's emotional state.

[2072] A means for providing voice chat to users

[2073] User:

[2074] Users launch a dedicated app on their device and connect to the server. The app downloads voice chat data from the server and provides the user with voice chat. The voice chat data is played back using the device's speaker, allowing the user to enjoy interacting with the animals. Furthermore, the content of the generated voice chat is dynamically adjusted based on the user's emotions recognized by the emotion engine.

[2075] SNS function means

[2076] server:

[2077] The server receives user posted data and comment data and stores it in a database. When there are new posts or comments, it notifies other users of the updated information.

[2078] User:

[2079] Users can communicate with other dog lovers through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[2080] Specific examples

[2081] Example 1: Data collection and transmission

[2082] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then sends it to the server in a batch process.

[2083] Example 2: Voice chat generation

[2084] The server retrieves the collected data from cloud storage, and the AI ​​model analyzes that "the dog is excited." As a result of the analysis, it generates the text "I feel like playing," and the voice synthesis system creates a voice chat saying "Let's play!" The user plays the voice chat in the app and understands the dog's feelings.

[2085] Example 3: Dynamic voice chat with emotion engine

[2086] The emotion engine analyzes the user's voice and facial expression data and recognizes that the user is happy. When this happens, the server adds a message to the generated voice chat that matches the user's emotion, such as "Let's play together!" The user receives this message in the app, allowing for deeper interaction.

[2087] Example 4: SNS function

[2088] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments to communicate with each other.

[2089] The processing flow will be explained below.

[2090] Program processing flow

[2091] Data collection and transmission methods

[2092] Device:

[2093] Step 1:

[2094] Microphones and motion sensors capture animal sounds and movements in real time.

[2095] Step 2:

[2096] Convert the captured analog signal into a digital signal.

[2097] Step 3:

[2098] The converted digital signal is temporarily stored in the terminal's memory.

[2099] Step 4:

[2100] At regular intervals, the terminal processes a batch of digital data temporarily stored in memory and transmits it to the server.

[2101] Data analysis and voice chat generation methods

[2102] server:

[2103] Step 1:

[2104] The server receives the data sent from the terminal.

[2105] Step 2:

[2106] The received data is temporarily stored in local storage.

[2107] Step 3:

[2108] Periodically, the server uploads the temporarily stored data to cloud storage.

[2109] Step 4:

[2110] Get the latest data from cloud storage.

[2111] Step 5:

[2112] An AI model analyzes the collected data and infers the animal's emotions and desires.

[2113] Step 6:

[2114] Based on the analysis results, text for voice chat is generated.

[2115] Step 7:

[2116] The generated text is input into a speech synthesis system to generate a voice chat.

[2117] Step 8:

[2118] The generated voice chat is stored in the server, and preparations for providing it to the user are completed.

[2119] A method for recognizing user emotions using an emotion engine

[2120] server:

[2121] Step 1:

[2122] Collect user voice and facial expression data from input devices (microphones, cameras, etc.) for emotion recognition.

[2123] Step 2:

[2124] Emotion recognition algorithms analyze collected voice and facial expression data to determine the user's emotional state.

[2125] Step 3:

[2126] To dynamically adjust the content of a voice chat based on a user's emotional state.

[2127] A means for providing voice chat to users

[2128] User:

[2129] Step 1:

[2130] The user launches the dedicated app.

[2131] Step 2:

[2132] The app will connect to the server and download the latest voice chat data.

[2133] Step 3:

[2134] The downloaded voice chat data is displayed within the app and a play button is provided.

[2135] Step 4:

[2136] When the user presses the play button, the app will play the voice chat using the device's speaker.

[2137] SNS function means

[2138] User:

[2139] Step 1:

[2140] A user creates a new post in the app and enters text and images.

[2141] Step 2:

[2142] When the user presses the post button, the post data is sent from the terminal to the server.

[2143] server:

[2144] Step 1:

[2145] The server receives the posted data sent by the user.

[2146] Step 2:

[2147] Save the received post data in the database.

[2148] Step 3:

[2149] Send push notifications to let other users know that you have posted something new.

[2150] User (other users):

[2151] Step 1:

[2152] Other users receive notifications of new posts.

[2153] Step 2:

[2154] Other users open the app and see your new posts.

[2155] Step 3:

[2156] Other users leave comments and start communicating with the poster.

[2157] Specific examples

[2158] Example 1: Data collection and transmission

[2159] Step 1:

[2160] The device uses a microphone to capture audio data of the dog barking.

[2161] Step 2:

[2162] The captured audio data is converted into a digital signal in real time.

[2163] Step 3:

[2164] The converted digital signal is temporarily stored in the terminal's memory.

[2165] Step 4:

[2166] Send audio data to the server in batch processing.

[2167] Example 2: Voice chat generation

[2168] Step 1:

[2169] The server retrieves the collected data from the cloud storage.

[2170] Step 2:

[2171] The AI ​​model analyzes that the dog is in an excited state.

[2172] Step 3:

[2173] Based on the analysis results, the text "I feel like playing" is generated.

[2174] Step 4:

[2175] The generated text is converted into a voice chat message such as "Let's play!" using a speech synthesis system.

[2176] Step 5:

[2177] Users can understand their dog's feelings by playing back audio chats through the app.

[2178] Example 3: Dynamic voice chat with emotion engine

[2179] Step 1:

[2180] The server's emotion engine collects and analyzes the user's voice and facial expression data.

[2181] Step 2:

[2182] The emotion engine recognizes when the user is happy.

[2183] Step 3:

[2184] The server generates a voice chat that includes the additional message "Let's play together!"

[2185] Step 4:

[2186] The user receives this message in the app and enjoys deeper interaction.

[2187] Example 4: SNS function

[2188] Step 1:

[2189] User A posts "What happened on today's walk" on the app.

[2190] Step 2:

[2191] The posted data is sent to the server and stored in a database.

[2192] Step 3:

[2193] The server sends notifications of new posts to other users.

[2194] Step 4:

[2195] Other users receive notifications and view your posts.

[2196] Step 5:

[2197] Other users can post comments and communicate with each other.

[2198] Example 2

[2199] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2200] In modern times, communication between animals and humans is extremely important, but there is a lack of effective means to understand animal behavior and emotions. There are also technical challenges to properly infer animal emotions from their behavior and vocalizations, enabling more accurate and meaningful communication. Furthermore, there is a need for an effective way to share information about animals with other users.

[2201] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2202] In this invention, the server includes a means for collecting data from the voice input device and the motion detection device attached to the animal, a means for transmitting the data to storage on a communication network, and a means for comparing the data with previously stored data and analyzing it using artificial intelligence. This allows for accurate understanding of the animal's behavior and emotions in real time and for generating voice conversations directed at the user, enabling richer communication. Furthermore, by combining an information sharing function for sharing information with other users, a system is provided that allows for the widespread sharing of information and experiences about animals.

[2203] An "audio input device" is a device for collecting animal sounds, and includes a microphone and the like.

[2204] A "motion detection device" is a sensor for detecting animal movements, and includes an acceleration sensor, a gyro sensor, and the like.

[2205] "Data collection means" refers to a function that automatically collects animal sound and movement data.

[2206] "Storage on a communication network" refers to a data storage area that can be accessed via the Internet, etc., and includes cloud storage.

[2207] "Data transmission means" refers to a function for transmitting collected data to a remote system such as a server.

[2208] "Artificial intelligence analysis methods" refers to technologies that use algorithms and machine learning models to analyze collected data and infer animal behavior and emotions.

[2209] "Voice conversation generation means" refers to the function of generating text based on the analysis results and converting it into speech using speech synthesis technology.

[2210] "User provision means" refers to a function for providing the generated voice conversation to the user through a voice output device.

[2211] "Information sharing function" refers to the social networking service (SNS) function for sharing information between users.

[2212] "Past accumulated data" refers to data on animal sounds and movements that have been collected and stored to date, and is a data set that will be used for analysis.

[2213] The present invention is a system that uses a voice input device and a motion detection device attached to an animal to collect, analyze, and provide animal voice and motion data to users, with the aim of realizing interactive communication with animals.

[2214] Data collection methods

[2215] Device:

[2216] The audio input device (microphone) and motion detection devices (accelerometer, gyro sensor) attached to the animal's collar collect the animal's sounds and movement data in real time. This data is instantly converted into digital signals and temporarily stored in the device's memory.

[2217] Data transmission method

[2218] Device:

[2219] The collected data is batch processed at regular intervals and sent to storage (cloud storage) on the communication network. The TCP / IP protocol is used for communication to ensure secure data transfer.

[2220] Data storage method

[2221] server:

[2222] Receives data sent from the device and temporarily stores it in local storage. The received data is periodically uploaded to cloud storage and safely stored. For example, AWS S3 is used as cloud storage.

[2223] Data Analysis Methods

[2224] server:

[2225] The latest data is retrieved from cloud storage and analyzed using a generative AI model. The AI ​​uses voice recognition and motion analysis algorithms to infer the animal's emotions and desires. The analysis results are generated as text data to understand the animal's behavior and emotions.

[2226] A means of generating voice chat

[2227] server:

[2228] Based on the analysis results, a text for the voice conversation is generated, and the text is converted into speech using a speech synthesis system (e.g., speech synthesis software). The generated speech is stored in the server and later provided to the user.

[2229] Means of user emotion recognition

[2230] server:

[2231] The app uses an emotion engine to analyze the user's voice and facial expression data captured by the camera. It uses voice processing software and facial recognition algorithms to determine the user's emotions, allowing it to dynamically adjust the content of voice chats.

[2232] Means of providing voice chat

[2233] User:

[2234] Users launch the app and download the voice chat data from the server. The downloaded voice chat data is then played through the device's speaker, allowing users to enjoy interacting with the animals.

[2235] SNS function means

[2236] server:

[2237] It receives post data and comment data from users and stores them in a database. It also has the function of sending notifications to other users when there are new posts or comments.

[2238] User:

[2239] Users can communicate with other users through a dedicated app, create posts and comments, send them to the server, and receive feedback from other users.

[2240] Specific examples

[2241] Example 1: Data collection and transmission

[2242] The device captures the sound of the dog barking with a microphone, converts it into a digital signal in real time, stores it temporarily in memory, and then transmits the data to a server in batch processing.

[2243] Example 2: Voice chat generation

[2244] The server retrieves the collected data from cloud storage, and the generative AI model analyzes it to determine that the dog is excited. As a result, it generates the text "I want to play," and the voice synthesis system creates a voice chat saying "Let's play!" The user can play the voice chat in the app and understand the dog's feelings.

[2245] Example 3: Dynamic voice chat with emotion engine

[2246] The emotion engine analyzes the user's voice and facial expression data and recognizes that the user is happy. When this happens, the server adds a message to the generated voice chat that matches the user's emotion, such as "Let's play together!" The user receives this message in the app, allowing for deeper interaction.

[2247] Example 4: SNS function

[2248] User A posts "Today's Walking Events" on the app and sends it to the server. The server stores it in a database and sends notifications to other users. Other users can view it and post comments, thereby communicating with each other.

[2249] Prompt Sentence Examples

[2250] 1. "I want to improve the accuracy of an AI model that analyzes why a dog barks."

[2251] 2. "Please suggest ways to improve the emotion engine to accurately recognize whether a user is laughing or not."

[2252] 3. "What are the criteria for selecting an effective speech synthesis system?"

[2253] 4. "Please give us some ideas for new features to encourage social media communication with other dog lovers."

[2254] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2255] Step 1: Data collection

[2256] Device:

[2257] An audio input device (microphone) and motion detection devices (accelerometer, gyro sensor) attached to the animal's collar collect sounds and movement data.

[2258] Input: Animal sounds and movements

[2259] Data processing and calculation: Audio data is collected as an analog signal by a microphone and converted into a digital signal. Movement data is measured by an acceleration sensor and a gyro sensor and converted into digital movement data.

[2260] Output: Digitized voice and motion data

[2261] Step 2: Send data

[2262] Device:

[2263] The collected voice data and movement data are batch processed at regular intervals and sent to a server via a communication network.

[2264] Input: Digitized voice and motion data

[2265] Data processing and calculation: The data is batch processed (a certain amount of data is processed in a batch), and then sent to the server using a communication protocol (e.g. TCP / IP).

[2266] Output: Data sent to the server

[2267] Step 3: Save data

[2268] server:

[2269] Receives data sent from the device and temporarily stores it in local storage, then periodically uploads the received data to cloud storage.

[2270] Input: Data received from the terminal

[2271] Data processing and calculation: The received data is temporarily stored in local storage and then periodically uploaded to cloud storage (e.g., AWS S3).

[2272] Output: Data stored in cloud storage

[2273] Step 4: Data analysis

[2274] server:

[2275] The latest data is retrieved from cloud storage and analyzed using a generative AI model.

[2276] Input: Data retrieved from cloud storage

[2277] Data Processing and Computation: Using speech recognition and motion analysis algorithms to infer animal emotions and behaviors, a generative AI model analyzes the data and classifies the animal's emotional state.

[2278] Output: Text data as the analysis result (e.g., "The dog is excited")

[2279] Step 5: Create a voice chat

[2280] server:

[2281] Based on the analysis results, text for voice conversation is generated and converted into speech using a speech synthesis system.

[2282] Input: Text data as analysis results

[2283] Data processing and calculation: Text data is input into a speech synthesis system to generate natural-sounding voice chat (e.g., "Let's play!"). For speech synthesis, TTS (Text-To-Speech) technology is used, for example.

[2284] Output: Generated audio data

[2285] Step 6: Recognizing User Emotions

[2286] server:

[2287] The emotion engine analyzes the user's voice and facial expression data to determine their emotions.

[2288] Input: User's voice data and facial expression data

[2289] Data Processing and Computation: Using voice processing software and facial recognition algorithms to analyze the user's emotional state and classify the user's emotions.

[2290] Output: User's emotional state

[2291] Step 7: Provide voice chat

[2292] User:

[2293] Users launch a dedicated app and download voice chat data from the server. The app then plays the downloaded voice chat data.

[2294] Input: Generated audio data

[2295] Data processing and calculation: The app receives the audio data from the server and plays it through the speaker.

[2296] Output: Voice chat provided to the user

[2297] Step 8: Social Media Functionality

[2298] server:

[2299] It receives post data and comment data from users and stores them in a database. It also has the function of sending notifications to other users when there are new posts or comments.

[2300] Input: User posted data and comment data

[2301] Data processing and calculation: The received data is stored in a database. When there is a new post or comment, the notification function will notify other users.

[2302] Output: Notified post and comment information

[2303] User:

[2304] Users can use the app to communicate with other users, create and send posts and comments, and receive feedback from other users.

[2305] Input: Feedback from other users

[2306] Data processing and calculation: Read comments from other users and reply as necessary.

[2307] Output: Communication results with other users

[2308] (Application example 2)

[2309] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2310] When pet owners are away from home, there is a lack of means to properly recognize their pet's hunger state and respond promptly. Furthermore, there is a lack of means to enhance communication between pets and owners.

[2311] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the animal's emotions and automatically ordering food delivery if it determines that the animal is hungry, means for collecting data from a microphone and motion sensor attached to the animal, and means for comparing the data with past accumulated data and analyzing it using AI. This makes it possible to remotely and appropriately grasp the pet's hunger state and quickly provide food. It also enhances interactive communication with the user.

[2312] An "animal-worn microphone" is a device used to collect animal audio data.

[2313] A "motion sensor" is a sensor that detects and collects animal movement data.

[2314] "Means for sending data to cloud storage" refers to a system for sending collected data to cloud storage via the Internet.

[2315] "Means of analysis using AI" refers to a system that uses artificial intelligence to analyze collected data and infer the condition of animals.

[2316] The "means for generating voice chat" is a means for converting the animal's intentions into text based on the analysis results, and then converting the text into voice.

[2317] The "means for providing voice chat to users" is a system that provides the generated voice chat to the user's terminal.

[2318] "Means including SNS functions" are functions that allow users to share information and communicate with other users.

[2319] "Means for analyzing an animal's emotions and automatically ordering food delivery if it is determined to be hungry" is a system that analyzes an animal's emotional data and, if it is determined to be hungry, automatically uses a food delivery service to order food.

[2320] "Means of comparing with previously accumulated data" refers to a means of comparing and analyzing data collected in the past with newly collected data.

[2321] This invention uses microphones and motion sensors attached to the animals to collect audio and movement data. The collected data is sent to cloud storage and compared with previously stored data. An AI model then analyzes the data to infer the animal's emotional state.

[2322] If the emotional state of the pet is estimated to be hungry, the server automatically orders food delivery. Specifically, a pet-specific application is installed on the user's device, and voice chat is provided to the user through this application. Information can also be shared with other users via social networking functions.

[2323] The hardware requires a microphone and motion sensors attached to the animal's collar, while the software includes an emotion engine for AI analysis, a voice recognition system to convert voice data into text, and a motion sensor device to detect movement data. It also requires access to cloud storage and food delivery APIs.

[2324] The server performs the following processing based on the collected data.

[2325] 1. Data collection and transmission:

[2326] The microphone collects animal sound data, and the motion sensor detects animal movement data. This data is converted into digital signals in real time, temporarily stored, and then sent to cloud storage at regular intervals.

[2327] 2. Data analysis and voice chat generation:

[2328] The AI ​​model analyzes the data retrieved from cloud storage and infers the animal's emotional state. Based on the analysis results, it generates text for voice chat and converts the text into speech using a speech synthesis system. The generated voice chat is stored on a server.

[2329] 3. Automated food delivery ordering:

[2330] If the animal's emotion is determined to be hungry, the server automatically issues a food delivery order, sending the necessary information including the user ID and pet ID, and ordering food.

[2331] 4. Providing voice chat to users:

[2332] Users can receive voice chats through the app to understand their pet's condition, and the app also has a social networking function that allows users to share information with other users.

[2333] For example, if audio data of a dog barking is collected and it corresponds to a state of "hunger," AI analysis will determine that "food delivery should be ordered." When the user checks the app, they will receive a notification saying, "Your pet seems hungry. Food delivery has been ordered," along with feedback via voice chat.

[2334] An example of a prompt is as follows:

[2335] "The sound of a dog barking has been collected. This audio and behavioral data is analyzed to infer that the animal is hungry. Food delivery will be ordered within the next hour."

[2336] In this way, even when the owner is not present, the animal's condition can be properly managed remotely and any necessary measures can be taken promptly.

[2337] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2338] Step 1:

[2339] A microphone and motion sensor attached to the animal's collar collects audio and movement data in real time. The microphone captures the animal's sounds, and the motion sensor detects the animal's movements. These data are converted into digital signals and temporarily stored in memory. The input is the animal's audio and movement data, and the output is a digital signal.

[2340] Step 2:

[2341] The device transmits the temporarily stored data to the server at regular intervals. The transmitted data includes the animal's voice data and movement data. The input is the digital signal in the memory, and the output is the data transmitted to the server.

[2342] Step 3:

[2343] The server temporarily stores the received data in local storage and periodically uploads it to cloud storage. This process ensures data availability and redundancy. The input is the transmitted data, and the output is the data stored in cloud storage.

[2344] Step 4:

[2345] The server retrieves the latest data from the cloud storage and the AI ​​model analyzes it. The AI ​​model analyzes the animal's voice and movement data to infer the animal's emotions and desires. The input is the cloud storage data and the output is the animal's emotional state.

[2346] Step 5:

[2347] The server generates text for voice chat based on the analysis results, and converts the text into speech using a speech synthesis system. The input is the emotional state of the animal, and the output is the generated voice chat.

[2348] Step 6:

[2349] The server sends the generated voice chat to the user's device, and the user receives the voice chat through a dedicated app. The input is the generated voice chat, and the output is the voice chat sent to the user's device.

[2350] Step 7:

[2351] If the server determines that the animal's emotion is hungry, it automatically orders food delivery. The input is the animal's emotional state, and the output is the food delivery order.

[2352] Step 8:

[2353] Users can understand their pet's condition through the voice chat they receive and take necessary measures promptly. Users can also share information with other users using the app's social networking function. The input is the user's emotional state and feedback, and the output is enhanced communication.

[2354] This allows you to properly manage your pet's condition remotely and take any necessary action quickly.

[2355] 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.

[2356] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[2357] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2358] 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.

[2359] 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 includes both affect 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.

[2360] 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.

[2361] 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).

[2362] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, 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 indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2363] 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."

[2364] 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.

[2365] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2366] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2367] 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.

[2368] 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.

[2369] 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.

[2370] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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. Another example of a processor is 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.

[2371] The hardware resource that executes the specific processing 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 processing may be a single processor.

[2372] 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.

[2373] 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.

[2374] 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.

[2375] 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.

[2376] The following is further disclosed regarding the above embodiment.

[2377] (Claim 1)

[2378] means for collecting data from a microphone and motion sensors attached to the animal;

[2379] means for transmitting the data to a cloud storage;

[2380] A method to compare it with past accumulated data and analyze it using AI,

[2381] A means for generating voice chat based on the analysis results;

[2382] means for providing the generated voice chat to a user;

[2383] A means including a social networking service function for sharing information with other users;

[2384] A system including:

[2385] (Claim 2)

[2386] 10. The system of claim 1, wherein the microphone and motion sensor further comprises means for collecting animal sounds and movement data in real time and converting the data into digital signals.

[2387] (Claim 3)

[2388] 10. The system of claim 1, wherein the AI ​​analysis means further comprises means for using audio data and movement data to infer an emotional state of the animal.

[2389] "Example 1"

[2390] (Claim 1)

[2391] means for collecting data from sound collecting devices and motion detecting devices attached to the animal;

[2392] means for temporarily storing the data in an internal storage device;

[2393] means for transmitting said data to a server at regular intervals;

[2394] A server receives and temporarily stores the data;

[2395] A server uploads the data to a cloud storage device;

[2396] means for acquiring data from a storage device on the cloud and analyzing the data using a generative AI model;

[2397] A means for generating voice conversation data based on the analysis results;

[2398] A means for storing voice conversation data generated by the voice synthesizer in a server;

[2399] A means for a user to connect to the server through a dedicated application;

[2400] A means for a user to download the voice conversation data and play it on a terminal device;

[2401] means including communication capabilities for sharing information with other users;

[2402] A system including:

[2403] (Claim 2)

[2404] 10. The system of claim 1, wherein the sound collecting and motion detecting device further comprises means for collecting animal sounds and motion data in real time and converting them into digital signals.

[2405] (Claim 3)

[2406] 10. The system of claim 1, wherein the generative AI model analysis means further comprises means for using audio data and movement data to infer an emotional state of the animal.

[2407] "Application Example 1"

[2408] (Claim 1)

[2409] means for collecting data from a microphone and motion sensors attached to the animal;

[2410] means for transmitting the data to a cloud storage;

[2411] A method to compare it with past accumulated data and analyze it using a generative AI model,

[2412] A means for generating voice chat based on the analysis results;

[2413] means for providing the generated voice chat to a user;

[2414] A means including a social networking service function for sharing information with other users;

[2415] A means to experience real-time interactions with animals through user terminals installed in physical stores where animals are present,

[2416] A system including:

[2417] (Claim 2)

[2418] 10. The system of claim 1, wherein the microphone and motion sensor further comprises means for collecting animal sounds and movement data in real time and converting the data into digital signals.

[2419] (Claim 3)

[2420] 10. The system of claim 1, wherein the generative AI model further comprises means for using audio data and movement data to infer an emotional state of the animal.

[2421] "Example 2: Combining Emotion Engines"

[2422] (Claim 1)

[2423] means for collecting data from audio input devices and motion detection devices attached to the animal;

[2424] means for transmitting the data to a storage device on a communication network;

[2425] A method to compare it with past accumulated data and analyze it using artificial intelligence,

[2426] A means for generating a voice conversation based on the analysis results;

[2427] means for providing the generated voice conversation to a user;

[2428] A means including an information sharing function for sharing information with other users;

[2429] A system including:

[2430] (Claim 2)

[2431] 10. The system of claim 1, wherein the audio input device and motion detection device further comprises means for collecting animal audio and motion data in real time and converting it into digital signals.

[2432] (Claim 3)

[2433] 10. The system of claim 1, wherein said artificial intelligence analysis means further comprises means for using audio data and movement data to infer an emotional state of the animal.

[2434] "Application example 2 when combining emotion engines"

[2435] (Claim 1)

[2436] means for collecting data from a microphone and motion sensors attached to the animal;

[2437] means for transmitting the data to a cloud storage;

[2438] A method to compare it with past accumulated data and analyze it using AI,

[2439] A means for generating voice chat based on the analysis results;

[2440] means for providing the generated voice chat to a user;

[2441] A means including a social networking service function for sharing information with other users;

[2442] A way to analyze an animal's emotions and automatically order food delivery if it determines it is hungry,

[2443] A system including:

[2444] (Claim 2)

[2445] 10. The system of claim 1, wherein the microphone and motion sensor further comprises means for collecting animal sounds and movement data in real time and converting the data into digital signals.

[2446] (Claim 3)

[2447] 10. The system of claim 1, wherein the AI ​​analysis means further comprises means for using audio data and movement data to infer an emotional state of the animal. [Explanation of symbols]

[2448] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for collecting data from a microphone and motion sensors attached to the animal; means for transmitting the data to a cloud storage; A method to compare it with past accumulated data and analyze it using AI, A means for generating voice chat based on the analysis results; means for providing the generated voice chat to a user; A means including a social networking service function for sharing information with other users; A system including:

2. 10. The system of claim 1, wherein the microphone and motion sensor further comprises means for collecting animal sounds and movement data in real time and converting the data into digital signals.

3. 10. The system of claim 1, wherein the AI ​​analysis means further comprises means for using audio data and movement data to infer an emotional state of the animal.

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