System

Abstract

A system is provided.SOLUTION: The system includes a means for acquiring weather forecast information, a means for generating new music by using a music generation AI on the basis of the acquired weather forecast information, a means for setting the generated music as an alarm sound, and a means for reproducing the generated music at an alarm setting time.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] If an alarm clock sounds the same every morning, people get used to it and end up oversleeping. There is a need for a way to solve this problem and always wake up to fresh music. Another challenge is to use music that matches the weather, allowing people to wake up comfortably according to their conditions that day. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for acquiring weather information, a means for generating new music using a music generation AI based on the acquired weather information, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. This system allows users to wake up to different music every morning, preventing them from oversleeping due to becoming accustomed to the same sound. Furthermore, since the parameters of the generated music are set based on weather information, music that matches the conditions of the day is provided, helping users wake up feeling refreshed. Furthermore, since the system also includes a means for identifying the user's current location when acquiring weather information, it is possible to generate music based on accurate weather information.

[0006] "Means for acquiring weather information" refers to devices or methods for collecting current weather conditions (e.g., temperature, humidity, weather, etc.).

[0007] "Means for generating new music using music generation AI" refers to devices and methods that utilize artificial intelligence technology to automatically create new music based on input parameters.

[0008] The "means for setting the generated music as an alarm sound" refers to a device or method for setting the generated music data to be used as the alarm sound of an alarm clock.

[0009] The "means for playing music generated at the set alarm time" refers to a device or method for playing music generated as an alarm sound at a preset time.

[0010] A "means for determining a user's current location" is a device or method for determining a user's current geographic location using GPS or other location-based services.

[0011] "Music parameters" refers to various setting items (for example, tempo, mood, instruments to be used, etc.) required when generating music. [Brief explanation of the drawings]

[0012] [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

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] 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).

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] The AI ​​Composition Alarm System of this invention aims to allow users to wake up to different music every morning, and has the ability to generate new music based on weather information. This prevents users from becoming accustomed to traditional alarm sounds, and provides a pleasant wake-up experience.

[0034] overview

[0035] The system consists of a means for acquiring weather information, a means for generating new music using music generation AI, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. Furthermore, when acquiring weather information, the system also includes a means for identifying the user's current location.

[0036] Program processing

[0037] Server Processing

[0038] Step 1: The server sends an alarm setting request to the device every day at a specific time (e.g., 6:00 AM). This request is made via an HTTP request, and the message contains an "alarm setting request."

[0039] Step 2: The server initializes the music generation AI based on the weather information. It sets the music parameters to be passed to the AI ​​based on the received weather information. For example, if it is sunny, it sets a bright melody and a fast tempo.

[0040] Step 3: The AI ​​generates new music based on the parameters you set, and the music is saved in MP3 or WAV format.

[0041] Step 4: The server sends the generated music data to the device, also using an HTTP response.

[0042] Terminal handling

[0043] Step 1: The device receives an alarm setting request from the server and uses GPS to determine the user's current location.

[0044] Step 2: The device sends a request to the weather information API to obtain current weather information, including weather conditions and temperature.

[0045] Step 3: The device sends the weather information to the server, which then generates music based on this information.

[0046] Step 4: The device receives the music data sent from the server and stores it in its local storage.

[0047] Step 5: The device will set the received music as the alarm sound and play it at the alarm time.

[0048] Specific examples

[0049] Assume that user A wants to wake up at 7:00 am every day.

[0050] 1. The server sends an "alarm setting request" to User A's device at 6:00 AM.

[0051] 2. The device receives the request and uses GPS to identify the current location of User A. For example, it identifies the location as "Shinjuku-ku, Tokyo."

[0052] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[0053] 4. The device sends this weather information to the server.

[0054] 5. The server receives weather information and instructs the music generation AI to create a "cheerful song suitable for sunny days."

[0055] 6. The server sends the generated music data to the device. For example, an up-tempo acoustic guitar song is generated.

[0056] 7. The device saves the music data to local storage and sets the alarm time to 7:00.

[0057] 8. At 7:00, the alarm time, the device plays music and User A wakes up to cheerful music.

[0058] 9. User A stops the alarm, giving them a comfortable start to their day.

[0059] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to habituation to the same sounds. It also uses weather-appropriate music to wake users up according to their conditions that day.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] The server checks its internal clock and sends an alarm setting request to the user's device at a specific time each day (e.g., 6:00 a.m.). This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[0063] Step 2:

[0064] The terminal receives an alarm setting request from the server, which causes the terminal to start the alarm setting process.

[0065] Step 3:

[0066] The device uses GPS to determine the user's current location. Specifically, it calls the device's location information service to obtain the latitude and longitude.

[0067] Step 4:

[0068] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to obtain weather information for the target area. This request includes latitude and longitude parameters.

[0069] Step 5:

[0070] The device receives weather information from the weather information API, including weather conditions (sunny, rainy, etc.) and temperature.

[0071] Step 6:

[0072] The weather information acquired by the device is sent to the server. Data including the weather information is sent to the server using the HTTP protocol.

[0073] Step 7:

[0074] The server receives weather information sent from the device and initializes the music generation AI based on this information.

[0075] Step 8:

[0076] The server sets music parameters based on weather information, for example, if it's "sunny," it will set the tempo faster and use bright instruments (e.g., acoustic guitar).

[0077] Step 9:

[0078] The server passes the set parameters to the music generation AI to generate new music. In this process, the AI ​​automatically creates music based on the user's specifications.

[0079] Step 10:

[0080] The server receives the generated music data and saves it in MP3 or WAV format.

[0081] Step 11:

[0082] The server sends the generated music data to the terminal using an HTTP response.

[0083] Step 12:

[0084] The device receives the music data sent from the server and stores it in local storage.

[0085] Step 13:

[0086] Set an alarm using the music data received by your device, and have the music play at the set time through the alarm application.

[0087] Step 14:

[0088] The device will play the stored music data at the set alarm time, allowing the user to wake up to new music.

[0089] Step 15:

[0090] The user wakes up to the sound of the alarm and can optionally dismiss the alarm or use the snooze function to set the alarm again.

[0091] Example 1

[0092] 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."

[0093] Conventional alarm clock devices have the problem that users become accustomed to the same sound every day, which makes it difficult to wake up effectively. In addition, there is no way to provide music that matches the weather or mood, so there is a lack of means for users to start their day more comfortably.

[0094] 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.

[0095] In this invention, the server includes means for acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information, means for setting the generated music as an alarm sound, means for playing the generated music at the set alarm time, means for identifying the user's current location, means for setting music parameters for the music generation AI from the terminal, means for transmitting the generated music data to the terminal, and means for saving the generated music data in local storage. This allows the user to wake up every day to fresh music that matches the weather, providing a pleasant awakening.

[0096] "Weather information" refers to meteorological data provided based on the user's current location, including weather conditions, temperature, humidity, and the like.

[0097] "Music generation AI" refers to algorithms or software that automatically generate music based on input parameters.

[0098] An "alarm sound" is an acoustic signal that wakes the user up at a set time, and in this system, generated music is used.

[0099] A "server" is a computer device that manages the overall processing of the system, such as obtaining weather information, initializing the music generation AI, and transmitting music data.

[0100] A "terminal" refers to an electronic device owned by a user, and in this system it mainly refers to a smartphone or the like.

[0101] "Current location" refers to the geographical location information of the user, which is determined using GPS or the like.

[0102] "Music parameters" are specific input data used to specify musical characteristics and conditions for music generation AI.

[0103] "Local storage" refers to a memory area provided within a terminal where music data and the like are stored.

[0104] An "HTTP request" is a protocol for sending data to a web server and is widely used as a means of communication.

[0105] The AI ​​Composition Alarm System of this invention aims to allow users to wake up to different music every morning by generating new music based on weather information. This prevents users from becoming accustomed to traditional alarm sounds and provides a pleasant wake-up experience.

[0106] The system consists of the following main elements:

[0107] Server Roles

[0108] The server sends an HTTP request to the user's device at a specified time each day (e.g., 6:00 AM) to notify the user of an "alarm setting request." The server also initializes the music generation AI based on weather information and sets music parameters. This music generation AI generates music with an appropriate melody and tempo according to specific weather conditions, such as sunny or rainy weather. The generated music data is saved in MP3 or WAV format and sent to the device.

[0109] Device Role

[0110] The device receives an alarm setting request from the server and uses GPS to identify the user's current location. It then sends a request to the weather information API to obtain current weather information for that location. It then sends the obtained weather information to the server and receives music data generated by the server. The received music data is saved in local storage and played at the alarm time.

[0111] User operations

[0112] Users wake up to new music every morning. When the set alarm sounds, users wake up to pleasant music and press the alarm stop button on their device to turn off the alarm.

[0113] Hardware and software used

[0114] Server: Virtual server on a cloud platform (e.g. AWS EC2)

[0115] Device: A smartphone owned by the user (e.g., an Android device)

[0116] Weather information API: Weather information provision service (e.g. OpenWeatherMap API)

[0117] Music generation AI: Automatic composition algorithms (e.g., OpenAI's music generation model)

[0118] Specific examples

[0119] Let's assume that User A wants to wake up at 7:00 AM every day. The server sends an "alarm setting request" to User A's device at 6:00 AM. The device receives the request and uses GPS to identify User A's current location. For example, it may identify it as "Shinjuku Ward, Tokyo." Based on this location, the device accesses a weather information API and obtains weather information such as "sunny, temperature 15 degrees." When the device sends this weather information to the server, the server instructs the music generation AI to generate "an upbeat song suitable for a sunny day." The generated music is sent to the device as an up-tempo acoustic guitar piece. The device stores this music in local storage and plays it at 7:00 AM, the alarm time. User A wakes up to upbeat music, allowing them to start their day feeling refreshed.

[0120] Prompt Sentence Examples

[0121] "Generate a bright, uptempo acoustic guitar song to welcome a new morning. The current weather is sunny and the temperature is 15 degrees."

[0122] This system allows users to wake up to new music every day, preventing them from becoming accustomed to the same music and providing a pleasant awakening. It also generates music based on weather information, helping users wake up to music that suits the conditions of the day.

[0123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0124] Step 1:

[0125] The server sends an "alarm setting request" via HTTP request to the user's device at the specified time of 6:00 AM every day.

[0126] What happens: The server uses a scheduler (e.g., a Cron job) to send an HTTP request to a specific endpoint at a specified time.

[0127] Input: Time (e.g. 6:00 AM)

[0128] Output: HTTP request (alarm setting request)

[0129] Step 2:

[0130] The terminal receives an alarm setting request from the server and identifies the user's current location using GPS.

[0131] Specific operation: The device analyzes the received request and activates the GPS function to obtain the current location information.

[0132] Input: HTTP request (alarm setting request)

[0133] Output: Current location (e.g. Shinjuku-ku, Tokyo)

[0134] Step 3:

[0135] The device sends a request to the weather information API to obtain current weather information.

[0136] Specific operation: The device uses the identified location information to send an API request to a weather information service to obtain weather data.

[0137] Input: Current location (e.g. Shinjuku-ku, Tokyo)

[0138] Output: Weather information (e.g. sunny, temperature 15 degrees)

[0139] Step 4:

[0140] The terminal sends the acquired weather information to the server as an HTTP request.

[0141] Specific operation: The device formats the acquired weather information and sends it to the server via an HTTP request.

[0142] Input: Weather information (e.g. sunny, temperature 15 degrees)

[0143] Output: HTTP request (weather information)

[0144] Step 5:

[0145] The server receives weather information sent from the device and initializes the music generation AI based on that information.

[0146] How it works: The server analyzes the received weather information and generates prompts for the music generation AI to set specific music parameters, for example, a bright melody and a fast tempo on a sunny day.

[0147] Input: HTTP request (weather information)

[0148] Output: Prompt sentence (e.g., upbeat melody, fast tempo)

[0149] Step 6:

[0150] The server generates new music using music generation AI and stores the generated music data.

[0151] Specific operation: The music generation AI receives a prompt, generates new music, and saves it as an MP3 or WAV file.

[0152] Input: prompt statement

[0153] Output: Music data (MP3 or WAV format)

[0154] Step 7:

[0155] The server transmits the generated music data to the terminal in an HTTP response.

[0156] Specific operation: The server encodes the generated music file and sends it back to the device in an HTTP response.

[0157] Input: Music data (MP3 or WAV format)

[0158] Output: URL of HTTP response (music data)

[0159] Step 8:

[0160] The terminal receives the music data sent from the server and stores it in local storage.

[0161] Specific operation: The device obtains the URL of the music file from the HTTP response, downloads it, and saves it to local storage.

[0162] Input: HTTP response (music data URL)

[0163] Output: Music file (saved to local storage)

[0164] Step 9:

[0165] The terminal sets the received music file as an alarm sound and plays it at the alarm time.

[0166] Specific behavior: The device uses the alarm management function to set a new music file as the alarm sound, and plays the saved music when the alarm time arrives.

[0167] Input: Music file (stored in local storage)

[0168] Output: Alarm sound (playback of music file)

[0169] Step 10:

[0170] The user wakes up to the alarm sound and presses the alarm stop button on the terminal to cancel the alarm.

[0171] Specific actions: The user taps the device's operation panel to stop the alarm and start their day.

[0172] Input: Alarm sound (playing a music file)

[0173] Output: Stop alarm

[0174] (Application example 1)

[0175] 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."

[0176] With conventional alarm systems, users often become accustomed to a certain set of music or sounds, resulting in poor awakening. Furthermore, the music that provides a comfortable wake-up experience for a user depends on the individual's situation and environment, so general alarm sounds have limitations. While there is a particular need to improve the quality of wake-ups based on external environmental factors such as weather and temperature, there has been a lack of means to achieve this. Another problem is that music generation is not optimized based on individual user preferences or wake-up data.

[0177] 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.

[0178] In this invention, the server includes means for acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information, means for setting the generated music as an alarm sound, means for playing the generated music at the set alarm time, means for setting parameters for the generated music based on the weather information, means for identifying the user's current location, and means for generating prompts for the music generation AI and generating music based on the prompts. This allows fresh music that is appropriate for the weather and environment to be automatically generated every morning, allowing the user to wake up comfortably and efficiently. Furthermore, the music generation can be adaptively optimized using the user's wake-up data, providing a consistently comfortable wake-up experience.

[0179] "Weather information" is data relating to weather conditions such as current weather conditions, temperature, humidity, rainfall, and wind speed.

[0180] "Music generation AI" is a system that uses artificial intelligence to automatically create new music.

[0181] An "alarm sound" is the music or sound that is played at the alarm time.

[0182] The "current location" is the geographical location information of the physical location of the user's terminal.

[0183] A "prompt" is an instruction or input given to an AI system based on specific conditions or needs.

[0184] "Music parameters" are control elements such as melody, tempo, rhythm, and volume that are used when generating music.

[0185] A "generative AI model" is a system that uses artificial intelligence algorithms to create new content and information.

[0186] "Local storage" refers to a data storage area attached to a user's device.

[0187] An "alarm" is a function that operates at a set time to notify the user.

[0188] "Adaptive optimization" is the process of incrementally improving a system's performance and results based on historical data and user input.

[0189] This invention is an "AI Composition Alarm System" that allows users to wake up comfortably with different music every morning. This system generates new music based on weather information and uses it as an alarm sound. Below, we will explain in detail how to implement this system.

[0190] System configuration

[0191] The system mainly consists of the following components:

[0192] server

[0193] How to get weather information

[0194] A method for generating new music using music generation AI based on acquired weather information

[0195] A means of generating prompts for a music generation AI and generating music based on the prompts

[0196] Terminal

[0197] A means of determining the user's current location

[0198] A means of accessing the weather information API and obtaining weather information

[0199] A means of storing music data received from a server in local storage

[0200] A way to play the generated music at the alarm time

[0201] User

[0202] Set an alarm through your device to wake you up every morning

[0203] Hardware and Software Configuration

[0204] Hardware

[0205] Mobile devices such as smartphones and smart glasses

[0206] server

[0207] GPS Modules

[0208] software

[0209] requests: A library for sending HTTP requests

[0210] geopy: a library for obtaining geolocation information

[0211] pydub: A library for manipulating music files

[0212] playsound: a library for playing music

[0213] Weather information API (e.g. OpenWeatherMap)

[0214] Program processing overview

[0215] Server Processing

[0216] The server sends a request to set an alarm to the user's device at a specified time (e.g., 6:00 AM). This request is made using an HTTP request. The server then initializes the music generation AI based on weather information and generates new music based on the specified parameters. The generated music data is saved in MP3 or WAV format and sent to the user's device using an HTTP response.

[0217] Terminal handling

[0218] The device identifies the user's current location in response to a request from the server, accesses the weather information API to obtain weather information, sends the obtained weather information to the server, and saves the music data sent from the server in local storage.The device then plays the music generated at the alarm time.

[0219] Specific examples

[0220] If user A wants to wake up at 7:00 am every day, the following happens:

[0221] 1. The server sends an "alarm setting request" to User A's device at 6:00 AM.

[0222] 2. The device receives the request and uses GPS to identify the current location of User A. For example, it identifies the location as "Shinjuku-ku, Tokyo."

[0223] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[0224] 4. The device sends this weather information to the server.

[0225] 5. The server receives weather information and instructs the music generation AI to create a "cheerful song suitable for sunny days."

[0226] 6. The server sends the generated music data to the device. For example, an up-tempo acoustic guitar song is generated.

[0227] 7. The device saves the music data to local storage and sets the alarm time to 7:00.

[0228] 8. At 7:00, the alarm time, the device plays music and User A wakes up to cheerful music.

[0229] 9. User A stops the alarm, giving them a comfortable start to their day.

[0230] Prompt Sentence Examples

[0231] Examples of prompts include:

[0232] "I'd like a song with a bright, lively melody line for sunny days. Please create an up-tempo song that will start the morning off on a pleasant note."

[0233] As described above, this system allows users to wake up to fresh music every morning, and also allows them to start their day off right with the optimal alarm sound depending on the weather and environment.

[0234] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0235] Step 1:

[0236] The server sends a request to set an alarm to the user's device at a specific time every day (e.g., 6:00 AM). This request is made via an HTTP request, and the message contains an "alarm setting request." The sent HTTP request is the input, and the arrival of the request data on the user's device is the output.

[0237] Step 2:

[0238] The device receives an alarm setting request from the server. It then uses the GPS module to determine the user's current location. Specifically, the device uses GPS to obtain longitude and latitude information and uses this as location information. The input is the request data from the server, and the output is the obtained location information.

[0239] Step 3:

[0240] The device sends a request to the weather information API based on its location information to obtain current weather information. The obtained weather information includes weather conditions, temperature, humidity, etc. Specifically, an HTTP request is sent to the API, and weather data is returned as a response. The input is location information, and the output is weather information.

[0241] Step 4:

[0242] The device sends the weather information it has acquired to the server. The weather information is essential because the server generates music based on this information. The weather information sent by the device is the input, and the server's receipt of it is the output.

[0243] Step 5:

[0244] The server initializes the music generation AI based on the received weather information and sets the music generation parameters. For example, if it's sunny, it sets a bright melody and a fast tempo. New music is then generated based on the set parameters. The input is the weather information and music generation parameters, and the output is the generated music data.

[0245] Step 6:

[0246] The server sends the generated music data to the user's device as an HTTP response. This generated music is saved in MP3 or WAV format. The input is the generated music data, and the output is the music data being sent to the user's device.

[0247] Step 7:

[0248] The device receives music data sent from the server and saves it in local storage. The saved music data is set as an alarm sound. The input is the music data received from the server, and the output is saving the music data to local storage.

[0249] Step 8:

[0250] The device sets the stored music data as an alarm sound and plays it at the alarm time. When the alarm time arrives, the music plays and the user wakes up. The input is the music data stored in local storage and the alarm time, and the output is the music playing and the user waking up.

[0251] These steps allow the user to wake up pleasantly to new music every morning.

[0252] 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.

[0253] The "AI Composition Alarm System" of this invention aims to allow users to wake up to different music every morning, and has the ability to generate new music based on weather information and the user's emotional information. This prevents users from becoming accustomed to the alarm sound and provides a comfortable awakening. Furthermore, by taking the user's emotions into consideration, the system further promotes a pleasant awakening.

[0254] overview

[0255] The system consists of a means for acquiring weather information, an emotion engine that recognizes the user's emotions, a means for generating new music using music generation AI, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. Furthermore, it also includes a means for identifying the user's current location when acquiring weather information.

[0256] Program processing

[0257] Server Processing

[0258] Step 1: The server sends an alarm setting request to the device every day at a specific time (e.g., 6:00 AM). This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[0259] Step 2: When the user's emotional information is sent, the server receives it and initializes the music generation AI. The emotional information is obtained from an emotion engine that analyzes the user's emotions using, for example, a camera or microphone.

[0260] Step 3: The server sets music parameters based on the received weather information and the user's emotional information. Further fine-tuning is performed based on the emotional information, such as bright and cheerful music for sunny days and relaxing music for rainy days.

[0261] Step 4: The AI ​​generates new music based on the parameters you set, which can then be saved in MP3 or WAV format, for example.

[0262] Step 5: The server sends the generated music data to the device, also using an HTTP response.

[0263] Terminal handling

[0264] Step 1: The device receives the alarm setting request from the server and uses GPS to determine the user's current location. Specifically, it calls the device's location service to obtain the latitude and longitude.

[0265] Step 2: The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to get weather information for the target area. This request includes latitude and longitude parameters.

[0266] Step 3: The device receives weather information from the weather information API, including the weather condition (sunny, rainy, etc.) and temperature.

[0267] Step 4: The device sends the acquired weather information and emotion data from the user's emotion engine to the server. The emotion engine analyzes the user's current emotion using the camera and microphone.

[0268] Step 5: The device receives the music data sent from the server and stores it in its local storage.

[0269] Step 6: The device uses the received music data to set an alarm, and the music will be played at the set time through the alarm application.

[0270] Step 7: At the set alarm time, the device will play the music data stored on it, allowing the user to wake up to new music.

[0271] Specific examples

[0272] Assume that user B wants to wake up at 7:00 AM every day.

[0273] 1. The server sends an "alarm setting request" to User B's device at 6:00 AM.

[0274] 2. The device receives the request and uses GPS to identify the current location of User B. For example, it identifies the location as "Chuo-ku, Osaka City."

[0275] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 20 degrees."

[0276] 4. The device uses the emotion engine to analyze User B's emotions and determine, for example, that he is "relaxed."

[0277] 5. The device combines weather information and emotion information and sends it to the server.

[0278] 6. The server receives weather information and emotional information and has the music generation AI create a "relaxing song suitable for a sunny day."

[0279] 7. The server sends the generated music data to the device. For example, a slow, relaxing acoustic guitar song is generated.

[0280] 8. The device saves the music data to local storage and sets the alarm time to 7:00.

[0281] 9. At 7:00, the alarm time, the device plays music and User B wakes up to relaxing music.

[0282] 10. User B turns off the alarm and starts the day in a relaxed state.

[0283] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up tailored to their individual condition.

[0284] The processing flow will be explained below.

[0285] Step 1:

[0286] The server sends an alarm setting request to the user's device every day at a specific time (e.g., 6:00 a.m.) This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[0287] Step 2:

[0288] The terminal receives an alarm setting request from the server, which causes the terminal to start the alarm setting process.

[0289] Step 3:

[0290] The device uses GPS to determine the user's current location. Specifically, it calls the device's location information service to obtain the latitude and longitude.

[0291] Step 4:

[0292] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to obtain weather information for the target area. This request includes latitude and longitude parameters.

[0293] Step 5:

[0294] The device receives weather information from the weather information API, including weather conditions (sunny, rainy, etc.) and temperature.

[0295] Step 6:

[0296] The device uses the built-in camera and microphone to acquire data to recognize emotions from the user's face and voice, and this processing is carried out by the emotion engine.

[0297] Step 7:

[0298] The device identifies the user's emotional state (e.g., relaxed, stressed, etc.) based on analysis by the emotion engine.

[0299] Step 8:

[0300] The weather information and emotion information acquired by the device are sent to the server. Weather information and emotion data are sent to the server using the HTTP protocol.

[0301] Step 9:

[0302] The server receives weather and emotion information sent from the device and initializes the music generation AI based on this information.

[0303] Step 10:

[0304] The server sets music parameters based on weather information and emotional information. For example, if the weather is "sunny" and the user is "relaxed," the tempo is slowed down and relaxing instruments (e.g., acoustic guitar or piano) are used.

[0305] Step 11:

[0306] The server passes the set parameters to the music generation AI to generate new music. In this process, the AI ​​automatically creates music based on the specified parameters.

[0307] Step 12:

[0308] The server receives the generated music data and saves it in MP3 or WAV format.

[0309] Step 13:

[0310] The server sends the generated music data to the terminal using an HTTP response.

[0311] Step 14:

[0312] The device receives the music data sent from the server and stores it in local storage.

[0313] Step 15:

[0314] Set an alarm using the music data received by the device, and use the alarm application to play the music at the set time.

[0315] Step 16:

[0316] The device will play the stored music data at the set alarm time, allowing the user to wake up to new music.

[0317] Step 17:

[0318] The user wakes up to the sound of the alarm and can optionally dismiss the alarm or use the snooze function to set the alarm again.

[0319] Specific examples

[0320] Assume that user B wants to wake up at 7:00 AM every day.

[0321] 1. The server sends an "alarm setting request" to User B's device at 6:00 AM.

[0322] 2. The device receives the request and uses GPS to identify the current location of User B. For example, it identifies that it is in Shinjuku Ward, Tokyo.

[0323] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[0324] 4. The device uses the emotion engine to analyze User B's emotions and determine, for example, that he is "relaxed."

[0325] 5. The device combines weather information and emotion information and sends it to the server.

[0326] 6. The server receives weather information and emotional information and has the music generation AI create a "relaxing song suitable for a sunny day."

[0327] 7. The server sends the generated music data to the device. For example, a slow, relaxing acoustic guitar song is generated.

[0328] 8. The device saves the music data to local storage and sets the alarm time to 7:00.

[0329] 9. At 7:00, the alarm time, the device plays music and User B wakes up to relaxing music.

[0330] 10. User B turns off the alarm and starts the day in a relaxed state.

[0331] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up tailored to their individual condition.

[0332] Example 2

[0333] 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."

[0334] With conventional alarm systems, users become accustomed to the same alarm sound, making it difficult to wake up effectively. Furthermore, there was a lack of technology to generate alarm sounds that took into account not only weather information but also the user's emotional information, making it impossible to provide a comfortable waking experience tailored to each individual user.

[0335] 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.

[0336] In this invention, the server includes means for acquiring weather information, means for acquiring a user's emotions using an emotion engine that recognizes the user's emotions, and means for generating new music using a music generation AI model based on the acquired weather information and user's emotion information. This allows new music that is optimal for each individual user to be generated every day, providing a pleasant awakening.

[0337] "Weather information" is a general term for relevant meteorological data such as current weather conditions, temperature, and humidity.

[0338] An "emotion engine" is software or hardware that analyzes a user's facial expressions, tone of voice, etc., to recognize the user's emotional state.

[0339] A "music generation AI model" is an artificial intelligence model that automatically generates new music based on specified parameters.

[0340] An "alarm sound" is an audio signal that is set to wake the user up.

[0341] "Current Location" means the user's actual geographic location as determined using GPS or other location technology.

[0342] The purpose of the "AI Composition Alarm System" of this invention is to allow users to wake up to different music every morning. Specifically, it generates new music based on weather information and the user's emotional state, and sets it as the alarm sound, preventing users from becoming accustomed to the alarm sound and providing a pleasant awakening. Furthermore, by taking the user's emotions into consideration, it further promotes a pleasant awakening.

[0343] System Components

[0344] The system includes the following components:

[0345] 1. How to get weather information:

[0346] Specifically, current weather information is obtained using a weather information API (e.g., OpenWeatherMap).

[0347] 2. Emotion engine that recognizes user emotions:

[0348] It includes hardware and software for analyzing the user's facial expressions and tone of voice to recognize their current emotional state.

[0349] 3. Music generation AI model:

[0350] Includes artificial intelligence models (e.g., GPT-3-based generative AI) that automatically generate new music based on specified parameters.

[0351] 4. How to set the generated music as an alarm sound:

[0352] Save the music data to the device's local storage and set it as the alarm sound through the alarm application.

[0353] 5. How to play the generated music at the alarm time:

[0354] It includes software and hardware for playing an alarm sound at a set time.

[0355] 6. How to determine the user's current location:

[0356] The user's current location is determined using location information services such as GPS.

[0357] Specific operation of the system

[0358] 1. Server operation:

[0359] The server sends an alarm setting request to the user's terminal at a specified time every day using the HTTP protocol.

[0360] The server receives weather information and user emotional information sent from the device and initializes the music generation AI model based on that information.

[0361] The music generation AI model is given a prompt like this to generate music:

[0362] "The user is feeling relaxed today. The current weather is sunny and the temperature is 20 degrees. Based on these conditions, generate a relaxing acoustic guitar song."

[0363] The generated music data is sent to the terminal in MP3 or WAV format.

[0364] 2. Device behavior:

[0365] The device receives an alarm setting request from the server and uses the GPS function to determine the current location.

[0366] Based on the identified current location, a request is sent to the weather information API to obtain weather information.

[0367] The device uses a camera and microphone to analyze the user's emotions with an emotion engine, and transmits the obtained emotion information to the server.

[0368] The terminal receives the music data sent from the server and stores it in local storage.

[0369] Use the Alarms application to set an alarm to play music at a specified time.

[0370] It plays music at a set time to wake the user up.

[0371] Hardware and software used

[0372] Server: Servers operated in data centers with high-performance processors (e.g., cloud infrastructure)

[0373] Device: Smartphone with GPS function, camera and microphone (e.g. smart device)

[0374] Weather Information API: Web API that provides weather information (e.g., OpenWeatherMap)

[0375] Music generation AI model: An artificial intelligence model that generates music based on specified parameters (e.g., GPT-3)

[0376] Location services: Standard GPS function of the device

[0377] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up in a way that suits their individual condition.

[0378] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0379] Step 1:

[0380] The server sends an "alarm setting request" to the user's device as an HTTP request every day at 6:00 AM. This request contains information for setting the alarm. The input is the server's scheduled time, and the output is the request sent to the user's device.

[0381] Step 2:

[0382] The device receives the alarm setting request from the server and uses the location information service to determine the current location. Specifically, it calls the device's GPS function to obtain latitude and longitude data. This location information is used as input, and the output is to save the location information in the device's internal memory.

[0383] Step 3:

[0384] The device sends a request to the weather information API based on the identified current location. The request includes latitude and longitude parameters. The input is location data, and the output is a request to the weather information API.

[0385] Step 4:

[0386] Receives a response from the weather information API and analyzes its contents. Specifically, it obtains data such as the current weather conditions and temperature. The input is the response data from the API, and the output is the analyzed weather information.

[0387] Step 5:

[0388] The device uses a camera and microphone to capture the user's facial expressions and voice, which are then analyzed by the emotion engine. The emotion engine then determines the user's emotional state based on this data. The input is the user's facial expressions and voice data, and the output is the determined emotional information.

[0389] Step 6:

[0390] The device sends the acquired weather information and emotion information to the server. Specifically, it uses an HTTP POST request and includes the header "Content-Type: application / json". The input is weather information and emotion information, and the output is data sent to the server.

[0391] Step 7:

[0392] The server receives weather information and emotion information sent from the device. Based on this data, it creates a prompt sentence to input into the music generation AI model. The input is weather information and emotion information, and the output is the generation of a prompt sentence. Specifically, it generates a sentence such as, "The user is feeling relaxed today. The current weather is sunny, and the temperature is 20 degrees. Based on these conditions, please generate a relaxing acoustic guitar song."

[0393] Step 8:

[0394] The music generation AI model generates new music based on a created prompt. The input is the prompt, and the output is the generated music data. Specifically, music files are generated in MP3 or WAV format.

[0395] Step 9:

[0396] The server sends the generated music data to the terminal. This is done using HTTP responses. The input is the music data, and the output is data sent to the user's terminal.

[0397] Step 10:

[0398] The device saves the received music data in local storage. The save destination is, for example, a directory called " / storage / emulated / 0 / Alarms / ". The input is music data, and the output is saved to local storage.

[0399] Step 11:

[0400] The device sets an alarm using stored music data. Using the alarm management application API, music is played at the set time (e.g., 7:00 AM). The input is the music data and the set time, and the output is the alarm setting.

[0401] Step 12:

[0402] At the set time, the device will play music to wake the user up. The input is setting the alarm and the output is playing music. The user can wake up comfortably to new music.

[0403] (Application example 2)

[0404] 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."

[0405] Conventional alarm systems wake users up with the same sound every time, which can lead to users becoming accustomed to the alarm sound and making it difficult to wake up. Furthermore, background music in stores tends to be fixed, and music is played without taking into account the emotions of customers and employees or external weather information, making it difficult to maximize the store atmosphere and customer experience.

[0406] 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 acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information and emotional information, means for setting the generated music as an alarm sound or background music for the store, means for playing the generated music at the set alarm time or in real time, and means for acquiring emotional information of customers and employees. This makes it possible to generate appropriate music according to the emotional state of the user or customer and the weather information, allowing for a comfortable awakening and providing an optimal store atmosphere.

[0407] "Weather information" refers to current and near-future weather conditions and meteorological data such as temperature, precipitation, and wind speed.

[0408] "Emotion information" is data that represents the psychological state or emotions of a user or customer, and is classified into emotion categories such as "happy," "relaxed," and "excited."

[0409] "Music generation AI" is an artificial intelligence system that automatically generates new music by setting parameters based on weather information and emotional information.

[0410] An "alarm sound" is music or sound that is played to wake the user up at a specified time.

[0411] "BGM" is an abbreviation for background music, and refers to the background music played in indoor spaces such as stores and commercial facilities.

[0412] A "server" is a computing device that provides specific services and data processing over a network and serves client devices.

[0413] "Device" refers to a hardware device that collects user or customer emotions and weather information and plays generated music. Examples include smartphones, smart glasses, head-mounted displays, and robots.

[0414] "Location information" is data that indicates the current geographical location of a user or a store and is expressed in the form of latitude and longitude.

[0415] A "weather information API" is an application programming interface that provides weather information over the web and is a means for obtaining weather data.

[0416] An "emotion analysis engine" is software that analyzes data obtained from input devices such as cameras and microphones and identifies the emotional state of users or customers.

[0417] "HTTP protocol" is an abbreviation for Hypertext Transfer Protocol, an Internet protocol for data communication.

[0418] "Music parameters" are set values ​​that determine the characteristics of music, and include tempo, key, instrument composition, and the like.

[0419] This invention is a system that uses music generation AI to generate new music based on weather information and emotional information, and plays it as an alarm sound or background music in a physical store. Specifically, it is implemented using a server and a terminal.

[0420] System configuration

[0421] The system consists of the following main components:

[0422] Weather information acquisition means: Uses a weather information API (e.g., OpenWeatherMap) to acquire weather data based on the terminal's current location.

[0423] Emotion information acquisition means: An emotion analysis engine that uses cameras and microphones to analyze the emotional state of users, store customers, and employees.

[0424] Music generation method: Based on the weather and emotional information, the music generation AI generates new music. The generated music is saved in MP3 or WAV format.

[0425] Alarm / BGM setting method: The generated music is set as an alarm sound or background music in the store. Devices such as smartphones, smart glasses, head-mounted displays, and robots are used.

[0426] Playback method: Play the generated music at a specified time or in real time.

[0427] Server Processing

[0428] The server has the following functions:

[0429] Sending an alarm setting request: Send an alarm setting request to the client device at a specific time every day (e.g., 10:00 a.m.), which wakes up the user or store's system and collects the appropriate data.

[0430] Music generation: Music parameters are set based on received weather and emotional information, and new music is generated using music generation AI.

[0431] Sending music data: The generated music data is sent to the device so that it can be used as an alarm sound or background music.

[0432] Terminal handling

[0433] The main processing of the terminal is as follows:

[0434] Obtaining location information: Use GPS to determine current location information, and send it to a weather information API to obtain weather information for the target area.

[0435] Acquiring emotional information: Emotional information of users and customers is acquired using a camera or microphone and sent to the server.

[0436] Receiving and storing music data: Receives music data sent from the server and stores it in local storage.

[0437] Setting and playing alarms and background music: Set the generated music as an alarm sound or background music and play it at a specified time or in real time.

[0438] Examples of specific examples and prompts

[0439] The actual usage scenario is described below.

[0440] Specific examples

[0441] The flow when Store A starts the system at 10:00 in the morning while preparing to open is as follows.

[0442] 1. The server sends a "BGM setting request" to the terminal at store A.

[0443] 2. The device receives the request and uses GPS to determine its current location. For example, it may determine that it is in Shibuya Ward, Tokyo.

[0444] 3. The device accesses the weather information API and obtains weather information for Shibuya Ward, Tokyo. For example, it obtains weather information such as "sunny, temperature 25 degrees."

[0445] 4. The emotion analysis engine analyzes the employee's emotions and determines that they are "energetic and cheerful."

[0446] 5. The device sends weather information and emotion information to the server.

[0447] 6. The server asks the music generation AI to create a "lively and cheerful song suitable for a sunny day."

[0448] 7. The server sends the generated music data to the device. For example, lively pop music is generated.

[0449] 8. The device stores the music data locally and then plays it on the store's sound system.

[0450] 9. The music in the store creates a lively and cheerful atmosphere, making customers feel comfortable.

[0451] Prompt Sentence Examples

[0452] Weather: Sunny, 25 degrees

[0453] Emotional information: Lively and cheerful

[0454] Generated Music Style: Pop

[0455] Generated music tempo: Fast

[0456] In this way, appropriate music is generated according to the emotional state of the user or customer and weather information, thereby providing a pleasant awakening and an optimal store atmosphere.

[0457] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0458] Step 1:

[0459] The server sends an alarm setting request to the client device at a specific time every day (e.g., 10:00 a.m.). This request is sent using the HTTP protocol and contains the message "Request to set alarm." The input is the specified time, and the output is the alarm setting request message.

[0460] Step 2:

[0461] The device receives an alarm setting request from the server and uses GPS to determine the current location. The input is the alarm setting request message, and the output is the current location information (latitude and longitude). Specifically, the device's location information service is called to obtain the latitude and longitude.

[0462] Step 3:

[0463] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location information to obtain weather information for the target area. This request includes latitude and longitude parameters. The input is the current location information, and the output is weather information.

[0464] Step 4:

[0465] The device receives weather information from the weather information API. This information includes the weather condition (sunny, rainy, etc.) and temperature. The input is the response from the weather information API, and the output is the specific weather information.

[0466] Step 5:

[0467] The device uses a camera and microphone to obtain emotional information from the user or customer through an emotion analysis engine. The input is data from the camera or microphone, and the output is analyzed emotional information. Specifically, facial expression analysis and voice analysis technologies are used.

[0468] Step 6:

[0469] The device combines the acquired weather information and emotion information and sends it to the server. The input is weather information and emotion information, and the output is request data to the server. Specifically, the weather information and emotion information are sent to the server as parameters using the HTTP protocol.

[0470] Step 7:

[0471] The server initializes the music generation AI and sets the music parameters based on the received weather and emotional information. Further fine-tuning is made based on emotional information, such as bright and cheerful music for sunny days and relaxing music for rainy days. The input is weather information and emotional information, and the output is the set music parameters.

[0472] Step 8:

[0473] The server generates new music based on the set parameters using music generation AI. This music is saved in MP3 or WAV format, for example. The input is the music parameters, and the output is the generated music data. Specifically, the AI ​​model generates music by inputting prompts.

[0474] Step 9:

[0475] The server sends the generated music data to the device. This is also done using HTTP responses. The input is the generated music data, and the output is the transmission of the music data to the device.

[0476] Step 10:

[0477] The device receives the music data sent from the server and stores it in local storage. The input is music data, and the output is storage in local storage.

[0478] Step 11:

[0479] The device uses the received music data to set alarms and background music for the store. Music is played at the set time or in real time through an alarm application or sound system. The input is music data, and the output is alarm and background music settings. Specifically, this includes scheduler functions and sound system settings.

[0480] Step 12:

[0481] The device plays music data stored on it at the set alarm time or in real time. This allows users to wake up to new music or enjoy appropriate background music in the store. The input is the set timing, and the output is music playback.

[0482] 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.

[0483] 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.

[0484] 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.

[0485] [Second embodiment]

[0486] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0487] 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.

[0488] 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).

[0489] 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.

[0490] 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.

[0491] 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).

[0492] 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.

[0493] 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.

[0494] 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.

[0495] 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.

[0496] 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.

[0497] 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."

[0498] The AI ​​Composition Alarm System of this invention aims to allow users to wake up to different music every morning, and has the ability to generate new music based on weather information. This prevents users from becoming accustomed to traditional alarm sounds, and provides a pleasant wake-up experience.

[0499] overview

[0500] The system consists of a means for acquiring weather information, a means for generating new music using music generation AI, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. Furthermore, when acquiring weather information, the system also includes a means for identifying the user's current location.

[0501] Program processing

[0502] Server Processing

[0503] Step 1: The server sends an alarm setting request to the device every day at a specific time (e.g., 6:00 AM). This request is made via an HTTP request, and the message contains an "alarm setting request."

[0504] Step 2: The server initializes the music generation AI based on the weather information. It sets the music parameters to be passed to the AI ​​based on the received weather information. For example, if it is sunny, it sets a bright melody and a fast tempo.

[0505] Step 3: The AI ​​generates new music based on the parameters you set, and the music is saved in MP3 or WAV format.

[0506] Step 4: The server sends the generated music data to the device, also using an HTTP response.

[0507] Terminal handling

[0508] Step 1: The device receives an alarm setting request from the server and uses GPS to determine the user's current location.

[0509] Step 2: The device sends a request to the weather information API to obtain current weather information, including weather conditions and temperature.

[0510] Step 3: The device sends the weather information to the server, which then generates music based on this information.

[0511] Step 4: The device receives the music data sent from the server and stores it in its local storage.

[0512] Step 5: The device will set the received music as the alarm sound and play it at the alarm time.

[0513] Specific examples

[0514] Assume that user A wants to wake up at 7:00 am every day.

[0515] 1. The server sends an "alarm setting request" to User A's device at 6:00 AM.

[0516] 2. The device receives the request and uses GPS to identify the current location of User A. For example, it identifies the location as "Shinjuku-ku, Tokyo."

[0517] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[0518] 4. The device sends this weather information to the server.

[0519] 5. The server receives weather information and instructs the music generation AI to create a "cheerful song suitable for sunny days."

[0520] 6. The server sends the generated music data to the device. For example, an up-tempo acoustic guitar song is generated.

[0521] 7. The device saves the music data to local storage and sets the alarm time to 7:00.

[0522] 8. At 7:00, the alarm time, the device plays music and User A wakes up to cheerful music.

[0523] 9. User A stops the alarm, giving them a comfortable start to their day.

[0524] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to habituation to the same sounds. It also uses weather-appropriate music to wake users up according to their conditions that day.

[0525] The processing flow will be explained below.

[0526] Step 1:

[0527] The server checks its internal clock and sends an alarm setting request to the user's device at a specific time each day (e.g., 6:00 a.m.). This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[0528] Step 2:

[0529] The terminal receives an alarm setting request from the server, which causes the terminal to start the alarm setting process.

[0530] Step 3:

[0531] The device uses GPS to determine the user's current location. Specifically, it calls the device's location information service to obtain the latitude and longitude.

[0532] Step 4:

[0533] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to obtain weather information for the target area. This request includes latitude and longitude parameters.

[0534] Step 5:

[0535] The device receives weather information from the weather information API, including weather conditions (sunny, rainy, etc.) and temperature.

[0536] Step 6:

[0537] The weather information acquired by the device is sent to the server. Data including the weather information is sent to the server using the HTTP protocol.

[0538] Step 7:

[0539] The server receives weather information sent from the device and initializes the music generation AI based on this information.

[0540] Step 8:

[0541] The server sets music parameters based on weather information, for example, if it's "sunny," it will set the tempo faster and use bright instruments (e.g., acoustic guitar).

[0542] Step 9:

[0543] The server passes the set parameters to the music generation AI to generate new music. In this process, the AI ​​automatically creates music based on the user's specifications.

[0544] Step 10:

[0545] The server receives the generated music data and saves it in MP3 or WAV format.

[0546] Step 11:

[0547] The server sends the generated music data to the terminal using an HTTP response.

[0548] Step 12:

[0549] The device receives the music data sent from the server and stores it in local storage.

[0550] Step 13:

[0551] Set an alarm using the music data received by your device, and have the music play at the set time through the alarm application.

[0552] Step 14:

[0553] The device will play the stored music data at the set alarm time, allowing the user to wake up to new music.

[0554] Step 15:

[0555] The user wakes up to the sound of the alarm and can optionally dismiss the alarm or use the snooze function to set the alarm again.

[0556] Example 1

[0557] 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."

[0558] Conventional alarm clock devices have the problem that users become accustomed to the same sound every day, which makes it difficult to wake up effectively. In addition, there is no way to provide music that matches the weather or mood, so there is a lack of means for users to start their day more comfortably.

[0559] 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.

[0560] In this invention, the server includes means for acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information, means for setting the generated music as an alarm sound, means for playing the generated music at the set alarm time, means for identifying the user's current location, means for setting music parameters for the music generation AI from the terminal, means for transmitting the generated music data to the terminal, and means for saving the generated music data in local storage. This allows the user to wake up every day to fresh music that matches the weather, providing a pleasant awakening.

[0561] "Weather information" refers to meteorological data provided based on the user's current location, including weather conditions, temperature, humidity, and the like.

[0562] "Music generation AI" refers to algorithms or software that automatically generate music based on input parameters.

[0563] An "alarm sound" is an acoustic signal that wakes the user up at a set time, and in this system, generated music is used.

[0564] A "server" is a computer device that manages the overall processing of the system, such as obtaining weather information, initializing the music generation AI, and transmitting music data.

[0565] A "terminal" refers to an electronic device owned by a user, and in this system it mainly refers to a smartphone or the like.

[0566] "Current location" refers to the geographical location information of the user, which is determined using GPS or the like.

[0567] "Music parameters" are specific input data used to specify musical characteristics and conditions for music generation AI.

[0568] "Local storage" refers to a memory area provided within a terminal where music data and the like are stored.

[0569] An "HTTP request" is a protocol for sending data to a web server and is widely used as a means of communication.

[0570] The AI ​​Composition Alarm System of this invention aims to allow users to wake up to different music every morning by generating new music based on weather information. This prevents users from becoming accustomed to traditional alarm sounds and provides a pleasant wake-up experience.

[0571] The system consists of the following main elements:

[0572] Server Roles

[0573] The server sends an HTTP request to the user's device at a specified time each day (e.g., 6:00 AM) to notify the user of an "alarm setting request." The server also initializes the music generation AI based on weather information and sets music parameters. This music generation AI generates music with an appropriate melody and tempo according to specific weather conditions, such as sunny or rainy weather. The generated music data is saved in MP3 or WAV format and sent to the device.

[0574] Device Role

[0575] The device receives an alarm setting request from the server and uses GPS to identify the user's current location. It then sends a request to the weather information API to obtain current weather information for that location. It then sends the obtained weather information to the server and receives music data generated by the server. The received music data is saved in local storage and played at the alarm time.

[0576] User operations

[0577] Users wake up to new music every morning. When the set alarm sounds, users wake up to pleasant music and press the alarm stop button on their device to turn off the alarm.

[0578] Hardware and software used

[0579] Server: Virtual server on a cloud platform (e.g. AWS EC2)

[0580] Device: A smartphone owned by the user (e.g., an Android device)

[0581] Weather information API: Weather information provision service (e.g. OpenWeatherMap API)

[0582] Music generation AI: Automatic composition algorithms (e.g., OpenAI's music generation model)

[0583] Specific examples

[0584] Let's assume that User A wants to wake up at 7:00 AM every day. The server sends an "alarm setting request" to User A's device at 6:00 AM. The device receives the request and uses GPS to identify User A's current location. For example, it may identify it as "Shinjuku Ward, Tokyo." Based on this location, the device accesses a weather information API and obtains weather information such as "sunny, temperature 15 degrees." When the device sends this weather information to the server, the server instructs the music generation AI to generate "an upbeat song suitable for a sunny day." The generated music is sent to the device as an up-tempo acoustic guitar piece. The device stores this music in local storage and plays it at 7:00 AM, the alarm time. User A wakes up to upbeat music, allowing them to start their day feeling refreshed.

[0585] Prompt Sentence Examples

[0586] "Generate a bright, uptempo acoustic guitar song to welcome a new morning. The current weather is sunny and the temperature is 15 degrees."

[0587] This system allows users to wake up to new music every day, preventing them from becoming accustomed to the same music and providing a pleasant awakening. It also generates music based on weather information, helping users wake up to music that suits the conditions of the day.

[0588] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0589] Step 1:

[0590] The server sends an "alarm setting request" via HTTP request to the user's device at the specified time of 6:00 AM every day.

[0591] What happens: The server uses a scheduler (e.g., a Cron job) to send an HTTP request to a specific endpoint at a specified time.

[0592] Input: Time (e.g. 6:00 AM)

[0593] Output: HTTP request (alarm setting request)

[0594] Step 2:

[0595] The terminal receives an alarm setting request from the server and identifies the user's current location using GPS.

[0596] Specific operation: The device analyzes the received request and activates the GPS function to obtain the current location information.

[0597] Input: HTTP request (alarm setting request)

[0598] Output: Current location (e.g. Shinjuku-ku, Tokyo)

[0599] Step 3:

[0600] The device sends a request to the weather information API to obtain current weather information.

[0601] Specific operation: The device uses the identified location information to send an API request to a weather information service to obtain weather data.

[0602] Input: Current location (e.g. Shinjuku-ku, Tokyo)

[0603] Output: Weather information (e.g. sunny, temperature 15 degrees)

[0604] Step 4:

[0605] The terminal sends the acquired weather information to the server as an HTTP request.

[0606] Specific operation: The device formats the acquired weather information and sends it to the server via an HTTP request.

[0607] Input: Weather information (e.g. sunny, temperature 15 degrees)

[0608] Output: HTTP request (weather information)

[0609] Step 5:

[0610] The server receives weather information sent from the device and initializes the music generation AI based on that information.

[0611] How it works: The server analyzes the received weather information and generates prompts for the music generation AI to set specific music parameters, for example, a bright melody and a fast tempo on a sunny day.

[0612] Input: HTTP request (weather information)

[0613] Output: Prompt sentence (e.g., upbeat melody, fast tempo)

[0614] Step 6:

[0615] The server generates new music using music generation AI and stores the generated music data.

[0616] Specific operation: The music generation AI receives a prompt, generates new music, and saves it as an MP3 or WAV file.

[0617] Input: prompt statement

[0618] Output: Music data (MP3 or WAV format)

[0619] Step 7:

[0620] The server transmits the generated music data to the terminal in an HTTP response.

[0621] Specific operation: The server encodes the generated music file and sends it back to the device in an HTTP response.

[0622] Input: Music data (MP3 or WAV format)

[0623] Output: URL of HTTP response (music data)

[0624] Step 8:

[0625] The terminal receives the music data sent from the server and stores it in local storage.

[0626] Specific operation: The device obtains the URL of the music file from the HTTP response, downloads it, and saves it to local storage.

[0627] Input: HTTP response (music data URL)

[0628] Output: Music file (saved to local storage)

[0629] Step 9:

[0630] The terminal sets the received music file as an alarm sound and plays it at the alarm time.

[0631] Specific behavior: The device uses the alarm management function to set a new music file as the alarm sound, and plays the saved music when the alarm time arrives.

[0632] Input: Music file (stored in local storage)

[0633] Output: Alarm sound (playback of music file)

[0634] Step 10:

[0635] The user wakes up to the alarm sound and presses the alarm stop button on the terminal to cancel the alarm.

[0636] Specific actions: The user taps the device's operation panel to stop the alarm and start their day.

[0637] Input: Alarm sound (playing a music file)

[0638] Output: Stop alarm

[0639] (Application example 1)

[0640] 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."

[0641] With conventional alarm systems, users often become accustomed to a certain set of music or sounds, resulting in poor awakening. Furthermore, the music that provides a comfortable wake-up experience for a user depends on the individual's situation and environment, so general alarm sounds have limitations. While there is a particular need to improve the quality of wake-ups based on external environmental factors such as weather and temperature, there has been a lack of means to achieve this. Another problem is that music generation is not optimized based on individual user preferences or wake-up data.

[0642] 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.

[0643] In this invention, the server includes means for acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information, means for setting the generated music as an alarm sound, means for playing the generated music at the set alarm time, means for setting parameters for the generated music based on the weather information, means for identifying the user's current location, and means for generating prompts for the music generation AI and generating music based on the prompts. This allows fresh music that is appropriate for the weather and environment to be automatically generated every morning, allowing the user to wake up comfortably and efficiently. Furthermore, the music generation can be adaptively optimized using the user's wake-up data, providing a consistently comfortable wake-up experience.

[0644] "Weather information" is data relating to weather conditions such as current weather conditions, temperature, humidity, rainfall, and wind speed.

[0645] "Music generation AI" is a system that uses artificial intelligence to automatically create new music.

[0646] An "alarm sound" is the music or sound that is played at the alarm time.

[0647] The "current location" is the geographical location information of the physical location of the user's terminal.

[0648] A "prompt" is an instruction or input given to an AI system based on specific conditions or needs.

[0649] "Music parameters" are control elements such as melody, tempo, rhythm, and volume that are used when generating music.

[0650] A "generative AI model" is a system that uses artificial intelligence algorithms to create new content and information.

[0651] "Local storage" refers to a data storage area attached to a user's device.

[0652] An "alarm" is a function that operates at a set time to notify the user.

[0653] "Adaptive optimization" is the process of incrementally improving a system's performance and results based on historical data and user input.

[0654] This invention is an "AI Composition Alarm System" that allows users to wake up comfortably with different music every morning. This system generates new music based on weather information and uses it as an alarm sound. Below, we will explain in detail how to implement this system.

[0655] System configuration

[0656] The system mainly consists of the following components:

[0657] server

[0658] How to get weather information

[0659] A method for generating new music using music generation AI based on acquired weather information

[0660] A means of generating prompts for a music generation AI and generating music based on the prompts

[0661] Terminal

[0662] A means of determining the user's current location

[0663] A means of accessing the weather information API and obtaining weather information

[0664] A means of storing music data received from a server in local storage

[0665] A way to play the generated music at the alarm time

[0666] User

[0667] Set an alarm through your device to wake you up every morning

[0668] Hardware and Software Configuration

[0669] Hardware

[0670] Mobile devices such as smartphones and smart glasses

[0671] server

[0672] GPS Modules

[0673] software

[0674] requests: A library for sending HTTP requests

[0675] geopy: a library for obtaining geolocation information

[0676] pydub: A library for manipulating music files

[0677] playsound: a library for playing music

[0678] Weather information API (e.g. OpenWeatherMap)

[0679] Program processing overview

[0680] Server Processing

[0681] The server sends a request to set an alarm to the user's device at a specified time (e.g., 6:00 AM). This request is made using an HTTP request. The server then initializes the music generation AI based on weather information and generates new music based on the specified parameters. The generated music data is saved in MP3 or WAV format and sent to the user's device using an HTTP response.

[0682] Terminal handling

[0683] The device identifies the user's current location in response to a request from the server, accesses the weather information API to obtain weather information, sends the obtained weather information to the server, and saves the music data sent from the server in local storage.The device then plays the music generated at the alarm time.

[0684] Specific examples

[0685] If user A wants to wake up at 7:00 am every day, the following happens:

[0686] 1. The server sends an "alarm setting request" to User A's device at 6:00 AM.

[0687] 2. The device receives the request and uses GPS to identify the current location of User A. For example, it identifies the location as "Shinjuku-ku, Tokyo."

[0688] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[0689] 4. The device sends this weather information to the server.

[0690] 5. The server receives weather information and instructs the music generation AI to create a "cheerful song suitable for sunny days."

[0691] 6. The server sends the generated music data to the device. For example, an up-tempo acoustic guitar song is generated.

[0692] 7. The device saves the music data to local storage and sets the alarm time to 7:00.

[0693] 8. At 7:00, the alarm time, the device plays music and User A wakes up to cheerful music.

[0694] 9. User A stops the alarm, giving them a comfortable start to their day.

[0695] Prompt Sentence Examples

[0696] Examples of prompts include:

[0697] "I'd like a song with a bright, lively melody line for sunny days. Please create an up-tempo song that will start the morning off on a pleasant note."

[0698] As described above, this system allows users to wake up to fresh music every morning, and also allows them to start their day off right with the optimal alarm sound depending on the weather and environment.

[0699] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0700] Step 1:

[0701] The server sends a request to set an alarm to the user's device at a specific time every day (e.g., 6:00 AM). This request is made via an HTTP request, and the message contains an "alarm setting request." The sent HTTP request is the input, and the arrival of the request data on the user's device is the output.

[0702] Step 2:

[0703] The device receives an alarm setting request from the server. It then uses the GPS module to determine the user's current location. Specifically, the device uses GPS to obtain longitude and latitude information and uses this as location information. The input is the request data from the server, and the output is the obtained location information.

[0704] Step 3:

[0705] The device sends a request to the weather information API based on its location information to obtain current weather information. The obtained weather information includes weather conditions, temperature, humidity, etc. Specifically, an HTTP request is sent to the API, and weather data is returned as a response. The input is location information, and the output is weather information.

[0706] Step 4:

[0707] The device sends the weather information it has acquired to the server. The weather information is essential because the server generates music based on this information. The weather information sent by the device is the input, and the server's receipt of it is the output.

[0708] Step 5:

[0709] The server initializes the music generation AI based on the received weather information and sets the music generation parameters. For example, if it's sunny, it sets a bright melody and a fast tempo. New music is then generated based on the set parameters. The input is the weather information and music generation parameters, and the output is the generated music data.

[0710] Step 6:

[0711] The server sends the generated music data to the user's device as an HTTP response. This generated music is saved in MP3 or WAV format. The input is the generated music data, and the output is the music data being sent to the user's device.

[0712] Step 7:

[0713] The device receives music data sent from the server and saves it in local storage. The saved music data is set as an alarm sound. The input is the music data received from the server, and the output is saving the music data to local storage.

[0714] Step 8:

[0715] The device sets the stored music data as an alarm sound and plays it at the alarm time. When the alarm time arrives, the music plays and the user wakes up. The input is the music data stored in local storage and the alarm time, and the output is the music playing and the user waking up.

[0716] These steps allow the user to wake up pleasantly to new music every morning.

[0717] 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.

[0718] The "AI Composition Alarm System" of this invention aims to allow users to wake up to different music every morning, and has the ability to generate new music based on weather information and the user's emotional information. This prevents users from becoming accustomed to the alarm sound and provides a comfortable awakening. Furthermore, by taking the user's emotions into consideration, the system further promotes a pleasant awakening.

[0719] overview

[0720] The system consists of a means for acquiring weather information, an emotion engine that recognizes the user's emotions, a means for generating new music using music generation AI, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. Furthermore, it also includes a means for identifying the user's current location when acquiring weather information.

[0721] Program processing

[0722] Server Processing

[0723] Step 1: The server sends an alarm setting request to the device every day at a specific time (e.g., 6:00 AM). This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[0724] Step 2: When the user's emotional information is sent, the server receives it and initializes the music generation AI. The emotional information is obtained from an emotion engine that analyzes the user's emotions using, for example, a camera or microphone.

[0725] Step 3: The server sets music parameters based on the received weather information and the user's emotional information. Further fine-tuning is performed based on the emotional information, such as bright and cheerful music for sunny days and relaxing music for rainy days.

[0726] Step 4: The AI ​​generates new music based on the parameters you set, which can then be saved in MP3 or WAV format, for example.

[0727] Step 5: The server sends the generated music data to the device, also using an HTTP response.

[0728] Terminal handling

[0729] Step 1: The device receives the alarm setting request from the server and uses GPS to determine the user's current location. Specifically, it calls the device's location service to obtain the latitude and longitude.

[0730] Step 2: The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to get weather information for the target area. This request includes latitude and longitude parameters.

[0731] Step 3: The device receives weather information from the weather information API, including the weather condition (sunny, rainy, etc.) and temperature.

[0732] Step 4: The device sends the acquired weather information and emotion data from the user's emotion engine to the server. The emotion engine analyzes the user's current emotion using the camera and microphone.

[0733] Step 5: The device receives the music data sent from the server and stores it in its local storage.

[0734] Step 6: The device uses the received music data to set an alarm, and the music will be played at the set time through the alarm application.

[0735] Step 7: At the set alarm time, the device will play the music data stored on it, allowing the user to wake up to new music.

[0736] Specific examples

[0737] Assume that user B wants to wake up at 7:00 AM every day.

[0738] 1. The server sends an "alarm setting request" to User B's device at 6:00 AM.

[0739] 2. The device receives the request and uses GPS to identify the current location of User B. For example, it identifies the location as "Chuo-ku, Osaka City."

[0740] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 20 degrees."

[0741] 4. The device uses the emotion engine to analyze User B's emotions and determine, for example, that he is "relaxed."

[0742] 5. The device combines weather information and emotion information and sends it to the server.

[0743] 6. The server receives weather information and emotional information and has the music generation AI create a "relaxing song suitable for a sunny day."

[0744] 7. The server sends the generated music data to the device. For example, a slow, relaxing acoustic guitar song is generated.

[0745] 8. The device saves the music data to local storage and sets the alarm time to 7:00.

[0746] 9. At 7:00, the alarm time, the device plays music and User B wakes up to relaxing music.

[0747] 10. User B turns off the alarm and starts the day in a relaxed state.

[0748] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up tailored to their individual condition.

[0749] The processing flow will be explained below.

[0750] Step 1:

[0751] The server sends an alarm setting request to the user's device every day at a specific time (e.g., 6:00 a.m.) This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[0752] Step 2:

[0753] The terminal receives an alarm setting request from the server, which causes the terminal to start the alarm setting process.

[0754] Step 3:

[0755] The device uses GPS to determine the user's current location. Specifically, it calls the device's location information service to obtain the latitude and longitude.

[0756] Step 4:

[0757] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to obtain weather information for the target area. This request includes latitude and longitude parameters.

[0758] Step 5:

[0759] The device receives weather information from the weather information API, including weather conditions (sunny, rainy, etc.) and temperature.

[0760] Step 6:

[0761] The device uses the built-in camera and microphone to acquire data to recognize emotions from the user's face and voice, and this processing is carried out by the emotion engine.

[0762] Step 7:

[0763] The device identifies the user's emotional state (e.g., relaxed, stressed, etc.) based on analysis by the emotion engine.

[0764] Step 8:

[0765] The weather information and emotion information acquired by the device are sent to the server. Weather information and emotion data are sent to the server using the HTTP protocol.

[0766] Step 9:

[0767] The server receives weather and emotion information sent from the device and initializes the music generation AI based on this information.

[0768] Step 10:

[0769] The server sets music parameters based on weather information and emotional information. For example, if the weather is "sunny" and the user is "relaxed," the tempo is slowed down and relaxing instruments (e.g., acoustic guitar or piano) are used.

[0770] Step 11:

[0771] The server passes the set parameters to the music generation AI to generate new music. In this process, the AI ​​automatically creates music based on the specified parameters.

[0772] Step 12:

[0773] The server receives the generated music data and saves it in MP3 or WAV format.

[0774] Step 13:

[0775] The server sends the generated music data to the terminal using an HTTP response.

[0776] Step 14:

[0777] The device receives the music data sent from the server and stores it in local storage.

[0778] Step 15:

[0779] Set an alarm using the music data received by the device, and use the alarm application to play the music at the set time.

[0780] Step 16:

[0781] The device will play the stored music data at the set alarm time, allowing the user to wake up to new music.

[0782] Step 17:

[0783] The user wakes up to the sound of the alarm and can optionally dismiss the alarm or use the snooze function to set the alarm again.

[0784] Specific examples

[0785] Assume that user B wants to wake up at 7:00 AM every day.

[0786] 1. The server sends an "alarm setting request" to User B's device at 6:00 AM.

[0787] 2. The device receives the request and uses GPS to identify the current location of User B. For example, it identifies that it is in Shinjuku Ward, Tokyo.

[0788] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[0789] 4. The device uses the emotion engine to analyze User B's emotions and determine, for example, that he is "relaxed."

[0790] 5. The device combines weather information and emotion information and sends it to the server.

[0791] 6. The server receives weather information and emotional information and has the music generation AI create a "relaxing song suitable for a sunny day."

[0792] 7. The server sends the generated music data to the device. For example, a slow, relaxing acoustic guitar song is generated.

[0793] 8. The device saves the music data to local storage and sets the alarm time to 7:00.

[0794] 9. At 7:00, the alarm time, the device plays music and User B wakes up to relaxing music.

[0795] 10. User B turns off the alarm and starts the day in a relaxed state.

[0796] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up tailored to their individual condition.

[0797] Example 2

[0798] 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."

[0799] With conventional alarm systems, users become accustomed to the same alarm sound, making it difficult to wake up effectively. Furthermore, there was a lack of technology to generate alarm sounds that took into account not only weather information but also the user's emotional information, making it impossible to provide a comfortable waking experience tailored to each individual user.

[0800] 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.

[0801] In this invention, the server includes means for acquiring weather information, means for acquiring a user's emotions using an emotion engine that recognizes the user's emotions, and means for generating new music using a music generation AI model based on the acquired weather information and user's emotion information. This allows new music that is optimal for each individual user to be generated every day, providing a pleasant awakening.

[0802] "Weather information" is a general term for relevant meteorological data such as current weather conditions, temperature, and humidity.

[0803] An "emotion engine" is software or hardware that analyzes a user's facial expressions, tone of voice, etc., to recognize the user's emotional state.

[0804] A "music generation AI model" is an artificial intelligence model that automatically generates new music based on specified parameters.

[0805] An "alarm sound" is an audio signal that is set to wake the user up.

[0806] "Current Location" means the user's actual geographic location as determined using GPS or other location technology.

[0807] The purpose of the "AI Composition Alarm System" of this invention is to allow users to wake up to different music every morning. Specifically, it generates new music based on weather information and the user's emotional state, and sets it as the alarm sound, preventing users from becoming accustomed to the alarm sound and providing a pleasant awakening. Furthermore, by taking the user's emotions into consideration, it further promotes a pleasant awakening.

[0808] System Components

[0809] The system includes the following components:

[0810] 1. How to get weather information:

[0811] Specifically, current weather information is obtained using a weather information API (e.g., OpenWeatherMap).

[0812] 2. Emotion engine that recognizes user emotions:

[0813] It includes hardware and software for analyzing the user's facial expressions and tone of voice to recognize their current emotional state.

[0814] 3. Music generation AI model:

[0815] Includes artificial intelligence models (e.g., GPT-3-based generative AI) that automatically generate new music based on specified parameters.

[0816] 4. How to set the generated music as an alarm sound:

[0817] Save the music data to the device's local storage and set it as the alarm sound through the alarm application.

[0818] 5. How to play the generated music at the alarm time:

[0819] It includes software and hardware for playing an alarm sound at a set time.

[0820] 6. How to determine the user's current location:

[0821] The user's current location is determined using location information services such as GPS.

[0822] Specific operation of the system

[0823] 1. Server operation:

[0824] The server sends an alarm setting request to the user's terminal at a specified time every day using the HTTP protocol.

[0825] The server receives weather information and user emotional information sent from the device and initializes the music generation AI model based on that information.

[0826] The music generation AI model is given a prompt like this to generate music:

[0827] "The user is feeling relaxed today. The current weather is sunny and the temperature is 20 degrees. Based on these conditions, generate a relaxing acoustic guitar song."

[0828] The generated music data is sent to the terminal in MP3 or WAV format.

[0829] 2. Device behavior:

[0830] The device receives an alarm setting request from the server and uses the GPS function to determine the current location.

[0831] Based on the identified current location, a request is sent to the weather information API to obtain weather information.

[0832] The device uses a camera and microphone to analyze the user's emotions with an emotion engine, and transmits the obtained emotion information to the server.

[0833] The terminal receives the music data sent from the server and stores it in local storage.

[0834] Use the Alarms application to set an alarm to play music at a specified time.

[0835] It plays music at a set time to wake the user up.

[0836] Hardware and software used

[0837] Server: Servers operated in data centers with high-performance processors (e.g., cloud infrastructure)

[0838] Device: Smartphone with GPS function, camera and microphone (e.g. smart device)

[0839] Weather Information API: Web API that provides weather information (e.g., OpenWeatherMap)

[0840] Music generation AI model: An artificial intelligence model that generates music based on specified parameters (e.g., GPT-3)

[0841] Location services: Standard GPS function of the device

[0842] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up in a way that suits their individual condition.

[0843] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0844] Step 1:

[0845] The server sends an "alarm setting request" to the user's device as an HTTP request every day at 6:00 AM. This request contains information for setting the alarm. The input is the server's scheduled time, and the output is the request sent to the user's device.

[0846] Step 2:

[0847] The device receives the alarm setting request from the server and uses the location information service to determine the current location. Specifically, it calls the device's GPS function to obtain latitude and longitude data. This location information is used as input, and the output is to save the location information in the device's internal memory.

[0848] Step 3:

[0849] The device sends a request to the weather information API based on the identified current location. The request includes latitude and longitude parameters. The input is location data, and the output is a request to the weather information API.

[0850] Step 4:

[0851] Receives a response from the weather information API and analyzes its contents. Specifically, it obtains data such as the current weather conditions and temperature. The input is the response data from the API, and the output is the analyzed weather information.

[0852] Step 5:

[0853] The device uses a camera and microphone to capture the user's facial expressions and voice, which are then analyzed by the emotion engine. The emotion engine then determines the user's emotional state based on this data. The input is the user's facial expressions and voice data, and the output is the determined emotional information.

[0854] Step 6:

[0855] The device sends the acquired weather information and emotion information to the server. Specifically, it uses an HTTP POST request and includes the header "Content-Type: application / json". The input is weather information and emotion information, and the output is data sent to the server.

[0856] Step 7:

[0857] The server receives weather information and emotion information sent from the device. Based on this data, it creates a prompt sentence to input into the music generation AI model. The input is weather information and emotion information, and the output is the generation of a prompt sentence. Specifically, it generates a sentence such as, "The user is feeling relaxed today. The current weather is sunny, and the temperature is 20 degrees. Based on these conditions, please generate a relaxing acoustic guitar song."

[0858] Step 8:

[0859] The music generation AI model generates new music based on a created prompt. The input is the prompt, and the output is the generated music data. Specifically, music files are generated in MP3 or WAV format.

[0860] Step 9:

[0861] The server sends the generated music data to the terminal. This is done using HTTP responses. The input is the music data, and the output is data sent to the user's terminal.

[0862] Step 10:

[0863] The device saves the received music data in local storage. The save destination is, for example, a directory called " / storage / emulated / 0 / Alarms / ". The input is music data, and the output is saved to local storage.

[0864] Step 11:

[0865] The device sets an alarm using stored music data. Using the alarm management application API, music is played at the set time (e.g., 7:00 AM). The input is the music data and the set time, and the output is the alarm setting.

[0866] Step 12:

[0867] At the set time, the device will play music to wake the user up. The input is setting the alarm and the output is playing music. The user can wake up comfortably to new music.

[0868] (Application example 2)

[0869] 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."

[0870] Conventional alarm systems wake users up with the same sound every time, which can lead to users becoming accustomed to the alarm sound and making it difficult to wake up. Furthermore, background music in stores tends to be fixed, and music is played without taking into account the emotions of customers and employees or external weather information, making it difficult to maximize the store atmosphere and customer experience.

[0871] 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 acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information and emotional information, means for setting the generated music as an alarm sound or background music for the store, means for playing the generated music at the set alarm time or in real time, and means for acquiring emotional information of customers and employees. This makes it possible to generate appropriate music according to the emotional state of the user or customer and the weather information, allowing for a comfortable awakening and providing an optimal store atmosphere.

[0872] "Weather information" refers to current and near-future weather conditions and meteorological data such as temperature, precipitation, and wind speed.

[0873] "Emotion information" is data that represents the psychological state or emotions of a user or customer, and is classified into emotion categories such as "happy," "relaxed," and "excited."

[0874] "Music generation AI" is an artificial intelligence system that automatically generates new music by setting parameters based on weather information and emotional information.

[0875] An "alarm sound" is music or sound that is played to wake the user up at a specified time.

[0876] "BGM" is an abbreviation for background music, and refers to the background music played in indoor spaces such as stores and commercial facilities.

[0877] A "server" is a computing device that provides specific services and data processing over a network and serves client devices.

[0878] "Device" refers to a hardware device that collects user or customer emotions and weather information and plays generated music. Examples include smartphones, smart glasses, head-mounted displays, and robots.

[0879] "Location information" is data that indicates the current geographical location of a user or a store and is expressed in the form of latitude and longitude.

[0880] A "weather information API" is an application programming interface that provides weather information over the web and is a means for obtaining weather data.

[0881] An "emotion analysis engine" is software that analyzes data obtained from input devices such as cameras and microphones and identifies the emotional state of users or customers.

[0882] "HTTP protocol" is an abbreviation for Hypertext Transfer Protocol, an Internet protocol for data communication.

[0883] "Music parameters" are set values ​​that determine the characteristics of music, and include tempo, key, instrument composition, and the like.

[0884] This invention is a system that uses music generation AI to generate new music based on weather information and emotional information, and plays it as an alarm sound or background music in a physical store. Specifically, it is implemented using a server and a terminal.

[0885] System configuration

[0886] The system consists of the following main components:

[0887] Weather information acquisition means: Uses a weather information API (e.g., OpenWeatherMap) to acquire weather data based on the terminal's current location.

[0888] Emotion information acquisition means: An emotion analysis engine that uses cameras and microphones to analyze the emotional state of users, store customers, and employees.

[0889] Music generation method: Based on the weather and emotional information, the music generation AI generates new music. The generated music is saved in MP3 or WAV format.

[0890] Alarm / BGM setting method: The generated music is set as an alarm sound or background music in the store. Devices such as smartphones, smart glasses, head-mounted displays, and robots are used.

[0891] Playback method: Play the generated music at a specified time or in real time.

[0892] Server Processing

[0893] The server has the following functions:

[0894] Sending an alarm setting request: Send an alarm setting request to the client device at a specific time every day (e.g., 10:00 a.m.), which wakes up the user or store's system and collects the appropriate data.

[0895] Music generation: Music parameters are set based on received weather and emotional information, and new music is generated using music generation AI.

[0896] Sending music data: The generated music data is sent to the device so that it can be used as an alarm sound or background music.

[0897] Terminal handling

[0898] The main processing of the terminal is as follows:

[0899] Obtaining location information: Use GPS to determine current location information, and send it to a weather information API to obtain weather information for the target area.

[0900] Acquiring emotional information: Emotional information of users and customers is acquired using a camera or microphone and sent to the server.

[0901] Receiving and storing music data: Receives music data sent from the server and stores it in local storage.

[0902] Setting and playing alarms and background music: Set the generated music as an alarm sound or background music and play it at a specified time or in real time.

[0903] Examples of specific examples and prompts

[0904] The actual usage scenario is described below.

[0905] Specific examples

[0906] The flow when Store A starts the system at 10:00 in the morning while preparing to open is as follows.

[0907] 1. The server sends a "BGM setting request" to the terminal at store A.

[0908] 2. The device receives the request and uses GPS to determine its current location. For example, it may determine that it is in Shibuya Ward, Tokyo.

[0909] 3. The device accesses the weather information API and obtains weather information for Shibuya Ward, Tokyo. For example, it obtains weather information such as "sunny, temperature 25 degrees."

[0910] 4. The emotion analysis engine analyzes the employee's emotions and determines that they are "energetic and cheerful."

[0911] 5. The device sends weather information and emotion information to the server.

[0912] 6. The server asks the music generation AI to create a "lively and cheerful song suitable for a sunny day."

[0913] 7. The server sends the generated music data to the device. For example, lively pop music is generated.

[0914] 8. The device stores the music data locally and then plays it on the store's sound system.

[0915] 9. The music in the store creates a lively and cheerful atmosphere, making customers feel comfortable.

[0916] Prompt Sentence Examples

[0917] Weather: Sunny, 25 degrees

[0918] Emotional information: Lively and cheerful

[0919] Generated Music Style: Pop

[0920] Generated music tempo: Fast

[0921] In this way, appropriate music is generated according to the emotional state of the user or customer and weather information, thereby providing a pleasant awakening and an optimal store atmosphere.

[0922] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0923] Step 1:

[0924] The server sends an alarm setting request to the client device at a specific time every day (e.g., 10:00 a.m.). This request is sent using the HTTP protocol and contains the message "Request to set alarm." The input is the specified time, and the output is the alarm setting request message.

[0925] Step 2:

[0926] The device receives an alarm setting request from the server and uses GPS to determine the current location. The input is the alarm setting request message, and the output is the current location information (latitude and longitude). Specifically, the device's location information service is called to obtain the latitude and longitude.

[0927] Step 3:

[0928] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location information to obtain weather information for the target area. This request includes latitude and longitude parameters. The input is the current location information, and the output is weather information.

[0929] Step 4:

[0930] The device receives weather information from the weather information API. This information includes the weather condition (sunny, rainy, etc.) and temperature. The input is the response from the weather information API, and the output is the specific weather information.

[0931] Step 5:

[0932] The device uses a camera and microphone to obtain emotional information from the user or customer through an emotion analysis engine. The input is data from the camera or microphone, and the output is analyzed emotional information. Specifically, facial expression analysis and voice analysis technologies are used.

[0933] Step 6:

[0934] The device combines the acquired weather information and emotion information and sends it to the server. The input is weather information and emotion information, and the output is request data to the server. Specifically, the weather information and emotion information are sent to the server as parameters using the HTTP protocol.

[0935] Step 7:

[0936] The server initializes the music generation AI and sets the music parameters based on the received weather and emotional information. Further fine-tuning is made based on emotional information, such as bright and cheerful music for sunny days and relaxing music for rainy days. The input is weather information and emotional information, and the output is the set music parameters.

[0937] Step 8:

[0938] The server generates new music based on the set parameters using music generation AI. This music is saved in MP3 or WAV format, for example. The input is the music parameters, and the output is the generated music data. Specifically, the AI ​​model generates music by inputting prompts.

[0939] Step 9:

[0940] The server sends the generated music data to the device. This is also done using HTTP responses. The input is the generated music data, and the output is the transmission of the music data to the device.

[0941] Step 10:

[0942] The device receives the music data sent from the server and stores it in local storage. The input is music data, and the output is storage in local storage.

[0943] Step 11:

[0944] The device uses the received music data to set alarms and background music for the store. Music is played at the set time or in real time through an alarm application or sound system. The input is music data, and the output is alarm and background music settings. Specifically, this includes scheduler functions and sound system settings.

[0945] Step 12:

[0946] The device plays music data stored on it at the set alarm time or in real time. This allows users to wake up to new music or enjoy appropriate background music in the store. The input is the set timing, and the output is music playback.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] [Third embodiment]

[0951] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0952] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0953] 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).

[0954] 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.

[0955] 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.

[0956] 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).

[0957] 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.

[0958] 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.

[0959] 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.

[0960] 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.

[0961] 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.

[0962] 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."

[0963] The AI ​​Composition Alarm System of this invention aims to allow users to wake up to different music every morning, and has the ability to generate new music based on weather information. This prevents users from becoming accustomed to traditional alarm sounds, and provides a pleasant wake-up experience.

[0964] overview

[0965] The system consists of a means for acquiring weather information, a means for generating new music using music generation AI, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. Furthermore, when acquiring weather information, the system also includes a means for identifying the user's current location.

[0966] Program processing

[0967] Server Processing

[0968] Step 1: The server sends an alarm setting request to the device every day at a specific time (e.g., 6:00 AM). This request is made via an HTTP request, and the message contains an "alarm setting request."

[0969] Step 2: The server initializes the music generation AI based on the weather information. It sets the music parameters to be passed to the AI ​​based on the received weather information. For example, if it is sunny, it sets a bright melody and a fast tempo.

[0970] Step 3: The AI ​​generates new music based on the parameters you set, and the music is saved in MP3 or WAV format.

[0971] Step 4: The server sends the generated music data to the device, also using an HTTP response.

[0972] Terminal handling

[0973] Step 1: The device receives an alarm setting request from the server and uses GPS to determine the user's current location.

[0974] Step 2: The device sends a request to the weather information API to obtain current weather information, including weather conditions and temperature.

[0975] Step 3: The device sends the weather information to the server, which then generates music based on this information.

[0976] Step 4: The device receives the music data sent from the server and stores it in its local storage.

[0977] Step 5: The device will set the received music as the alarm sound and play it at the alarm time.

[0978] Specific examples

[0979] Assume that user A wants to wake up at 7:00 am every day.

[0980] 1. The server sends an "alarm setting request" to User A's device at 6:00 AM.

[0981] 2. The device receives the request and uses GPS to identify the current location of User A. For example, it identifies the location as "Shinjuku-ku, Tokyo."

[0982] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[0983] 4. The device sends this weather information to the server.

[0984] 5. The server receives weather information and instructs the music generation AI to create a "cheerful song suitable for sunny days."

[0985] 6. The server sends the generated music data to the device. For example, an up-tempo acoustic guitar song is generated.

[0986] 7. The device saves the music data to local storage and sets the alarm time to 7:00.

[0987] 8. At 7:00, the alarm time, the device plays music and User A wakes up to cheerful music.

[0988] 9. User A stops the alarm, giving them a comfortable start to their day.

[0989] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to habituation to the same sounds. It also uses weather-appropriate music to wake users up according to their conditions that day.

[0990] The processing flow will be explained below.

[0991] Step 1:

[0992] The server checks its internal clock and sends an alarm setting request to the user's device at a specific time each day (e.g., 6:00 a.m.). This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[0993] Step 2:

[0994] The terminal receives an alarm setting request from the server, which causes the terminal to start the alarm setting process.

[0995] Step 3:

[0996] The device uses GPS to determine the user's current location. Specifically, it calls the device's location information service to obtain the latitude and longitude.

[0997] Step 4:

[0998] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to obtain weather information for the target area. This request includes latitude and longitude parameters.

[0999] Step 5:

[1000] The device receives weather information from the weather information API, including weather conditions (sunny, rainy, etc.) and temperature.

[1001] Step 6:

[1002] The weather information acquired by the device is sent to the server. Data including the weather information is sent to the server using the HTTP protocol.

[1003] Step 7:

[1004] The server receives weather information sent from the device and initializes the music generation AI based on this information.

[1005] Step 8:

[1006] The server sets music parameters based on weather information, for example, if it's "sunny," it will set the tempo faster and use bright instruments (e.g., acoustic guitar).

[1007] Step 9:

[1008] The server passes the set parameters to the music generation AI to generate new music. In this process, the AI ​​automatically creates music based on the user's specifications.

[1009] Step 10:

[1010] The server receives the generated music data and saves it in MP3 or WAV format.

[1011] Step 11:

[1012] The server sends the generated music data to the terminal using an HTTP response.

[1013] Step 12:

[1014] The device receives the music data sent from the server and stores it in local storage.

[1015] Step 13:

[1016] Set an alarm using the music data received by your device, and have the music play at the set time through the alarm application.

[1017] Step 14:

[1018] The device will play the stored music data at the set alarm time, allowing the user to wake up to new music.

[1019] Step 15:

[1020] The user wakes up to the sound of the alarm and can optionally dismiss the alarm or use the snooze function to set the alarm again.

[1021] Example 1

[1022] 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."

[1023] Conventional alarm clock devices have the problem that users become accustomed to the same sound every day, which makes it difficult to wake up effectively. In addition, there is no way to provide music that matches the weather or mood, so there is a lack of means for users to start their day more comfortably.

[1024] 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.

[1025] In this invention, the server includes means for acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information, means for setting the generated music as an alarm sound, means for playing the generated music at the set alarm time, means for identifying the user's current location, means for setting music parameters for the music generation AI from the terminal, means for transmitting the generated music data to the terminal, and means for saving the generated music data in local storage. This allows the user to wake up every day to fresh music that matches the weather, providing a pleasant awakening.

[1026] "Weather information" refers to meteorological data provided based on the user's current location, including weather conditions, temperature, humidity, and the like.

[1027] "Music generation AI" refers to algorithms or software that automatically generate music based on input parameters.

[1028] An "alarm sound" is an acoustic signal that wakes the user up at a set time, and in this system, generated music is used.

[1029] A "server" is a computer device that manages the overall processing of the system, such as obtaining weather information, initializing the music generation AI, and transmitting music data.

[1030] A "terminal" refers to an electronic device owned by a user, and in this system it mainly refers to a smartphone or the like.

[1031] "Current location" refers to the geographical location information of the user, which is determined using GPS or the like.

[1032] "Music parameters" are specific input data used to specify musical characteristics and conditions for music generation AI.

[1033] "Local storage" refers to a memory area provided within a terminal where music data and the like are stored.

[1034] An "HTTP request" is a protocol for sending data to a web server and is widely used as a means of communication.

[1035] The AI ​​Composition Alarm System of this invention aims to allow users to wake up to different music every morning by generating new music based on weather information. This prevents users from becoming accustomed to traditional alarm sounds and provides a pleasant wake-up experience.

[1036] The system consists of the following main elements:

[1037] Server Roles

[1038] The server sends an HTTP request to the user's device at a specified time each day (e.g., 6:00 AM) to notify the user of an "alarm setting request." The server also initializes the music generation AI based on weather information and sets music parameters. This music generation AI generates music with an appropriate melody and tempo according to specific weather conditions, such as sunny or rainy weather. The generated music data is saved in MP3 or WAV format and sent to the device.

[1039] Device Role

[1040] The device receives an alarm setting request from the server and uses GPS to identify the user's current location. It then sends a request to the weather information API to obtain current weather information for that location. It then sends the obtained weather information to the server and receives music data generated by the server. The received music data is saved in local storage and played at the alarm time.

[1041] User operations

[1042] Users wake up to new music every morning. When the set alarm sounds, users wake up to pleasant music and press the alarm stop button on their device to turn off the alarm.

[1043] Hardware and software used

[1044] Server: Virtual server on a cloud platform (e.g. AWS EC2)

[1045] Device: A smartphone owned by the user (e.g., an Android device)

[1046] Weather information API: Weather information provision service (e.g. OpenWeatherMap API)

[1047] Music generation AI: Automatic composition algorithms (e.g., OpenAI's music generation model)

[1048] Specific examples

[1049] Let's assume that User A wants to wake up at 7:00 AM every day. The server sends an "alarm setting request" to User A's device at 6:00 AM. The device receives the request and uses GPS to identify User A's current location. For example, it may identify it as "Shinjuku Ward, Tokyo." Based on this location, the device accesses a weather information API and obtains weather information such as "sunny, temperature 15 degrees." When the device sends this weather information to the server, the server instructs the music generation AI to generate "an upbeat song suitable for a sunny day." The generated music is sent to the device as an up-tempo acoustic guitar piece. The device stores this music in local storage and plays it at 7:00 AM, the alarm time. User A wakes up to upbeat music, allowing them to start their day feeling refreshed.

[1050] Prompt Sentence Examples

[1051] "Generate a bright, uptempo acoustic guitar song to welcome a new morning. The current weather is sunny and the temperature is 15 degrees."

[1052] This system allows users to wake up to new music every day, preventing them from becoming accustomed to the same music and providing a pleasant awakening. It also generates music based on weather information, helping users wake up to music that suits the conditions of the day.

[1053] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1054] Step 1:

[1055] The server sends an "alarm setting request" via HTTP request to the user's device at the specified time of 6:00 AM every day.

[1056] What happens: The server uses a scheduler (e.g., a Cron job) to send an HTTP request to a specific endpoint at a specified time.

[1057] Input: Time (e.g. 6:00 AM)

[1058] Output: HTTP request (alarm setting request)

[1059] Step 2:

[1060] The terminal receives an alarm setting request from the server and identifies the user's current location using GPS.

[1061] Specific operation: The device analyzes the received request and activates the GPS function to obtain the current location information.

[1062] Input: HTTP request (alarm setting request)

[1063] Output: Current location (e.g. Shinjuku-ku, Tokyo)

[1064] Step 3:

[1065] The device sends a request to the weather information API to obtain current weather information.

[1066] Specific operation: The device uses the identified location information to send an API request to a weather information service to obtain weather data.

[1067] Input: Current location (e.g. Shinjuku-ku, Tokyo)

[1068] Output: Weather information (e.g. sunny, temperature 15 degrees)

[1069] Step 4:

[1070] The terminal sends the acquired weather information to the server as an HTTP request.

[1071] Specific operation: The device formats the acquired weather information and sends it to the server via an HTTP request.

[1072] Input: Weather information (e.g. sunny, temperature 15 degrees)

[1073] Output: HTTP request (weather information)

[1074] Step 5:

[1075] The server receives weather information sent from the device and initializes the music generation AI based on that information.

[1076] How it works: The server analyzes the received weather information and generates prompts for the music generation AI to set specific music parameters, for example, a bright melody and a fast tempo on a sunny day.

[1077] Input: HTTP request (weather information)

[1078] Output: Prompt sentence (e.g., upbeat melody, fast tempo)

[1079] Step 6:

[1080] The server generates new music using music generation AI and stores the generated music data.

[1081] Specific operation: The music generation AI receives a prompt, generates new music, and saves it as an MP3 or WAV file.

[1082] Input: prompt statement

[1083] Output: Music data (MP3 or WAV format)

[1084] Step 7:

[1085] The server transmits the generated music data to the terminal in an HTTP response.

[1086] Specific operation: The server encodes the generated music file and sends it back to the device in an HTTP response.

[1087] Input: Music data (MP3 or WAV format)

[1088] Output: URL of HTTP response (music data)

[1089] Step 8:

[1090] The terminal receives the music data sent from the server and stores it in local storage.

[1091] Specific operation: The device obtains the URL of the music file from the HTTP response, downloads it, and saves it to local storage.

[1092] Input: HTTP response (music data URL)

[1093] Output: Music file (saved to local storage)

[1094] Step 9:

[1095] The terminal sets the received music file as an alarm sound and plays it at the alarm time.

[1096] Specific behavior: The device uses the alarm management function to set a new music file as the alarm sound, and plays the saved music when the alarm time arrives.

[1097] Input: Music file (stored in local storage)

[1098] Output: Alarm sound (playback of music file)

[1099] Step 10:

[1100] The user wakes up to the alarm sound and presses the alarm stop button on the terminal to cancel the alarm.

[1101] Specific actions: The user taps the device's operation panel to stop the alarm and start their day.

[1102] Input: Alarm sound (playing a music file)

[1103] Output: Stop alarm

[1104] (Application example 1)

[1105] 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."

[1106] With conventional alarm systems, users often become accustomed to a certain set of music or sounds, resulting in poor awakening. Furthermore, the music that provides a comfortable wake-up experience for a user depends on the individual's situation and environment, so general alarm sounds have limitations. While there is a particular need to improve the quality of wake-ups based on external environmental factors such as weather and temperature, there has been a lack of means to achieve this. Another problem is that music generation is not optimized based on individual user preferences or wake-up data.

[1107] 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.

[1108] In this invention, the server includes means for acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information, means for setting the generated music as an alarm sound, means for playing the generated music at the set alarm time, means for setting parameters for the generated music based on the weather information, means for identifying the user's current location, and means for generating prompts for the music generation AI and generating music based on the prompts. This allows fresh music that is appropriate for the weather and environment to be automatically generated every morning, allowing the user to wake up comfortably and efficiently. Furthermore, the music generation can be adaptively optimized using the user's wake-up data, providing a consistently comfortable wake-up experience.

[1109] "Weather information" is data relating to weather conditions such as current weather conditions, temperature, humidity, rainfall, and wind speed.

[1110] "Music generation AI" is a system that uses artificial intelligence to automatically create new music.

[1111] An "alarm sound" is the music or sound that is played at the alarm time.

[1112] The "current location" is the geographical location information of the physical location of the user's terminal.

[1113] A "prompt" is an instruction or input given to an AI system based on specific conditions or needs.

[1114] "Music parameters" are control elements such as melody, tempo, rhythm, and volume that are used when generating music.

[1115] A "generative AI model" is a system that uses artificial intelligence algorithms to create new content and information.

[1116] "Local storage" refers to a data storage area attached to a user's device.

[1117] An "alarm" is a function that operates at a set time to notify the user.

[1118] "Adaptive optimization" is the process of incrementally improving a system's performance and results based on historical data and user input.

[1119] This invention is an "AI Composition Alarm System" that allows users to wake up comfortably with different music every morning. This system generates new music based on weather information and uses it as an alarm sound. Below, we will explain in detail how to implement this system.

[1120] System configuration

[1121] The system mainly consists of the following components:

[1122] server

[1123] How to get weather information

[1124] A method for generating new music using music generation AI based on acquired weather information

[1125] A means of generating prompts for a music generation AI and generating music based on the prompts

[1126] Terminal

[1127] A means of determining the user's current location

[1128] A means of accessing the weather information API and obtaining weather information

[1129] A means of storing music data received from a server in local storage

[1130] A way to play the generated music at the alarm time

[1131] User

[1132] Set an alarm through your device to wake you up every morning

[1133] Hardware and Software Configuration

[1134] Hardware

[1135] Mobile devices such as smartphones and smart glasses

[1136] server

[1137] GPS Modules

[1138] software

[1139] requests: A library for sending HTTP requests

[1140] geopy: a library for obtaining geolocation information

[1141] pydub: A library for manipulating music files

[1142] playsound: a library for playing music

[1143] Weather information API (e.g. OpenWeatherMap)

[1144] Program processing overview

[1145] Server Processing

[1146] The server sends a request to set an alarm to the user's device at a specified time (e.g., 6:00 AM). This request is made using an HTTP request. The server then initializes the music generation AI based on weather information and generates new music based on the specified parameters. The generated music data is saved in MP3 or WAV format and sent to the user's device using an HTTP response.

[1147] Terminal handling

[1148] The device identifies the user's current location in response to a request from the server, accesses the weather information API to obtain weather information, sends the obtained weather information to the server, and saves the music data sent from the server in local storage.The device then plays the music generated at the alarm time.

[1149] Specific examples

[1150] If user A wants to wake up at 7:00 am every day, the following happens:

[1151] 1. The server sends an "alarm setting request" to User A's device at 6:00 AM.

[1152] 2. The device receives the request and uses GPS to identify the current location of User A. For example, it identifies the location as "Shinjuku-ku, Tokyo."

[1153] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[1154] 4. The device sends this weather information to the server.

[1155] 5. The server receives weather information and instructs the music generation AI to create a "cheerful song suitable for sunny days."

[1156] 6. The server sends the generated music data to the device. For example, an up-tempo acoustic guitar song is generated.

[1157] 7. The device saves the music data to local storage and sets the alarm time to 7:00.

[1158] 8. At 7:00, the alarm time, the device plays music and User A wakes up to cheerful music.

[1159] 9. User A stops the alarm, giving them a comfortable start to their day.

[1160] Prompt Sentence Examples

[1161] Examples of prompts include:

[1162] "I'd like a song with a bright, lively melody line for sunny days. Please create an up-tempo song that will start the morning off on a pleasant note."

[1163] As described above, this system allows users to wake up to fresh music every morning, and also allows them to start their day off right with the optimal alarm sound depending on the weather and environment.

[1164] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1165] Step 1:

[1166] The server sends a request to set an alarm to the user's device at a specific time every day (e.g., 6:00 AM). This request is made via an HTTP request, and the message contains an "alarm setting request." The sent HTTP request is the input, and the arrival of the request data on the user's device is the output.

[1167] Step 2:

[1168] The device receives an alarm setting request from the server. It then uses the GPS module to determine the user's current location. Specifically, the device uses GPS to obtain longitude and latitude information and uses this as location information. The input is the request data from the server, and the output is the obtained location information.

[1169] Step 3:

[1170] The device sends a request to the weather information API based on its location information to obtain current weather information. The obtained weather information includes weather conditions, temperature, humidity, etc. Specifically, an HTTP request is sent to the API, and weather data is returned as a response. The input is location information, and the output is weather information.

[1171] Step 4:

[1172] The device sends the weather information it has acquired to the server. The weather information is essential because the server generates music based on this information. The weather information sent by the device is the input, and the server's receipt of it is the output.

[1173] Step 5:

[1174] The server initializes the music generation AI based on the received weather information and sets the music generation parameters. For example, if it's sunny, it sets a bright melody and a fast tempo. New music is then generated based on the set parameters. The input is the weather information and music generation parameters, and the output is the generated music data.

[1175] Step 6:

[1176] The server sends the generated music data to the user's device as an HTTP response. This generated music is saved in MP3 or WAV format. The input is the generated music data, and the output is the music data being sent to the user's device.

[1177] Step 7:

[1178] The device receives music data sent from the server and saves it in local storage. The saved music data is set as an alarm sound. The input is the music data received from the server, and the output is saving the music data to local storage.

[1179] Step 8:

[1180] The device sets the stored music data as an alarm sound and plays it at the alarm time. When the alarm time arrives, the music plays and the user wakes up. The input is the music data stored in local storage and the alarm time, and the output is the music playing and the user waking up.

[1181] These steps allow the user to wake up pleasantly to new music every morning.

[1182] 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.

[1183] The "AI Composition Alarm System" of this invention aims to allow users to wake up to different music every morning, and has the ability to generate new music based on weather information and the user's emotional information. This prevents users from becoming accustomed to the alarm sound and provides a comfortable awakening. Furthermore, by taking the user's emotions into consideration, the system further promotes a pleasant awakening.

[1184] overview

[1185] The system consists of a means for acquiring weather information, an emotion engine that recognizes the user's emotions, a means for generating new music using music generation AI, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. Furthermore, it also includes a means for identifying the user's current location when acquiring weather information.

[1186] Program processing

[1187] Server Processing

[1188] Step 1: The server sends an alarm setting request to the device every day at a specific time (e.g., 6:00 AM). This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[1189] Step 2: When the user's emotional information is sent, the server receives it and initializes the music generation AI. The emotional information is obtained from an emotion engine that analyzes the user's emotions using, for example, a camera or microphone.

[1190] Step 3: The server sets music parameters based on the received weather information and the user's emotional information. Further fine-tuning is performed based on the emotional information, such as bright and cheerful music for sunny days and relaxing music for rainy days.

[1191] Step 4: The AI ​​generates new music based on the parameters you set, which can then be saved in MP3 or WAV format, for example.

[1192] Step 5: The server sends the generated music data to the device, also using an HTTP response.

[1193] Terminal handling

[1194] Step 1: The device receives the alarm setting request from the server and uses GPS to determine the user's current location. Specifically, it calls the device's location service to obtain the latitude and longitude.

[1195] Step 2: The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to get weather information for the target area. This request includes latitude and longitude parameters.

[1196] Step 3: The device receives weather information from the weather information API, including the weather condition (sunny, rainy, etc.) and temperature.

[1197] Step 4: The device sends the acquired weather information and emotion data from the user's emotion engine to the server. The emotion engine analyzes the user's current emotion using the camera and microphone.

[1198] Step 5: The device receives the music data sent from the server and stores it in its local storage.

[1199] Step 6: The device uses the received music data to set an alarm, and the music will be played at the set time through the alarm application.

[1200] Step 7: At the set alarm time, the device will play the music data stored on it, allowing the user to wake up to new music.

[1201] Specific examples

[1202] Assume that user B wants to wake up at 7:00 AM every day.

[1203] 1. The server sends an "alarm setting request" to User B's device at 6:00 AM.

[1204] 2. The device receives the request and uses GPS to identify the current location of User B. For example, it identifies the location as "Chuo-ku, Osaka City."

[1205] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 20 degrees."

[1206] 4. The device uses the emotion engine to analyze User B's emotions and determine, for example, that he is "relaxed."

[1207] 5. The device combines weather information and emotion information and sends it to the server.

[1208] 6. The server receives weather information and emotional information and has the music generation AI create a "relaxing song suitable for a sunny day."

[1209] 7. The server sends the generated music data to the device. For example, a slow, relaxing acoustic guitar song is generated.

[1210] 8. The device saves the music data to local storage and sets the alarm time to 7:00.

[1211] 9. At 7:00, the alarm time, the device plays music and User B wakes up to relaxing music.

[1212] 10. User B turns off the alarm and starts the day in a relaxed state.

[1213] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up tailored to their individual condition.

[1214] The processing flow will be explained below.

[1215] Step 1:

[1216] The server sends an alarm setting request to the user's device every day at a specific time (e.g., 6:00 a.m.) This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[1217] Step 2:

[1218] The terminal receives an alarm setting request from the server, which causes the terminal to start the alarm setting process.

[1219] Step 3:

[1220] The device uses GPS to determine the user's current location. Specifically, it calls the device's location information service to obtain the latitude and longitude.

[1221] Step 4:

[1222] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to obtain weather information for the target area. This request includes latitude and longitude parameters.

[1223] Step 5:

[1224] The device receives weather information from the weather information API, including weather conditions (sunny, rainy, etc.) and temperature.

[1225] Step 6:

[1226] The device uses the built-in camera and microphone to acquire data to recognize emotions from the user's face and voice, and this processing is carried out by the emotion engine.

[1227] Step 7:

[1228] The device identifies the user's emotional state (e.g., relaxed, stressed, etc.) based on analysis by the emotion engine.

[1229] Step 8:

[1230] The weather information and emotion information acquired by the device are sent to the server. Weather information and emotion data are sent to the server using the HTTP protocol.

[1231] Step 9:

[1232] The server receives weather and emotion information sent from the device and initializes the music generation AI based on this information.

[1233] Step 10:

[1234] The server sets music parameters based on weather information and emotional information. For example, if the weather is "sunny" and the user is "relaxed," the tempo is slowed down and relaxing instruments (e.g., acoustic guitar or piano) are used.

[1235] Step 11:

[1236] The server passes the set parameters to the music generation AI to generate new music. In this process, the AI ​​automatically creates music based on the specified parameters.

[1237] Step 12:

[1238] The server receives the generated music data and saves it in MP3 or WAV format.

[1239] Step 13:

[1240] The server sends the generated music data to the terminal using an HTTP response.

[1241] Step 14:

[1242] The device receives the music data sent from the server and stores it in local storage.

[1243] Step 15:

[1244] Set an alarm using the music data received by the device, and use the alarm application to play the music at the set time.

[1245] Step 16:

[1246] The device will play the stored music data at the set alarm time, allowing the user to wake up to new music.

[1247] Step 17:

[1248] The user wakes up to the sound of the alarm and can optionally dismiss the alarm or use the snooze function to set the alarm again.

[1249] Specific examples

[1250] Assume that user B wants to wake up at 7:00 AM every day.

[1251] 1. The server sends an "alarm setting request" to User B's device at 6:00 AM.

[1252] 2. The device receives the request and uses GPS to identify the current location of User B. For example, it identifies that it is in Shinjuku Ward, Tokyo.

[1253] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[1254] 4. The device uses the emotion engine to analyze User B's emotions and determine, for example, that he is "relaxed."

[1255] 5. The device combines weather information and emotion information and sends it to the server.

[1256] 6. The server receives weather information and emotional information and has the music generation AI create a "relaxing song suitable for a sunny day."

[1257] 7. The server sends the generated music data to the device. For example, a slow, relaxing acoustic guitar song is generated.

[1258] 8. The device saves the music data to local storage and sets the alarm time to 7:00.

[1259] 9. At 7:00, the alarm time, the device plays music and User B wakes up to relaxing music.

[1260] 10. User B turns off the alarm and starts the day in a relaxed state.

[1261] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up tailored to their individual condition.

[1262] Example 2

[1263] 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."

[1264] With conventional alarm systems, users become accustomed to the same alarm sound, making it difficult to wake up effectively. Furthermore, there was a lack of technology to generate alarm sounds that took into account not only weather information but also the user's emotional information, making it impossible to provide a comfortable waking experience tailored to each individual user.

[1265] 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.

[1266] In this invention, the server includes means for acquiring weather information, means for acquiring a user's emotions using an emotion engine that recognizes the user's emotions, and means for generating new music using a music generation AI model based on the acquired weather information and user's emotion information. This allows new music that is optimal for each individual user to be generated every day, providing a pleasant awakening.

[1267] "Weather information" is a general term for relevant meteorological data such as current weather conditions, temperature, and humidity.

[1268] An "emotion engine" is software or hardware that analyzes a user's facial expressions, tone of voice, etc., to recognize the user's emotional state.

[1269] A "music generation AI model" is an artificial intelligence model that automatically generates new music based on specified parameters.

[1270] An "alarm sound" is an audio signal that is set to wake the user up.

[1271] "Current Location" means the user's actual geographic location as determined using GPS or other location technology.

[1272] The purpose of the "AI Composition Alarm System" of this invention is to allow users to wake up to different music every morning. Specifically, it generates new music based on weather information and the user's emotional state, and sets it as the alarm sound, preventing users from becoming accustomed to the alarm sound and providing a pleasant awakening. Furthermore, by taking the user's emotions into consideration, it further promotes a pleasant awakening.

[1273] System Components

[1274] The system includes the following components:

[1275] 1. How to get weather information:

[1276] Specifically, current weather information is obtained using a weather information API (e.g., OpenWeatherMap).

[1277] 2. Emotion engine that recognizes user emotions:

[1278] It includes hardware and software for analyzing the user's facial expressions and tone of voice to recognize their current emotional state.

[1279] 3. Music generation AI model:

[1280] Includes artificial intelligence models (e.g., GPT-3-based generative AI) that automatically generate new music based on specified parameters.

[1281] 4. How to set the generated music as an alarm sound:

[1282] Save the music data to the device's local storage and set it as the alarm sound through the alarm application.

[1283] 5. How to play the generated music at the alarm time:

[1284] It includes software and hardware for playing an alarm sound at a set time.

[1285] 6. How to determine the user's current location:

[1286] The user's current location is determined using location information services such as GPS.

[1287] Specific operation of the system

[1288] 1. Server operation:

[1289] The server sends an alarm setting request to the user's terminal at a specified time every day using the HTTP protocol.

[1290] The server receives weather information and user emotional information sent from the device and initializes the music generation AI model based on that information.

[1291] The music generation AI model is given a prompt like this to generate music:

[1292] "The user is feeling relaxed today. The current weather is sunny and the temperature is 20 degrees. Based on these conditions, generate a relaxing acoustic guitar song."

[1293] The generated music data is sent to the terminal in MP3 or WAV format.

[1294] 2. Device behavior:

[1295] The device receives an alarm setting request from the server and uses the GPS function to determine the current location.

[1296] Based on the identified current location, a request is sent to the weather information API to obtain weather information.

[1297] The device uses a camera and microphone to analyze the user's emotions with an emotion engine, and transmits the obtained emotion information to the server.

[1298] The terminal receives the music data sent from the server and stores it in local storage.

[1299] Use the Alarms application to set an alarm to play music at a specified time.

[1300] It plays music at a set time to wake the user up.

[1301] Hardware and software used

[1302] Server: Servers operated in data centers with high-performance processors (e.g., cloud infrastructure)

[1303] Device: Smartphone with GPS function, camera and microphone (e.g. smart device)

[1304] Weather Information API: Web API that provides weather information (e.g., OpenWeatherMap)

[1305] Music generation AI model: An artificial intelligence model that generates music based on specified parameters (e.g., GPT-3)

[1306] Location services: Standard GPS function of the device

[1307] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up in a way that suits their individual condition.

[1308] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1309] Step 1:

[1310] The server sends an "alarm setting request" to the user's device as an HTTP request every day at 6:00 AM. This request contains information for setting the alarm. The input is the server's scheduled time, and the output is the request sent to the user's device.

[1311] Step 2:

[1312] The device receives the alarm setting request from the server and uses the location information service to determine the current location. Specifically, it calls the device's GPS function to obtain latitude and longitude data. This location information is used as input, and the output is to save the location information in the device's internal memory.

[1313] Step 3:

[1314] The device sends a request to the weather information API based on the identified current location. The request includes latitude and longitude parameters. The input is location data, and the output is a request to the weather information API.

[1315] Step 4:

[1316] Receives a response from the weather information API and analyzes its contents. Specifically, it obtains data such as the current weather conditions and temperature. The input is the response data from the API, and the output is the analyzed weather information.

[1317] Step 5:

[1318] The device uses a camera and microphone to capture the user's facial expressions and voice, which are then analyzed by the emotion engine. The emotion engine then determines the user's emotional state based on this data. The input is the user's facial expressions and voice data, and the output is the determined emotional information.

[1319] Step 6:

[1320] The device sends the acquired weather information and emotion information to the server. Specifically, it uses an HTTP POST request and includes the header "Content-Type: application / json". The input is weather information and emotion information, and the output is data sent to the server.

[1321] Step 7:

[1322] The server receives weather information and emotion information sent from the device. Based on this data, it creates a prompt sentence to input into the music generation AI model. The input is weather information and emotion information, and the output is the generation of a prompt sentence. Specifically, it generates a sentence such as, "The user is feeling relaxed today. The current weather is sunny, and the temperature is 20 degrees. Based on these conditions, please generate a relaxing acoustic guitar song."

[1323] Step 8:

[1324] The music generation AI model generates new music based on a created prompt. The input is the prompt, and the output is the generated music data. Specifically, music files are generated in MP3 or WAV format.

[1325] Step 9:

[1326] The server sends the generated music data to the terminal. This is done using HTTP responses. The input is the music data, and the output is data sent to the user's terminal.

[1327] Step 10:

[1328] The device saves the received music data in local storage. The save destination is, for example, a directory called " / storage / emulated / 0 / Alarms / ". The input is music data, and the output is saved to local storage.

[1329] Step 11:

[1330] The device sets an alarm using stored music data. Using the alarm management application API, music is played at the set time (e.g., 7:00 AM). The input is the music data and the set time, and the output is the alarm setting.

[1331] Step 12:

[1332] At the set time, the device will play music to wake the user up. The input is setting the alarm and the output is playing music. The user can wake up comfortably to new music.

[1333] (Application example 2)

[1334] 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."

[1335] Conventional alarm systems wake users up with the same sound every time, which can lead to users becoming accustomed to the alarm sound and making it difficult to wake up. Furthermore, background music in stores tends to be fixed, and music is played without taking into account the emotions of customers and employees or external weather information, making it difficult to maximize the store atmosphere and customer experience.

[1336] 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 acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information and emotional information, means for setting the generated music as an alarm sound or background music for the store, means for playing the generated music at the set alarm time or in real time, and means for acquiring emotional information of customers and employees. This makes it possible to generate appropriate music according to the emotional state of the user or customer and the weather information, allowing for a comfortable awakening and providing an optimal store atmosphere.

[1337] "Weather information" refers to current and near-future weather conditions and meteorological data such as temperature, precipitation, and wind speed.

[1338] "Emotion information" is data that represents the psychological state or emotions of a user or customer, and is classified into emotion categories such as "happy," "relaxed," and "excited."

[1339] "Music generation AI" is an artificial intelligence system that automatically generates new music by setting parameters based on weather information and emotional information.

[1340] An "alarm sound" is music or sound that is played to wake the user up at a specified time.

[1341] "BGM" is an abbreviation for background music, and refers to the background music played in indoor spaces such as stores and commercial facilities.

[1342] A "server" is a computing device that provides specific services and data processing over a network and serves client devices.

[1343] "Device" refers to a hardware device that collects user or customer emotions and weather information and plays generated music. Examples include smartphones, smart glasses, head-mounted displays, and robots.

[1344] "Location information" is data that indicates the current geographical location of a user or a store and is expressed in the form of latitude and longitude.

[1345] A "weather information API" is an application programming interface that provides weather information over the web and is a means for obtaining weather data.

[1346] An "emotion analysis engine" is software that analyzes data obtained from input devices such as cameras and microphones and identifies the emotional state of users or customers.

[1347] "HTTP protocol" is an abbreviation for Hypertext Transfer Protocol, an Internet protocol for data communication.

[1348] "Music parameters" are set values ​​that determine the characteristics of music, and include tempo, key, instrument composition, and the like.

[1349] This invention is a system that uses music generation AI to generate new music based on weather information and emotional information, and plays it as an alarm sound or background music in a physical store. Specifically, it is implemented using a server and a terminal.

[1350] System configuration

[1351] The system consists of the following main components:

[1352] Weather information acquisition means: Uses a weather information API (e.g., OpenWeatherMap) to acquire weather data based on the terminal's current location.

[1353] Emotion information acquisition means: An emotion analysis engine that uses cameras and microphones to analyze the emotional state of users, store customers, and employees.

[1354] Music generation method: Based on the weather and emotional information, the music generation AI generates new music. The generated music is saved in MP3 or WAV format.

[1355] Alarm / BGM setting method: The generated music is set as an alarm sound or background music in the store. Devices such as smartphones, smart glasses, head-mounted displays, and robots are used.

[1356] Playback method: Play the generated music at a specified time or in real time.

[1357] Server Processing

[1358] The server has the following functions:

[1359] Sending an alarm setting request: Send an alarm setting request to the client device at a specific time every day (e.g., 10:00 a.m.), which wakes up the user or store's system and collects the appropriate data.

[1360] Music generation: Music parameters are set based on received weather and emotional information, and new music is generated using music generation AI.

[1361] Sending music data: The generated music data is sent to the device so that it can be used as an alarm sound or background music.

[1362] Terminal handling

[1363] The main processing of the terminal is as follows:

[1364] Obtaining location information: Use GPS to determine current location information, and send it to a weather information API to obtain weather information for the target area.

[1365] Acquiring emotional information: Emotional information of users and customers is acquired using a camera or microphone and sent to the server.

[1366] Receiving and storing music data: Receives music data sent from the server and stores it in local storage.

[1367] Setting and playing alarms and background music: Set the generated music as an alarm sound or background music and play it at a specified time or in real time.

[1368] Examples of specific examples and prompts

[1369] The actual usage scenario is described below.

[1370] Specific examples

[1371] The flow when Store A starts the system at 10:00 in the morning while preparing to open is as follows.

[1372] 1. The server sends a "BGM setting request" to the terminal at store A.

[1373] 2. The device receives the request and uses GPS to determine its current location. For example, it may determine that it is in Shibuya Ward, Tokyo.

[1374] 3. The device accesses the weather information API and obtains weather information for Shibuya Ward, Tokyo. For example, it obtains weather information such as "sunny, temperature 25 degrees."

[1375] 4. The emotion analysis engine analyzes the employee's emotions and determines that they are "energetic and cheerful."

[1376] 5. The device sends weather information and emotion information to the server.

[1377] 6. The server asks the music generation AI to create a "lively and cheerful song suitable for a sunny day."

[1378] 7. The server sends the generated music data to the device. For example, lively pop music is generated.

[1379] 8. The device stores the music data locally and then plays it on the store's sound system.

[1380] 9. The music in the store creates a lively and cheerful atmosphere, making customers feel comfortable.

[1381] Prompt Sentence Examples

[1382] Weather: Sunny, 25 degrees

[1383] Emotional information: Lively and cheerful

[1384] Generated Music Style: Pop

[1385] Generated music tempo: Fast

[1386] In this way, appropriate music is generated according to the emotional state of the user or customer and weather information, thereby providing a pleasant awakening and an optimal store atmosphere.

[1387] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1388] Step 1:

[1389] The server sends an alarm setting request to the client device at a specific time every day (e.g., 10:00 a.m.). This request is sent using the HTTP protocol and contains the message "Request to set alarm." The input is the specified time, and the output is the alarm setting request message.

[1390] Step 2:

[1391] The device receives an alarm setting request from the server and uses GPS to determine the current location. The input is the alarm setting request message, and the output is the current location information (latitude and longitude). Specifically, the device's location information service is called to obtain the latitude and longitude.

[1392] Step 3:

[1393] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location information to obtain weather information for the target area. This request includes latitude and longitude parameters. The input is the current location information, and the output is weather information.

[1394] Step 4:

[1395] The device receives weather information from the weather information API. This information includes the weather condition (sunny, rainy, etc.) and temperature. The input is the response from the weather information API, and the output is the specific weather information.

[1396] Step 5:

[1397] The device uses a camera and microphone to obtain emotional information from the user or customer through an emotion analysis engine. The input is data from the camera or microphone, and the output is analyzed emotional information. Specifically, facial expression analysis and voice analysis technologies are used.

[1398] Step 6:

[1399] The device combines the acquired weather information and emotion information and sends it to the server. The input is weather information and emotion information, and the output is request data to the server. Specifically, the weather information and emotion information are sent to the server as parameters using the HTTP protocol.

[1400] Step 7:

[1401] The server initializes the music generation AI and sets the music parameters based on the received weather and emotional information. Further fine-tuning is made based on emotional information, such as bright and cheerful music for sunny days and relaxing music for rainy days. The input is weather information and emotional information, and the output is the set music parameters.

[1402] Step 8:

[1403] The server generates new music based on the set parameters using music generation AI. This music is saved in MP3 or WAV format, for example. The input is the music parameters, and the output is the generated music data. Specifically, the AI ​​model generates music by inputting prompts.

[1404] Step 9:

[1405] The server sends the generated music data to the device. This is also done using HTTP responses. The input is the generated music data, and the output is the transmission of the music data to the device.

[1406] Step 10:

[1407] The device receives the music data sent from the server and stores it in local storage. The input is music data, and the output is storage in local storage.

[1408] Step 11:

[1409] The device uses the received music data to set alarms and background music for the store. Music is played at the set time or in real time through an alarm application or sound system. The input is music data, and the output is alarm and background music settings. Specifically, this includes scheduler functions and sound system settings.

[1410] Step 12:

[1411] The device plays music data stored on it at the set alarm time or in real time. This allows users to wake up to new music or enjoy appropriate background music in the store. The input is the set timing, and the output is music playback.

[1412] 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.

[1413] 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.

[1414] 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.

[1415] [Fourth embodiment]

[1416] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1417] 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.

[1418] 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).

[1419] 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.

[1420] 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.

[1421] 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).

[1422] 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.

[1423] 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.

[1424] 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.

[1425] 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.

[1426] 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.

[1427] 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.

[1428] 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."

[1429] The AI ​​Composition Alarm System of this invention aims to allow users to wake up to different music every morning, and has the ability to generate new music based on weather information. This prevents users from becoming accustomed to traditional alarm sounds, and provides a pleasant wake-up experience.

[1430] overview

[1431] The system consists of a means for acquiring weather information, a means for generating new music using music generation AI, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. Furthermore, when acquiring weather information, the system also includes a means for identifying the user's current location.

[1432] Program processing

[1433] Server Processing

[1434] Step 1: The server sends an alarm setting request to the device every day at a specific time (e.g., 6:00 AM). This request is made via an HTTP request, and the message contains an "alarm setting request."

[1435] Step 2: The server initializes the music generation AI based on the weather information. It sets the music parameters to be passed to the AI ​​based on the received weather information. For example, if it is sunny, it sets a bright melody and a fast tempo.

[1436] Step 3: The AI ​​generates new music based on the parameters you set, and the music is saved in MP3 or WAV format.

[1437] Step 4: The server sends the generated music data to the device, also using an HTTP response.

[1438] Terminal handling

[1439] Step 1: The device receives an alarm setting request from the server and uses GPS to determine the user's current location.

[1440] Step 2: The device sends a request to the weather information API to obtain current weather information, including weather conditions and temperature.

[1441] Step 3: The device sends the weather information to the server, which then generates music based on this information.

[1442] Step 4: The device receives the music data sent from the server and stores it in its local storage.

[1443] Step 5: The device will set the received music as the alarm sound and play it at the alarm time.

[1444] Specific examples

[1445] Assume that user A wants to wake up at 7:00 am every day.

[1446] 1. The server sends an "alarm setting request" to User A's device at 6:00 AM.

[1447] 2. The device receives the request and uses GPS to identify the current location of User A. For example, it identifies the location as "Shinjuku-ku, Tokyo."

[1448] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[1449] 4. The device sends this weather information to the server.

[1450] 5. The server receives weather information and instructs the music generation AI to create a "cheerful song suitable for sunny days."

[1451] 6. The server sends the generated music data to the device. For example, an up-tempo acoustic guitar song is generated.

[1452] 7. The device saves the music data to local storage and sets the alarm time to 7:00.

[1453] 8. At 7:00, the alarm time, the device plays music and User A wakes up to cheerful music.

[1454] 9. User A stops the alarm, giving them a comfortable start to their day.

[1455] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to habituation to the same sounds. It also uses weather-appropriate music to wake users up according to their conditions that day.

[1456] The processing flow will be explained below.

[1457] Step 1:

[1458] The server checks its internal clock and sends an alarm setting request to the user's device at a specific time each day (e.g., 6:00 a.m.). This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[1459] Step 2:

[1460] The terminal receives an alarm setting request from the server, which causes the terminal to start the alarm setting process.

[1461] Step 3:

[1462] The device uses GPS to determine the user's current location. Specifically, it calls the device's location information service to obtain the latitude and longitude.

[1463] Step 4:

[1464] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to obtain weather information for the target area. This request includes latitude and longitude parameters.

[1465] Step 5:

[1466] The device receives weather information from the weather information API, including weather conditions (sunny, rainy, etc.) and temperature.

[1467] Step 6:

[1468] The weather information acquired by the device is sent to the server. Data including the weather information is sent to the server using the HTTP protocol.

[1469] Step 7:

[1470] The server receives weather information sent from the device and initializes the music generation AI based on this information.

[1471] Step 8:

[1472] The server sets music parameters based on weather information, for example, if it's "sunny," it will set the tempo faster and use bright instruments (e.g., acoustic guitar).

[1473] Step 9:

[1474] The server passes the set parameters to the music generation AI to generate new music. In this process, the AI ​​automatically creates music based on the user's specifications.

[1475] Step 10:

[1476] The server receives the generated music data and saves it in MP3 or WAV format.

[1477] Step 11:

[1478] The server sends the generated music data to the terminal using an HTTP response.

[1479] Step 12:

[1480] The device receives the music data sent from the server and stores it in local storage.

[1481] Step 13:

[1482] Set an alarm using the music data received by your device, and have the music play at the set time through the alarm application.

[1483] Step 14:

[1484] The device will play the stored music data at the set alarm time, allowing the user to wake up to new music.

[1485] Step 15:

[1486] The user wakes up to the sound of the alarm and can optionally dismiss the alarm or use the snooze function to set the alarm again.

[1487] Example 1

[1488] 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."

[1489] Conventional alarm clock devices have the problem that users become accustomed to the same sound every day, which makes it difficult to wake up effectively. In addition, there is no way to provide music that matches the weather or mood, so there is a lack of means for users to start their day more comfortably.

[1490] 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.

[1491] In this invention, the server includes means for acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information, means for setting the generated music as an alarm sound, means for playing the generated music at the set alarm time, means for identifying the user's current location, means for setting music parameters for the music generation AI from the terminal, means for transmitting the generated music data to the terminal, and means for saving the generated music data in local storage. This allows the user to wake up every day to fresh music that matches the weather, providing a pleasant awakening.

[1492] "Weather information" refers to meteorological data provided based on the user's current location, including weather conditions, temperature, humidity, and the like.

[1493] "Music generation AI" refers to algorithms or software that automatically generate music based on input parameters.

[1494] An "alarm sound" is an acoustic signal that wakes the user up at a set time, and in this system, generated music is used.

[1495] A "server" is a computer device that manages the overall processing of the system, such as obtaining weather information, initializing the music generation AI, and transmitting music data.

[1496] A "terminal" refers to an electronic device owned by a user, and in this system it mainly refers to a smartphone or the like.

[1497] "Current location" refers to the geographical location information of the user, which is determined using GPS or the like.

[1498] "Music parameters" are specific input data used to specify musical characteristics and conditions for music generation AI.

[1499] "Local storage" refers to a memory area provided within a terminal where music data and the like are stored.

[1500] An "HTTP request" is a protocol for sending data to a web server and is widely used as a means of communication.

[1501] The AI ​​Composition Alarm System of this invention aims to allow users to wake up to different music every morning by generating new music based on weather information. This prevents users from becoming accustomed to traditional alarm sounds and provides a pleasant wake-up experience.

[1502] The system consists of the following main elements:

[1503] Server Roles

[1504] The server sends an HTTP request to the user's device at a specified time each day (e.g., 6:00 AM) to notify the user of an "alarm setting request." The server also initializes the music generation AI based on weather information and sets music parameters. This music generation AI generates music with an appropriate melody and tempo according to specific weather conditions, such as sunny or rainy weather. The generated music data is saved in MP3 or WAV format and sent to the device.

[1505] Device Role

[1506] The device receives an alarm setting request from the server and uses GPS to identify the user's current location. It then sends a request to the weather information API to obtain current weather information for that location. It then sends the obtained weather information to the server and receives music data generated by the server. The received music data is saved in local storage and played at the alarm time.

[1507] User operations

[1508] Users wake up to new music every morning. When the set alarm sounds, users wake up to pleasant music and press the alarm stop button on their device to turn off the alarm.

[1509] Hardware and software used

[1510] Server: Virtual server on a cloud platform (e.g. AWS EC2)

[1511] Device: A smartphone owned by the user (e.g., an Android device)

[1512] Weather information API: Weather information provision service (e.g. OpenWeatherMap API)

[1513] Music generation AI: Automatic composition algorithms (e.g., OpenAI's music generation model)

[1514] Specific examples

[1515] Let's assume that User A wants to wake up at 7:00 AM every day. The server sends an "alarm setting request" to User A's device at 6:00 AM. The device receives the request and uses GPS to identify User A's current location. For example, it may identify it as "Shinjuku Ward, Tokyo." Based on this location, the device accesses a weather information API and obtains weather information such as "sunny, temperature 15 degrees." When the device sends this weather information to the server, the server instructs the music generation AI to generate "an upbeat song suitable for a sunny day." The generated music is sent to the device as an up-tempo acoustic guitar piece. The device stores this music in local storage and plays it at 7:00 AM, the alarm time. User A wakes up to upbeat music, allowing them to start their day feeling refreshed.

[1516] Prompt Sentence Examples

[1517] "Generate a bright, uptempo acoustic guitar song to welcome a new morning. The current weather is sunny and the temperature is 15 degrees."

[1518] This system allows users to wake up to new music every day, preventing them from becoming accustomed to the same music and providing a pleasant awakening. It also generates music based on weather information, helping users wake up to music that suits the conditions of the day.

[1519] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1520] Step 1:

[1521] The server sends an "alarm setting request" via HTTP request to the user's device at the specified time of 6:00 AM every day.

[1522] What happens: The server uses a scheduler (e.g., a Cron job) to send an HTTP request to a specific endpoint at a specified time.

[1523] Input: Time (e.g. 6:00 AM)

[1524] Output: HTTP request (alarm setting request)

[1525] Step 2:

[1526] The terminal receives an alarm setting request from the server and identifies the user's current location using GPS.

[1527] Specific operation: The device analyzes the received request and activates the GPS function to obtain the current location information.

[1528] Input: HTTP request (alarm setting request)

[1529] Output: Current location (e.g. Shinjuku-ku, Tokyo)

[1530] Step 3:

[1531] The device sends a request to the weather information API to obtain current weather information.

[1532] Specific operation: The device uses the identified location information to send an API request to a weather information service to obtain weather data.

[1533] Input: Current location (e.g. Shinjuku-ku, Tokyo)

[1534] Output: Weather information (e.g. sunny, temperature 15 degrees)

[1535] Step 4:

[1536] The terminal sends the acquired weather information to the server as an HTTP request.

[1537] Specific operation: The device formats the acquired weather information and sends it to the server via an HTTP request.

[1538] Input: Weather information (e.g. sunny, temperature 15 degrees)

[1539] Output: HTTP request (weather information)

[1540] Step 5:

[1541] The server receives weather information sent from the device and initializes the music generation AI based on that information.

[1542] How it works: The server analyzes the received weather information and generates prompts for the music generation AI to set specific music parameters, for example, a bright melody and a fast tempo on a sunny day.

[1543] Input: HTTP request (weather information)

[1544] Output: Prompt sentence (e.g., upbeat melody, fast tempo)

[1545] Step 6:

[1546] The server generates new music using music generation AI and stores the generated music data.

[1547] Specific operation: The music generation AI receives a prompt, generates new music, and saves it as an MP3 or WAV file.

[1548] Input: prompt statement

[1549] Output: Music data (MP3 or WAV format)

[1550] Step 7:

[1551] The server transmits the generated music data to the terminal in an HTTP response.

[1552] Specific operation: The server encodes the generated music file and sends it back to the device in an HTTP response.

[1553] Input: Music data (MP3 or WAV format)

[1554] Output: URL of HTTP response (music data)

[1555] Step 8:

[1556] The terminal receives the music data sent from the server and stores it in local storage.

[1557] Specific operation: The device obtains the URL of the music file from the HTTP response, downloads it, and saves it to local storage.

[1558] Input: HTTP response (music data URL)

[1559] Output: Music file (saved to local storage)

[1560] Step 9:

[1561] The terminal sets the received music file as an alarm sound and plays it at the alarm time.

[1562] Specific behavior: The device uses the alarm management function to set a new music file as the alarm sound, and plays the saved music when the alarm time arrives.

[1563] Input: Music file (stored in local storage)

[1564] Output: Alarm sound (playback of music file)

[1565] Step 10:

[1566] The user wakes up to the alarm sound and presses the alarm stop button on the terminal to cancel the alarm.

[1567] Specific actions: The user taps the device's operation panel to stop the alarm and start their day.

[1568] Input: Alarm sound (playing a music file)

[1569] Output: Stop alarm

[1570] (Application example 1)

[1571] 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."

[1572] With conventional alarm systems, users often become accustomed to a certain set of music or sounds, resulting in poor awakening. Furthermore, the music that provides a comfortable wake-up experience for a user depends on the individual's situation and environment, so general alarm sounds have limitations. While there is a particular need to improve the quality of wake-ups based on external environmental factors such as weather and temperature, there has been a lack of means to achieve this. Another problem is that music generation is not optimized based on individual user preferences or wake-up data.

[1573] 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.

[1574] In this invention, the server includes means for acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information, means for setting the generated music as an alarm sound, means for playing the generated music at the set alarm time, means for setting parameters for the generated music based on the weather information, means for identifying the user's current location, and means for generating prompts for the music generation AI and generating music based on the prompts. This allows fresh music that is appropriate for the weather and environment to be automatically generated every morning, allowing the user to wake up comfortably and efficiently. Furthermore, the music generation can be adaptively optimized using the user's wake-up data, providing a consistently comfortable wake-up experience.

[1575] "Weather information" is data relating to weather conditions such as current weather conditions, temperature, humidity, rainfall, and wind speed.

[1576] "Music generation AI" is a system that uses artificial intelligence to automatically create new music.

[1577] An "alarm sound" is the music or sound that is played at the alarm time.

[1578] The "current location" is the geographical location information of the physical location of the user's terminal.

[1579] A "prompt" is an instruction or input given to an AI system based on specific conditions or needs.

[1580] "Music parameters" are control elements such as melody, tempo, rhythm, and volume that are used when generating music.

[1581] A "generative AI model" is a system that uses artificial intelligence algorithms to create new content and information.

[1582] "Local storage" refers to a data storage area attached to a user's device.

[1583] An "alarm" is a function that operates at a set time to notify the user.

[1584] "Adaptive optimization" is the process of incrementally improving a system's performance and results based on historical data and user input.

[1585] This invention is an "AI Composition Alarm System" that allows users to wake up comfortably with different music every morning. This system generates new music based on weather information and uses it as an alarm sound. Below, we will explain in detail how to implement this system.

[1586] System configuration

[1587] The system mainly consists of the following components:

[1588] server

[1589] How to get weather information

[1590] A method for generating new music using music generation AI based on acquired weather information

[1591] A means of generating prompts for a music generation AI and generating music based on the prompts

[1592] Terminal

[1593] A means of determining the user's current location

[1594] A means of accessing the weather information API and obtaining weather information

[1595] A means of storing music data received from a server in local storage

[1596] A way to play the generated music at the alarm time

[1597] User

[1598] Set an alarm through your device to wake you up every morning

[1599] Hardware and Software Configuration

[1600] Hardware

[1601] Mobile devices such as smartphones and smart glasses

[1602] server

[1603] GPS Modules

[1604] software

[1605] requests: A library for sending HTTP requests

[1606] geopy: a library for obtaining geolocation information

[1607] pydub: A library for manipulating music files

[1608] playsound: a library for playing music

[1609] Weather information API (e.g. OpenWeatherMap)

[1610] Program processing overview

[1611] Server Processing

[1612] The server sends a request to set an alarm to the user's device at a specified time (e.g., 6:00 AM). This request is made using an HTTP request. The server then initializes the music generation AI based on weather information and generates new music based on the specified parameters. The generated music data is saved in MP3 or WAV format and sent to the user's device using an HTTP response.

[1613] Terminal handling

[1614] The device identifies the user's current location in response to a request from the server, accesses the weather information API to obtain weather information, sends the obtained weather information to the server, and saves the music data sent from the server in local storage.The device then plays the music generated at the alarm time.

[1615] Specific examples

[1616] If user A wants to wake up at 7:00 am every day, the following happens:

[1617] 1. The server sends an "alarm setting request" to User A's device at 6:00 AM.

[1618] 2. The device receives the request and uses GPS to identify the current location of User A. For example, it identifies the location as "Shinjuku-ku, Tokyo."

[1619] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[1620] 4. The device sends this weather information to the server.

[1621] 5. The server receives weather information and instructs the music generation AI to create a "cheerful song suitable for sunny days."

[1622] 6. The server sends the generated music data to the device. For example, an up-tempo acoustic guitar song is generated.

[1623] 7. The device saves the music data to local storage and sets the alarm time to 7:00.

[1624] 8. At 7:00, the alarm time, the device plays music and User A wakes up to cheerful music.

[1625] 9. User A stops the alarm, giving them a comfortable start to their day.

[1626] Prompt Sentence Examples

[1627] Examples of prompts include:

[1628] "I'd like a song with a bright, lively melody line for sunny days. Please create an up-tempo song that will start the morning off on a pleasant note."

[1629] As described above, this system allows users to wake up to fresh music every morning, and also allows them to start their day off right with the optimal alarm sound depending on the weather and environment.

[1630] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1631] Step 1:

[1632] The server sends a request to set an alarm to the user's device at a specific time every day (e.g., 6:00 AM). This request is made via an HTTP request, and the message contains an "alarm setting request." The sent HTTP request is the input, and the arrival of the request data on the user's device is the output.

[1633] Step 2:

[1634] The device receives an alarm setting request from the server. It then uses the GPS module to determine the user's current location. Specifically, the device uses GPS to obtain longitude and latitude information and uses this as location information. The input is the request data from the server, and the output is the obtained location information.

[1635] Step 3:

[1636] The device sends a request to the weather information API based on its location information to obtain current weather information. The obtained weather information includes weather conditions, temperature, humidity, etc. Specifically, an HTTP request is sent to the API, and weather data is returned as a response. The input is location information, and the output is weather information.

[1637] Step 4:

[1638] The device sends the weather information it has acquired to the server. The weather information is essential because the server generates music based on this information. The weather information sent by the device is the input, and the server's receipt of it is the output.

[1639] Step 5:

[1640] The server initializes the music generation AI based on the received weather information and sets the music generation parameters. For example, if it's sunny, it sets a bright melody and a fast tempo. New music is then generated based on the set parameters. The input is the weather information and music generation parameters, and the output is the generated music data.

[1641] Step 6:

[1642] The server sends the generated music data to the user's device as an HTTP response. This generated music is saved in MP3 or WAV format. The input is the generated music data, and the output is the music data being sent to the user's device.

[1643] Step 7:

[1644] The device receives music data sent from the server and saves it in local storage. The saved music data is set as an alarm sound. The input is the music data received from the server, and the output is saving the music data to local storage.

[1645] Step 8:

[1646] The device sets the stored music data as an alarm sound and plays it at the alarm time. When the alarm time arrives, the music plays and the user wakes up. The input is the music data stored in local storage and the alarm time, and the output is the music playing and the user waking up.

[1647] These steps allow the user to wake up pleasantly to new music every morning.

[1648] 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.

[1649] The "AI Composition Alarm System" of this invention aims to allow users to wake up to different music every morning, and has the ability to generate new music based on weather information and the user's emotional information. This prevents users from becoming accustomed to the alarm sound and provides a comfortable awakening. Furthermore, by taking the user's emotions into consideration, the system further promotes a pleasant awakening.

[1650] overview

[1651] The system consists of a means for acquiring weather information, an emotion engine that recognizes the user's emotions, a means for generating new music using music generation AI, a means for setting the generated music as an alarm sound, and a means for playing the generated music at the set alarm time. Furthermore, it also includes a means for identifying the user's current location when acquiring weather information.

[1652] Program processing

[1653] Server Processing

[1654] Step 1: The server sends an alarm setting request to the device every day at a specific time (e.g., 6:00 AM). This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[1655] Step 2: When the user's emotional information is sent, the server receives it and initializes the music generation AI. The emotional information is obtained from an emotion engine that analyzes the user's emotions using, for example, a camera or microphone.

[1656] Step 3: The server sets music parameters based on the received weather information and the user's emotional information. Further fine-tuning is performed based on the emotional information, such as bright and cheerful music for sunny days and relaxing music for rainy days.

[1657] Step 4: The AI ​​generates new music based on the parameters you set, which can then be saved in MP3 or WAV format, for example.

[1658] Step 5: The server sends the generated music data to the device, also using an HTTP response.

[1659] Terminal handling

[1660] Step 1: The device receives the alarm setting request from the server and uses GPS to determine the user's current location. Specifically, it calls the device's location service to obtain the latitude and longitude.

[1661] Step 2: The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to get weather information for the target area. This request includes latitude and longitude parameters.

[1662] Step 3: The device receives weather information from the weather information API, including the weather condition (sunny, rainy, etc.) and temperature.

[1663] Step 4: The device sends the acquired weather information and emotion data from the user's emotion engine to the server. The emotion engine analyzes the user's current emotion using the camera and microphone.

[1664] Step 5: The device receives the music data sent from the server and stores it in its local storage.

[1665] Step 6: The device uses the received music data to set an alarm, and the music will be played at the set time through the alarm application.

[1666] Step 7: At the set alarm time, the device will play the music data stored on it, allowing the user to wake up to new music.

[1667] Specific examples

[1668] Assume that user B wants to wake up at 7:00 AM every day.

[1669] 1. The server sends an "alarm setting request" to User B's device at 6:00 AM.

[1670] 2. The device receives the request and uses GPS to identify the current location of User B. For example, it identifies the location as "Chuo-ku, Osaka City."

[1671] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 20 degrees."

[1672] 4. The device uses the emotion engine to analyze User B's emotions and determine, for example, that he is "relaxed."

[1673] 5. The device combines weather information and emotion information and sends it to the server.

[1674] 6. The server receives weather information and emotional information and has the music generation AI create a "relaxing song suitable for a sunny day."

[1675] 7. The server sends the generated music data to the device. For example, a slow, relaxing acoustic guitar song is generated.

[1676] 8. The device saves the music data to local storage and sets the alarm time to 7:00.

[1677] 9. At 7:00, the alarm time, the device plays music and User B wakes up to relaxing music.

[1678] 10. User B turns off the alarm and starts the day in a relaxed state.

[1679] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up tailored to their individual condition.

[1680] The processing flow will be explained below.

[1681] Step 1:

[1682] The server sends an alarm setting request to the user's device every day at a specific time (e.g., 6:00 a.m.) This request is sent using the HTTP protocol and contains the message "Alarm setting request."

[1683] Step 2:

[1684] The terminal receives an alarm setting request from the server, which causes the terminal to start the alarm setting process.

[1685] Step 3:

[1686] The device uses GPS to determine the user's current location. Specifically, it calls the device's location information service to obtain the latitude and longitude.

[1687] Step 4:

[1688] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location to obtain weather information for the target area. This request includes latitude and longitude parameters.

[1689] Step 5:

[1690] The device receives weather information from the weather information API, including weather conditions (sunny, rainy, etc.) and temperature.

[1691] Step 6:

[1692] The device uses the built-in camera and microphone to acquire data to recognize emotions from the user's face and voice, and this processing is carried out by the emotion engine.

[1693] Step 7:

[1694] The device identifies the user's emotional state (e.g., relaxed, stressed, etc.) based on analysis by the emotion engine.

[1695] Step 8:

[1696] The weather information and emotion information acquired by the device are sent to the server. Weather information and emotion data are sent to the server using the HTTP protocol.

[1697] Step 9:

[1698] The server receives weather and emotion information sent from the device and initializes the music generation AI based on this information.

[1699] Step 10:

[1700] The server sets music parameters based on weather information and emotional information. For example, if the weather is "sunny" and the user is "relaxed," the tempo is slowed down and relaxing instruments (e.g., acoustic guitar or piano) are used.

[1701] Step 11:

[1702] The server passes the set parameters to the music generation AI to generate new music. In this process, the AI ​​automatically creates music based on the specified parameters.

[1703] Step 12:

[1704] The server receives the generated music data and saves it in MP3 or WAV format.

[1705] Step 13:

[1706] The server sends the generated music data to the terminal using an HTTP response.

[1707] Step 14:

[1708] The device receives the music data sent from the server and stores it in local storage.

[1709] Step 15:

[1710] Set an alarm using the music data received by the device, and use the alarm application to play the music at the set time.

[1711] Step 16:

[1712] The device will play the stored music data at the set alarm time, allowing the user to wake up to new music.

[1713] Step 17:

[1714] The user wakes up to the sound of the alarm and can optionally dismiss the alarm or use the snooze function to set the alarm again.

[1715] Specific examples

[1716] Assume that user B wants to wake up at 7:00 AM every day.

[1717] 1. The server sends an "alarm setting request" to User B's device at 6:00 AM.

[1718] 2. The device receives the request and uses GPS to identify the current location of User B. For example, it identifies that it is in Shinjuku Ward, Tokyo.

[1719] 3. The device accesses the weather information API and obtains the weather information "Sunny, temperature 15 degrees."

[1720] 4. The device uses the emotion engine to analyze User B's emotions and determine, for example, that he is "relaxed."

[1721] 5. The device combines weather information and emotion information and sends it to the server.

[1722] 6. The server receives weather information and emotional information and has the music generation AI create a "relaxing song suitable for a sunny day."

[1723] 7. The server sends the generated music data to the device. For example, a slow, relaxing acoustic guitar song is generated.

[1724] 8. The device saves the music data to local storage and sets the alarm time to 7:00.

[1725] 9. At 7:00, the alarm time, the device plays music and User B wakes up to relaxing music.

[1726] 10. User B turns off the alarm and starts the day in a relaxed state.

[1727] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up tailored to their individual condition.

[1728] Example 2

[1729] 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."

[1730] With conventional alarm systems, users become accustomed to the same alarm sound, making it difficult to wake up effectively. Furthermore, there was a lack of technology to generate alarm sounds that took into account not only weather information but also the user's emotional information, making it impossible to provide a comfortable waking experience tailored to each individual user.

[1731] 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.

[1732] In this invention, the server includes means for acquiring weather information, means for acquiring a user's emotions using an emotion engine that recognizes the user's emotions, and means for generating new music using a music generation AI model based on the acquired weather information and user's emotion information. This allows new music that is optimal for each individual user to be generated every day, providing a pleasant awakening.

[1733] "Weather information" is a general term for relevant meteorological data such as current weather conditions, temperature, and humidity.

[1734] An "emotion engine" is software or hardware that analyzes a user's facial expressions, tone of voice, etc., to recognize the user's emotional state.

[1735] A "music generation AI model" is an artificial intelligence model that automatically generates new music based on specified parameters.

[1736] An "alarm sound" is an audio signal that is set to wake the user up.

[1737] "Current Location" means the user's actual geographic location as determined using GPS or other location technology.

[1738] The purpose of the "AI Composition Alarm System" of this invention is to allow users to wake up to different music every morning. Specifically, it generates new music based on weather information and the user's emotional state, and sets it as the alarm sound, preventing users from becoming accustomed to the alarm sound and providing a pleasant awakening. Furthermore, by taking the user's emotions into consideration, it further promotes a pleasant awakening.

[1739] System Components

[1740] The system includes the following components:

[1741] 1. How to get weather information:

[1742] Specifically, current weather information is obtained using a weather information API (e.g., OpenWeatherMap).

[1743] 2. Emotion engine that recognizes user emotions:

[1744] It includes hardware and software for analyzing the user's facial expressions and tone of voice to recognize their current emotional state.

[1745] 3. Music generation AI model:

[1746] Includes artificial intelligence models (e.g., GPT-3-based generative AI) that automatically generate new music based on specified parameters.

[1747] 4. How to set the generated music as an alarm sound:

[1748] Save the music data to the device's local storage and set it as the alarm sound through the alarm application.

[1749] 5. How to play the generated music at the alarm time:

[1750] It includes software and hardware for playing an alarm sound at a set time.

[1751] 6. How to determine the user's current location:

[1752] The user's current location is determined using location information services such as GPS.

[1753] Specific operation of the system

[1754] 1. Server operation:

[1755] The server sends an alarm setting request to the user's terminal at a specified time every day using the HTTP protocol.

[1756] The server receives weather information and user emotional information sent from the device and initializes the music generation AI model based on that information.

[1757] The music generation AI model is given a prompt like this to generate music:

[1758] "The user is feeling relaxed today. The current weather is sunny and the temperature is 20 degrees. Based on these conditions, generate a relaxing acoustic guitar song."

[1759] The generated music data is sent to the terminal in MP3 or WAV format.

[1760] 2. Device behavior:

[1761] The device receives an alarm setting request from the server and uses the GPS function to determine the current location.

[1762] Based on the identified current location, a request is sent to the weather information API to obtain weather information.

[1763] The device uses a camera and microphone to analyze the user's emotions with an emotion engine, and transmits the obtained emotion information to the server.

[1764] The terminal receives the music data sent from the server and stores it in local storage.

[1765] Use the Alarms application to set an alarm to play music at a specified time.

[1766] It plays music at a set time to wake the user up.

[1767] Hardware and software used

[1768] Server: Servers operated in data centers with high-performance processors (e.g., cloud infrastructure)

[1769] Device: Smartphone with GPS function, camera and microphone (e.g. smart device)

[1770] Weather Information API: Web API that provides weather information (e.g., OpenWeatherMap)

[1771] Music generation AI model: An artificial intelligence model that generates music based on specified parameters (e.g., GPT-3)

[1772] Location services: Standard GPS function of the device

[1773] This system allows users to wake up to fresh music every morning, preventing them from oversleeping due to becoming accustomed to the same sounds. It also uses music that responds to emotions, allowing users to wake up in a way that suits their individual condition.

[1774] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1775] Step 1:

[1776] The server sends an "alarm setting request" to the user's device as an HTTP request every day at 6:00 AM. This request contains information for setting the alarm. The input is the server's scheduled time, and the output is the request sent to the user's device.

[1777] Step 2:

[1778] The device receives the alarm setting request from the server and uses the location information service to determine the current location. Specifically, it calls the device's GPS function to obtain latitude and longitude data. This location information is used as input, and the output is to save the location information in the device's internal memory.

[1779] Step 3:

[1780] The device sends a request to the weather information API based on the identified current location. The request includes latitude and longitude parameters. The input is location data, and the output is a request to the weather information API.

[1781] Step 4:

[1782] Receives a response from the weather information API and analyzes its contents. Specifically, it obtains data such as the current weather conditions and temperature. The input is the response data from the API, and the output is the analyzed weather information.

[1783] Step 5:

[1784] The device uses a camera and microphone to capture the user's facial expressions and voice, which are then analyzed by the emotion engine. The emotion engine then determines the user's emotional state based on this data. The input is the user's facial expressions and voice data, and the output is the determined emotional information.

[1785] Step 6:

[1786] The device sends the acquired weather information and emotion information to the server. Specifically, it uses an HTTP POST request and includes the header "Content-Type: application / json". The input is weather information and emotion information, and the output is data sent to the server.

[1787] Step 7:

[1788] The server receives weather information and emotion information sent from the device. Based on this data, it creates a prompt sentence to input into the music generation AI model. The input is weather information and emotion information, and the output is the generation of a prompt sentence. Specifically, it generates a sentence such as, "The user is feeling relaxed today. The current weather is sunny, and the temperature is 20 degrees. Based on these conditions, please generate a relaxing acoustic guitar song."

[1789] Step 8:

[1790] The music generation AI model generates new music based on a created prompt. The input is the prompt, and the output is the generated music data. Specifically, music files are generated in MP3 or WAV format.

[1791] Step 9:

[1792] The server sends the generated music data to the terminal. This is done using HTTP responses. The input is the music data, and the output is data sent to the user's terminal.

[1793] Step 10:

[1794] The device saves the received music data in local storage. The save destination is, for example, a directory called " / storage / emulated / 0 / Alarms / ". The input is music data, and the output is saved to local storage.

[1795] Step 11:

[1796] The device sets an alarm using stored music data. Using the alarm management application API, music is played at the set time (e.g., 7:00 AM). The input is the music data and the set time, and the output is the alarm setting.

[1797] Step 12:

[1798] At the set time, the device will play music to wake the user up. The input is setting the alarm and the output is playing music. The user can wake up comfortably to new music.

[1799] (Application example 2)

[1800] 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."

[1801] Conventional alarm systems wake users up with the same sound every time, which can lead to users becoming accustomed to the alarm sound and making it difficult to wake up. Furthermore, background music in stores tends to be fixed, and music is played without taking into account the emotions of customers and employees or external weather information, making it difficult to maximize the store atmosphere and customer experience.

[1802] 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 acquiring weather information, means for generating new music using a music generation AI based on the acquired weather information and emotional information, means for setting the generated music as an alarm sound or background music for the store, means for playing the generated music at the set alarm time or in real time, and means for acquiring emotional information of customers and employees. This makes it possible to generate appropriate music according to the emotional state of the user or customer and the weather information, allowing for a comfortable awakening and providing an optimal store atmosphere.

[1803] "Weather information" refers to current and near-future weather conditions and meteorological data such as temperature, precipitation, and wind speed.

[1804] "Emotion information" is data that represents the psychological state or emotions of a user or customer, and is classified into emotion categories such as "happy," "relaxed," and "excited."

[1805] "Music generation AI" is an artificial intelligence system that automatically generates new music by setting parameters based on weather information and emotional information.

[1806] An "alarm sound" is music or sound that is played to wake the user up at a specified time.

[1807] "BGM" is an abbreviation for background music, and refers to the background music played in indoor spaces such as stores and commercial facilities.

[1808] A "server" is a computing device that provides specific services and data processing over a network and serves client devices.

[1809] "Device" refers to a hardware device that collects user or customer emotions and weather information and plays generated music. Examples include smartphones, smart glasses, head-mounted displays, and robots.

[1810] "Location information" is data that indicates the current geographical location of a user or a store and is expressed in the form of latitude and longitude.

[1811] A "weather information API" is an application programming interface that provides weather information over the web and is a means for obtaining weather data.

[1812] An "emotion analysis engine" is software that analyzes data obtained from input devices such as cameras and microphones and identifies the emotional state of users or customers.

[1813] "HTTP protocol" is an abbreviation for Hypertext Transfer Protocol, an Internet protocol for data communication.

[1814] "Music parameters" are set values ​​that determine the characteristics of music, and include tempo, key, instrument composition, and the like.

[1815] This invention is a system that uses music generation AI to generate new music based on weather information and emotional information, and plays it as an alarm sound or background music in a physical store. Specifically, it is implemented using a server and a terminal.

[1816] System configuration

[1817] The system consists of the following main components:

[1818] Weather information acquisition means: Uses a weather information API (e.g., OpenWeatherMap) to acquire weather data based on the terminal's current location.

[1819] Emotion information acquisition means: An emotion analysis engine that uses cameras and microphones to analyze the emotional state of users, store customers, and employees.

[1820] Music generation method: Based on the weather and emotional information, the music generation AI generates new music. The generated music is saved in MP3 or WAV format.

[1821] Alarm / BGM setting method: The generated music is set as an alarm sound or background music in the store. Devices such as smartphones, smart glasses, head-mounted displays, and robots are used.

[1822] Playback method: Play the generated music at a specified time or in real time.

[1823] Server Processing

[1824] The server has the following functions:

[1825] Sending an alarm setting request: Send an alarm setting request to the client device at a specific time every day (e.g., 10:00 a.m.), which wakes up the user or store's system and collects the appropriate data.

[1826] Music generation: Music parameters are set based on received weather and emotional information, and new music is generated using music generation AI.

[1827] Sending music data: The generated music data is sent to the device so that it can be used as an alarm sound or background music.

[1828] Terminal handling

[1829] The main processing of the terminal is as follows:

[1830] Obtaining location information: Use GPS to determine current location information, and send it to a weather information API to obtain weather information for the target area.

[1831] Acquiring emotional information: Emotional information of users and customers is acquired using a camera or microphone and sent to the server.

[1832] Receiving and storing music data: Receives music data sent from the server and stores it in local storage.

[1833] Setting and playing alarms and background music: Set the generated music as an alarm sound or background music and play it at a specified time or in real time.

[1834] Examples of specific examples and prompts

[1835] The actual usage scenario is described below.

[1836] Specific examples

[1837] The flow when Store A starts the system at 10:00 in the morning while preparing to open is as follows.

[1838] 1. The server sends a "BGM setting request" to the terminal at store A.

[1839] 2. The device receives the request and uses GPS to determine its current location. For example, it may determine that it is in Shibuya Ward, Tokyo.

[1840] 3. The device accesses the weather information API and obtains weather information for Shibuya Ward, Tokyo. For example, it obtains weather information such as "sunny, temperature 25 degrees."

[1841] 4. The emotion analysis engine analyzes the employee's emotions and determines that they are "energetic and cheerful."

[1842] 5. The device sends weather information and emotion information to the server.

[1843] 6. The server asks the music generation AI to create a "lively and cheerful song suitable for a sunny day."

[1844] 7. The server sends the generated music data to the device. For example, lively pop music is generated.

[1845] 8. The device stores the music data locally and then plays it on the store's sound system.

[1846] 9. The music in the store creates a lively and cheerful atmosphere, making customers feel comfortable.

[1847] Prompt Sentence Examples

[1848] Weather: Sunny, 25 degrees

[1849] Emotional information: Lively and cheerful

[1850] Generated Music Style: Pop

[1851] Generated music tempo: Fast

[1852] In this way, appropriate music is generated according to the emotional state of the user or customer and weather information, thereby providing a pleasant awakening and an optimal store atmosphere.

[1853] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1854] Step 1:

[1855] The server sends an alarm setting request to the client device at a specific time every day (e.g., 10:00 a.m.). This request is sent using the HTTP protocol and contains the message "Request to set alarm." The input is the specified time, and the output is the alarm setting request message.

[1856] Step 2:

[1857] The device receives an alarm setting request from the server and uses GPS to determine the current location. The input is the alarm setting request message, and the output is the current location information (latitude and longitude). Specifically, the device's location information service is called to obtain the latitude and longitude.

[1858] Step 3:

[1859] The device sends a request to a weather information API (e.g., OpenWeatherMap) based on its current location information to obtain weather information for the target area. This request includes latitude and longitude parameters. The input is the current location information, and the output is weather information.

[1860] Step 4:

[1861] The device receives weather information from the weather information API. This information includes the weather condition (sunny, rainy, etc.) and temperature. The input is the response from the weather information API, and the output is the specific weather information.

[1862] Step 5:

[1863] The device uses a camera and microphone to obtain emotional information from the user or customer through an emotion analysis engine. The input is data from the camera or microphone, and the output is analyzed emotional information. Specifically, facial expression analysis and voice analysis technologies are used.

[1864] Step 6:

[1865] The device combines the acquired weather information and emotion information and sends it to the server. The input is weather information and emotion information, and the output is request data to the server. Specifically, the weather information and emotion information are sent to the server as parameters using the HTTP protocol.

[1866] Step 7:

[1867] The server initializes the music generation AI and sets the music parameters based on the received weather and emotional information. Further fine-tuning is made based on emotional information, such as bright and cheerful music for sunny days and relaxing music for rainy days. The input is weather information and emotional information, and the output is the set music parameters.

[1868] Step 8:

[1869] The server generates new music based on the set parameters using music generation AI. This music is saved in MP3 or WAV format, for example. The input is the music parameters, and the output is the generated music data. Specifically, the AI ​​model generates music by inputting prompts.

[1870] Step 9:

[1871] The server sends the generated music data to the device. This is also done using HTTP responses. The input is the generated music data, and the output is the transmission of the music data to the device.

[1872] Step 10:

[1873] The device receives the music data sent from the server and stores it in local storage. The input is music data, and the output is storage in local storage.

[1874] Step 11:

[1875] The device uses the received music data to set alarms and background music for the store. Music is played at the set time or in real time through an alarm application or sound system. The input is music data, and the output is alarm and background music settings. Specifically, this includes scheduler functions and sound system settings.

[1876] Step 12:

[1877] The device plays music data stored on it at the set alarm time or in real time. This allows users to wake up to new music or enjoy appropriate background music in the store. The input is the set timing, and the output is music playback.

[1878] 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.

[1879] 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.

[1880] 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.

[1881] 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.

[1882] FIG. 9 is a diagram illustrating 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 actions 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.

[1883] 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.

[1884] 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).

[1885] 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.

[1886] 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."

[1887] 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.

[1888] 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).

[1889] 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.

[1890] 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.

[1891] 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.

[1892] 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.

[1893] 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.

[1894] 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.

[1895] 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.

[1896] 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.

[1897] 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.

[1898] 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.

[1899] The following is further disclosed regarding the above embodiment.

[1900] (Claim 1)

[1901] A means for obtaining weather information;

[1902] A means to generate new music using music generation AI based on the acquired weather information, and

[1903] means for setting the generated music as an alarm sound;

[1904] a means for playing the generated music at the set alarm time;

[1905] A system including:

[1906] (Claim 2)

[1907] 10. The system of claim 1, further comprising means for determining a current location of the user when obtaining weather information.

[1908] (Claim 3)

[1909] 2. The system of claim 1, further comprising means for setting parameters of the music to be generated based on weather information.

[1910] "Example 1"

[1911] (Claim 1)

[1912] A means for obtaining weather information;

[1913] A means to generate new music using music generation AI based on the acquired weather information, and

[1914] means for setting the generated music as an alarm sound;

[1915] a means for playing the generated music at the set alarm time;

[1916] means for determining a user's current location;

[1917] A means for setting music parameters to the music generation AI from the device;

[1918] means for transmitting the generated music data to a terminal;

[1919] A means for storing the generated music data in local storage;

[1920] A system including:

[1921] (Claim 2)

[1922] 10. The system of claim 1, further comprising means for determining a current location of the user when obtaining weather information.

[1923] (Claim 3)

[1924] 2. The system of claim 1, further comprising means for setting parameters of the music to be generated based on weather information.

[1925] "Application Example 1"

[1926] (Claim 1)

[1927] A means for obtaining weather information;

[1928] A means to generate new music using music generation AI based on the acquired weather information, and

[1929] means for setting the generated music as an alarm sound;

[1930] a means for playing the generated music at the set alarm time;

[1931] a means for setting parameters of the music to be generated based on weather information;

[1932] means for determining a user's current location;

[1933] means for generating prompts for the music generation AI and generating music based on the prompts;

[1934] A system including:

[1935] (Claim 2)

[1936] 10. The system of claim 1, further comprising means for determining a current location of the user when obtaining weather information.

[1937] (Claim 3)

[1938] The system of claim 1, further comprising a function for adaptively optimizing music generation based on daily wake-up data.

[1939] "Example 2: Combining Emotion Engines"

[1940] (Claim 1)

[1941] A means for obtaining weather information;

[1942] A means for acquiring a user's emotion using an emotion engine that recognizes the user's emotion;

[1943] A means for generating new music using a music generation AI model based on the acquired weather information and user emotional information;

[1944] means for setting the generated music as an alarm sound;

[1945] a means for playing the generated music at the set alarm time;

[1946] A system including:

[1947] (Claim 2)

[1948] 10. The system of claim 1, further comprising means for determining a current location of the user when obtaining weather information.

[1949] (Claim 3)

[1950] 2. The system according to claim 1, further comprising means for setting parameters of the music to be generated based on weather information and emotional information of the user.

[1951] "Application example 2 when combining emotion engines"

[1952] (Claim 1)

[1953] A means for obtaining weather information;

[1954] A means for generating new music using music generation AI based on the acquired weather information and emotional information;

[1955] A means to set the generated music as an alarm sound or background music in the store,

[1956] a means for playing the generated music at the set alarm time or in real time;

[1957] A means of obtaining emotional information from customers and employees,

[1958] A system including:

[1959] (Claim 2)

[1960] 10. The system of claim 1, further comprising means for determining a current location of the user when obtaining weather information.

[1961] (Claim 3)

[1962] 10. The system of claim 1, further comprising means for setting parameters of the music to be generated based on weather information and emotion information. [Explanation of symbols]

[1963] 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. A means for obtaining weather information; A means to generate new music using music generation AI based on the acquired weather information, and means for setting the generated music as an alarm sound; a means for playing the generated music at the set alarm time; A system including:

2. 2. The system of claim 1, further comprising means for determining a user's current location when obtaining weather information.

3. 2. The system of claim 1, further comprising means for setting parameters of the music to be generated based on weather information.

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