system

Abstract

We provide the system. [Solution] A means of obtaining voice or text data input from the user, A means for analyzing the acquired data and generating music content, Means for generating visual content based on the aforementioned music content, A means of checking generated music and visual content in accordance with media science, Means for automatically transmitting the aforementioned music content and visual content to a platform on an electronic communication network, A means to enable real-time content creation on devices accessible to users, A system that includes this.

Description

Technical Field

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

Background Art

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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Music production requires specialized skills and expensive equipment, which makes it difficult for many amateur musicians and individual creators to materialize their ideas. Therefore, there is a need to provide a means that allows anyone to easily produce high-quality music and music videos and widely share them. Furthermore, it is necessary to establish a process for automatically publishing on the network while ensuring copyright confirmation and content security.

Means for Solving the Problems

[0005] This invention provides a system that generates music data based on voice or text input from a user, and further generates video based on this music data. This system has the functionality to automatically upload the generated content to social media and video platforms after content moderation and safety checks. It also includes means for users to easily publish their own works and receive notifications. This enables the rapid creation and sharing of high-quality music and video content without requiring specialized knowledge.

[0006] A "user" is an entity that operates the system and provides voice or text input.

[0007] "Voice or text input data" refers to raw voice or text information that the user provides to the system for music generation.

[0008] "Means of acquisition" refers to a method or device for incorporating user input data into the system.

[0009] "Means of analysis" refers to a method or apparatus that processes data to generate music data based on acquired input data.

[0010] "Music data" refers to audible sound information generated based on analyzed input information.

[0011] "Means of generation" refers to a method or device for creating new data (such as music or video) from the analysis results.

[0012] "Video data" refers to visual information that is represented based on music data.

[0013] "Content moderation" is the process of ensuring that generated content does not infringe on copyrights or contain inappropriate material.

[0014] "The "medium on the network" refers to a platform for publicly releasing content via the Internet."

[0015] "The "means for automatically uploading" refers to a method or device for posting generated music data and video data to a medium on the network without human intervention."

[0016] "The "means for notification" refers to a method or device for transmitting information from the system to the user."

Brief Description of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment." [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment." [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment." [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment." [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment." [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment." [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment." [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment." [Figure 9] It shows an emotion map to which a plurality of emotions are mapped." [Figure 10] It shows an emotion map to which a plurality of emotions are mapped." [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1." [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0021] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

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

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0034] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

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

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

[0038] This invention provides a system that simplifies music production, enabling even users without specialized knowledge to generate and widely publish high-quality music content. This system efficiently processes audio or text data provided by the user and generates music and video.

[0039] Users input their humming or lyric ideas using devices such as smartphones or PCs. This allows users to easily take their first steps into music production. The device converts the input data into an appropriate format and sends it to the server. The server analyzes the received data and creates a finished song using an AI music generation engine.

[0040] For the generated music, the server utilizes video generation AI to visualize the musical themes and emotions, creating a music video. The generated content is then subjected to content moderation by the server, with automatic checks for safety and copyright.

[0041] The completed music and video data are automatically uploaded by the server to major social networking services and video platforms. This allows users to quickly and widely share their work. After publication, the server notifies the user that the upload is complete and provides information to view the publication results.

[0042] For example, if a user records and sends a humming tune via a smartphone app, the server analyzes the audio and generates a song with a specific melody pattern. Then, a video generation AI creates visual content that aligns with the song's theme, and the finished content is posted to social media. This entire process allows users to share their music projects with the world in just a few minutes.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user inputs lyric ideas as humming or text using their own device. The device converts the input audio into the appropriate digital format, while saving the text as digital data.

[0046] Step 2:

[0047] The terminal compresses the converted audio and text data and sends it to the server using a secure communication protocol.

[0048] Step 3:

[0049] The server passes the received audio data to a speech recognition engine, which analyzes the characteristics of the sound. Based on the analysis, a melody generation AI creates a musical pattern. Additionally, the text data is passed to a natural language processing engine, which generates lyrics appropriate to the context.

[0050] Step 4:

[0051] The server integrates the acquired melody and lyric data and uses music generation AI to complete the song. Instrument selection and arrangement are also handled automatically.

[0052] Step 5:

[0053] After the song is completed, the server hands it over to a video generation AI, which automatically generates a music video based on the song's style and lyrics.

[0054] Step 6:

[0055] The server performs content moderation on the generated content. This is a process that includes copyright checks and filtering of inappropriate content.

[0056] Step 7:

[0057] The server automatically uploads music and videos that pass the inspection to major social media and video platforms. This makes the works available to audiences worldwide.

[0058] Step 8:

[0059] The server notifies the user that the content has been successfully uploaded. The notification includes a link to the published work and information to check viewer reactions.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] Traditional methods of music and video production require specialized knowledge and skills, and are time-consuming and labor-intensive. Therefore, it is difficult for the average user to easily create and publish high-quality music and visual media, limiting the scope of creativity.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for acquiring information via an input device, means for analyzing the acquired information and generating music information, and means for generating visual information from the music information. This makes it possible for even ordinary users to easily generate music and videos and quickly publish them to a wide audience.

[0065] An "input device" is a physical or virtual interface used by a user to provide information.

[0066] "Information" refers to materials provided by users, such as audio or text data.

[0067] "Song information" refers to music data generated based on acquired information.

[0068] "Visual information" refers to video data generated based on music information.

[0069] "Evaluation and verification" is the process of automatically or manually checking that the generated data is appropriate and secure.

[0070] An "information and communication network" is a digital network where data is sent and received.

[0071] "Transmission" refers to the act of transferring generated data to a specified medium or platform.

[0072] A "melody" is a melodic line in generated music data, particularly one that is formed along with the pitch and temporal progression of notes.

[0073] In implementing this invention, the user utilizes a terminal such as a smartphone or PC. Information such as voice and text provided by the user is collected via the terminal's input device. The terminal converts this input data into a processable digital format, reduces unnecessary noise and adjusts the format, and then transmits it to the server.

[0074] The server receives the information and performs analysis using a generative AI model. This AI model receives instructions from the user regarding the style and emotion they intend to create based on the provided information. For example, by giving the AI ​​model the prompt "Generate an energetic and moving rock song," it can generate a melody and accompaniment that meets the request.

[0075] After the music information is generated, the server uses video generation AI to design the visual information. This is the process of creating video data that aligns with the generated music, based on a theme specified by the user. For example, based on a prompt such as "space-themed visual content," it generates visually appealing videos.

[0076] Finally, the generated music and visual information is evaluated and verified on the server. After confirming that there are no safety or copyright issues, it is automatically transmitted to the designated media platform via the information and communication network. This transmission process allows users to widely publish their creations in a short amount of time.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The user uses a smartphone or PC to record audio data or input text data. The input device accurately captures the audio or text provided by the user and converts it into a digital format. The input for this process is the user's audio or text information, and the output is digital audio or text data.

[0080] Step 2:

[0081] The terminal performs noise reduction on the acquired digital audio data to generate clear audio data. In the case of text data, it adjusts the string format. In this step, the input is the output data from step 1, and the output is the improved digital audio data or formatted text data.

[0082] Step 3:

[0083] The terminal sends the adjusted digital audio or text data to the server via the internet. The input to this process is the output data from step 2, and the output is the audio or text data transferred to the server.

[0084] Step 4:

[0085] The server inputs the received data into the generation AI model and uses prompt statements to generate song information that reflects the user's intent. For example, it might use the prompt "Generate an energetic and moving rock song." The input for this step is the data and prompt statements transferred in step 3, and the output is the generated song information.

[0086] Step 5:

[0087] The server uses the generated music information to create visual information using a video generation AI. The video generation AI generates video that matches the theme of the music. The input to this process is the music information from step 4, and the output is the corresponding visual information.

[0088] Step 6:

[0089] The server evaluates and verifies music and visual information to eliminate inappropriate content. The input is the data generated in steps 4 and 5, and the output is evaluated and safe content.

[0090] Step 7:

[0091] The server automatically uploads verified music and visual information to the configured media platform. The input is evaluated data, and the output is publicly available content.

[0092] Step 8:

[0093] The server sends a notification to the user that publication is complete and provides information such as the content viewing status. The input is the result of step 7, and the output is the notification to the user and the viewing data.

[0094] (Application Example 1)

[0095] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0096] Music production requires specialized knowledge and tools, making it difficult for many ordinary users to easily create and publish music and video content. Furthermore, the lack of efficient means to share generated content presents a challenge, as users face the challenge of having to expedite and make their creations widely available.

[0097] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0098] In this invention, the server includes means for acquiring voice or text data input from a user, means for analyzing the acquired data and generating music content, and means for generating visual content based on the music content. This makes it possible for users to easily create music and video content without specialized knowledge and to quickly publish it through an electronic communication network.

[0099] "User" refers to any person who uses the system of the present invention for the purpose of creating and sharing music and visual content.

[0100] "Audio or text data" refers to digital information, including melodies, lyrics, or related linguistic information, that are entered by the user.

[0101] "Music content" refers to songs and sound files generated based on audio or text data.

[0102] "Visual content" refers to video files and visual data generated based on music content.

[0103] "Means of checking in accordance with media science" refers to a function that automatically evaluates generated music and visual content according to appropriate content moderation standards to ensure legality and quality.

[0104] A "platform on an electronic communication network" refers to a digital infrastructure such as social networking services or video sharing services used to publish or distribute generated content online.

[0105] "Digitized voice information" refers to data obtained by analyzing voice data entered by a user in a digital format and converting it into a format that can be processed on a computer.

[0106] This invention constructs a system that facilitates the creation and publication of music and visual content. Users can send their voice or entered text data to the system using mobile communication devices such as smartphones and tablet devices. The device runs commonly available speech recognition software, such as Google® Cloud Speech-to-Text API, to convert the voice data received from the user into digitized speech information.

[0107] The server receives this digitized audio information and text data and generates music content using a generative AI model. For music content generation, it utilizes the OpenAI® API to assemble appropriate melodies and sound patterns. Furthermore, based on the generated music content, it employs AI such as DeepArt to create visual content that aligns with the emotions and themes of the song.

[0108] Furthermore, the server checks the generated music and visual content in accordance with media science standards. After the check is complete, the server has the functionality to automatically transmit this content to platforms on electronic communication networks, specifically social networking services and video sharing services. This allows users to widely publish their work in a short amount of time.

[0109] As a concrete example, users can record melodies they come up with while out and about using the "Pocket Music Maker" app, and then instantly generate music and visual content based on those recordings, which they can then post to Instagram. An example of a prompt message used when generating music might be: "Based on this text, please create an upbeat, catchy melody. Please create a song that evokes the image of 'wind' mentioned in the lyrics, and a video that expresses that."

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] Users input voice or text data through an application using a smartphone or tablet. This input includes recordings or text entries of humming or lyrics. The device converts the input voice data into digitized speech information using the Google Cloud Speech-to-Text API. This makes the voice ready to be sent to the server in digital data format.

[0113] Step 2:

[0114] The server receives digitized audio information or text data sent from the terminal. Based on this input data, it generates music content using the OpenAI API. Specifically, a generation AI model analyzes the input data and arranges musical melodies and harmonies to produce a musical output.

[0115] Step 3:

[0116] Based on the generated music content, the server uses AI such as DeepArt to create visual content. Here, it generates videos that align with the emotional elements and themes of the music. The input is music content, and the output is video data that visually represents that music.

[0117] Step 4:

[0118] The server performs content moderation on the generated music and visual content. Specifically, it checks whether the generated content is legal and complies with media standards. The input is the generated music and video data, and the output is the checked data.

[0119] Step 5:

[0120] Verified music and visual content is automatically uploaded by the server to network platforms such as social networking services and video sharing services. The input here is moderated content data, and the output is the content published on the platform. Users can check the publication status of their work through a dedicated app.

[0121] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0122] This invention is a system that recognizes emotions from voice or text input provided by the user and reflects those emotions in the generation of music and video. This system utilizes an emotion engine to determine the user's intentions and emotional state, and adjusts the content based on the results to generate more personal and emotionally appealing works.

[0123] Users input ideas into the system using their smartphones or PCs, either by humming or writing them down as text. The device converts this input into an appropriate digital format and sends it to the server. The server analyzes the audio data using a speech recognition engine and extracts emotions from the user's voice and linguistic characteristics through an emotion engine.

[0124] The server adjusts the music generation process based on the extracted emotional data. Specifically, it incorporates emotional data into the selection of melody, tempo, and harmony. Meanwhile, emotions are also considered during the lyric generation process, and natural language processing is performed so that the content and structure of the lyrics change according to the emotions.

[0125] Once the music is complete, the server moves on to the video generation process, creating a video while reflecting emotional data in the mood and color of the visuals. In this way, content is produced in which emotions are consistently reflected in both the music and the visuals.

[0126] Furthermore, the completed content undergoes content moderation to ensure safety and copyright, and is then automatically uploaded to major social media and video platforms by the server. The server then notifies users that the content has been published and provides relevant information.

[0127] For example, if a user hums a tune while talking about an emotional experience they've had through a smartphone app, the server analyzes this using an emotion engine. If the emotion is recognized as "joy," it automatically generates a cheerful melody and positive lyrics, creating a music video with vibrant and hopeful visuals. This allows users to quickly distribute music projects that richly express their emotions.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] Users record themselves humming or input lyric ideas as text using their smartphone or PC. The device converts the audio into digital data and saves the text data accurately in the data format.

[0131] Step 2:

[0132] The terminal compresses the converted and stored audio and text data and sends it to the server using a secure communication protocol.

[0133] Step 3:

[0134] The server processes the received audio data through a speech recognition engine and sends the data, along with the melody, to an emotion engine to analyze the emotions in the user's voice. The emotion is identified based on the tone and pitch of the voice extracted from the audio.

[0135] Step 4:

[0136] The server applies a natural language processing engine to the text data to understand emotional keywords and context from the text. Here too, an emotion engine is used to identify the emotions embedded in the text.

[0137] Step 5:

[0138] The server generates music based on the identified emotions. It adjusts the tempo, tone, and instrumentation of the melody according to the emotion, and also reflects the emotion in the lyrics to coordinate the entire song.

[0139] Step 6:

[0140] After the song is completed, the server applies its emotional data to the video generation engine, using it to determine the atmosphere and color scheme of the music video. This results in the creation of visuals that match the emotions expressed.

[0141] Step 7:

[0142] The server checks the completed music and video data with a content moderation engine to ensure there are no copyright infringements or inappropriate elements. If there are no problems with this process, it proceeds to the next step.

[0143] Step 8:

[0144] The server automatically uploads verified content to major social media and video platform networks.

[0145] Step 9:

[0146] The server notifies the user that the generated content has been successfully uploaded. The user can then view the published content via the provided link.

[0147] (Example 2)

[0148] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0149] Traditional music and video production often fails to adequately reflect individual emotions and intentions during the creative process, making it difficult to generate highly personalized content. Furthermore, the copyright and security checks required for content uploads are cumbersome, necessitating automation. Moreover, the need to quickly share content that expresses one's emotions remains unmet.

[0150] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0151] In this invention, the server includes means for receiving audio or descriptive information from a user, means for generating music and video information using extracted emotional information, and means for reviewing the content of the generated music and video information. This makes it possible to quickly and automatically generate and share highly personalized content based on the emotions of individual users.

[0152] A "user" is the entity that inputs voice or written information into the system.

[0153] "Voice information" refers to data provided by users through voice.

[0154] "Descriptive information" refers to data provided by the user in text format.

[0155] "Emotional information" refers to data about emotions extracted from audio or written information.

[0156] "Music information" refers to data related to music that is generated based on emotional information.

[0157] "Visual information" refers to visual data generated based on music information.

[0158] "Content review" is the process of verifying whether the generated information is safe and appropriate.

[0159] A "communication network" is a network infrastructure used for sending and receiving information.

[0160] A "medium" is the platform to which the generated information is transmitted.

[0161] A description of embodiments for carrying out the present invention will be provided.

[0162] Users input voice or written information into the system using devices such as smartphones or personal computers. Specifically, they can record voice data or input text data using smartphone applications or desktop software. The devices are equipped with voice processing software for speech recognition and document editing software for text processing. For speech recognition, software is used to convert the voice data into digital audio file formats (WAV or MP3).

[0163] The device transmits the input voice or written information to the server via the internet. The server uses a speech recognition engine to convert the voice data into text and extracts the user's emotional information through an emotion engine. Sentiment analysis utilizes generative AI models to determine emotions from the user's voice tone and text. Various machine learning algorithms and AI models are used in this process.

[0164] Based on the extracted emotional information, a music generation engine generates musical information. This creates musical data with melodies, tempos, and harmonies based on emotions, and specific algorithms and modules (e.g., music generation software) can be used for music generation. Furthermore, a video generation engine generates video information based on the generated musical information. Video generation uses video processing algorithms to set the color tone and mood to match the emotions.

[0165] The completed music and video information is subjected to a content review process by the server. This process includes checking the safety of the content and verifying copyright. After the content passes the review, the server automatically sends the generated information to social media and video sharing platforms. This notifies users that the generated content has been published and provides them with relevant links.

[0166] For example, if a user uses a smartphone app to input a hummed tune while talking about an emotional experience they've had, the server analyzes it using an emotion engine. If the emotion is recognized as "joy," the server automatically generates a cheerful melody and positive lyrics, creating a music video with vibrant and hopeful visuals.

[0167] An example of a prompt message is: "Receive voice input from the user, analyze their emotions, and generate a joyful melody and lyrics, along with corresponding visuals."

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] Users input audio or written information using a smartphone or personal computer. Specific actions might include pressing a record button on the application to hum a tune or typing emotionally expressive text into a text input field. The output at this stage is the user's input data itself.

[0171] Step 2:

[0172] The device converts user voice input into digital audio files. It also uses speech recognition software to convert the voice data into text data. This conversion outputs clear digital data that can be used as a template.

[0173] Step 3:

[0174] The device sends digital data, either voice or text, to the server. Specifically, this involves uploading the data to the server's API endpoint via an HTTP request. The output is the digital data sent to the server.

[0175] Step 4:

[0176] The server further analyzes the received audio data using a speech recognition engine and converts it into text data. During this process, it analyzes the tone and linguistic features of the speech and extracts emotional information. The output is data that identifies the user's emotions.

[0177] Step 5:

[0178] The server uses emotional information to activate a music generation engine and generate music. It adjusts the melody, tempo, and harmony according to the emotion. Specifically, it generates a music pattern corresponding to the emotion. The output is the generated music file.

[0179] Step 6:

[0180] The server uses a video generation engine to create video information based on the generated music information. Visual effects and color tones are adjusted based on emotional information. Specifically, an appropriate video sequence is designed by AI. The output is video data.

[0181] Step 7:

[0182] The server then submits the completed music and video information to a content review process. This process checks copyright and content safety. Specifically, an AI model analyzes the content and confirms that there are no problems. The output is the final content that has passed the review.

[0183] Step 8:

[0184] The server automatically uploads the final content to social media and video platforms. This includes specific actions such as posting videos using each platform's API. The output is the content published on each platform.

[0185] (Application Example 2)

[0186] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0187] Conventional music and video generation systems have struggled to create content that reflects user emotions in real time. Furthermore, smoothly distributing the generated content over a network based on individual emotions has also been difficult. This has resulted in a limited user experience and the inability to quickly share personalized content that responds to emotions.

[0188] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0189] In this invention, the server includes means for acquiring voice or text input data from a user, means for analyzing the acquired input data and extracting emotions, and means for generating music data and video data based on the extracted emotions. This makes it possible to quickly generate personalized music and video content that reflects the user's emotions and distribute it over a network.

[0190] A "user" is an individual or organization that provides voice or text input data using the system.

[0191] "Emotion" refers to the mental or emotional state that a user expresses to the system through input data, and is information used for content generation.

[0192] "Music data" refers to information about a song generated based on the user's emotions, and is digital data that includes melody and lyrics.

[0193] "Video data" refers to visual content generated based on music data, and is a digital format of data where colors and moods are designed according to emotions.

[0194] "Content verification" is the process of confirming the safety and appropriateness of generated music and video data and preparing it for distribution.

[0195] "Digital media on information networks" refers to online platforms and services on which generated music and video data are distributed.

[0196] A "melody" is a major element of music, formed by the order and arrangement of sounds contained in musical data.

[0197] "Lyrics" are a portion of the text contained within music data, and are linguistic content generated based on the user's emotions.

[0198] The system that realizes this invention mainly consists of a server and a user terminal. The user inputs voice or text data using a terminal such as a smartphone or personal computer. This data is converted into a digital format by the terminal and transmitted to the server.

[0199] On the server side, a speech recognition engine is used to convert the input speech data into text, and emotions are extracted through an emotion analysis engine. Tools such as Google Speech-to-Text and IBM Watson® Tone Analyzer are used in this process. The extracted emotions are then reflected in the generation of musical melodies and lyrics using a generative AI model. For example, OpenAI's GPT can be used for lyric generation.

[0200] Music generation uses music generation software such as Amper Music to create melodies based on emotions. Furthermore, video generation engines such as RunwayML are utilized to generate videos that respond to emotions. This results in content that consistently reflects the user's emotions.

[0201] The completed music and video data are verified for security and appropriateness through content verification tools before being distributed to digital media on the information network. After distribution, users are notified that the content has been uploaded and can share it on social media and other platforms.

[0202] As a concrete example, imagine a situation where a user "hums a tune while talking about their first hot air balloon experience." The server recognizes this as "excitement," generates a lively melody and lyrics that evoke a sense of freedom, and creates content that combines these with visuals of the balloon floating in the sky.

[0203] An example of a prompt for a generative AI model would be, "Generate lyrics that convey a sense of freedom, based on the emotions contained in this audio clip." This would allow users to easily create and share content that richly expresses their personal experiences.

[0204] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0205] Step 1:

[0206] The user inputs voice or text into a device such as a smartphone or computer. The input data is converted into a digital format by the device and sent to the server. In the case of voice input, the device's microphone records it, saves it as an audio file, and prepares it for the next processing step.

[0207] Step 2:

[0208] The server uses a speech recognition engine to convert the transmitted audio data into text. In this process, the audio data is taken as input and converted into text data format. This text data then becomes available for use in the next sentiment extraction step.

[0209] Step 3:

[0210] The server uses a sentiment analysis engine to extract emotions from text data. The input is text data, and the output is extracted emotion data. The sentiment analysis engine calculates linguistic features to identify emotions.

[0211] Step 4:

[0212] The server inputs emotional data into a generative AI model and generates corresponding lyrics. The input consists of emotional data and, in some cases, user prompts, and the output is the generated lyrics text. The generative AI model generates lyrics using language patterns corresponding to the emotions.

[0213] Step 5:

[0214] The server uses music generation software to create emotionally-based musical melodies. The input is emotional data, and the output is musical data containing the melody. The music generation software determines the appropriate tempo and scale to express the emotion.

[0215] Step 6:

[0216] The server uses a video generation engine to generate video data that matches the music data. The input is music data and emotion data, and the output is video data with set visual mood and color settings.

[0217] Step 7:

[0218] The server verifies the generated music and video data using a content verification tool. The input is music and video data, and the output after verification is content that has been approved for publication.

[0219] Step 8:

[0220] The server automatically distributes authorized music and video content to digital media on the information network. In this step, verified content is used as input, and the data is processed for distribution across multiple platforms.

[0221] Step 9:

[0222] The server notifies the user that the created content has been uploaded. The input is information about the distributed content, and the output is a notification sent to the user's terminal. This notification allows the user to confirm the publication of the content on the platform.

[0223] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0224] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0225] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0226] [Second Embodiment]

[0227] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0228] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0229] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0230] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0231] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0232] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0233] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0234] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0235] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0236] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0237] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0238] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0239] This invention provides a system that simplifies music production, enabling even users without specialized knowledge to generate and widely publish high-quality music content. This system efficiently processes audio or text data provided by the user and generates music and video.

[0240] Users input their humming or lyric ideas using devices such as smartphones or PCs. This allows users to easily take their first steps into music production. The device converts the input data into an appropriate format and sends it to the server. The server analyzes the received data and creates a finished song using an AI music generation engine.

[0241] For the generated music, the server utilizes video generation AI to visualize the musical themes and emotions, creating a music video. The generated content is then subjected to content moderation by the server, with automatic checks for safety and copyright.

[0242] The completed music and video data are automatically uploaded by the server to major social networking services and video platforms. This allows users to quickly and widely share their work. After publication, the server notifies the user that the upload is complete and provides information to view the publication results.

[0243] For example, if a user records and sends a humming tune via a smartphone app, the server analyzes the audio and generates a song with a specific melody pattern. Then, a video generation AI creates visual content that aligns with the song's theme, and the finished content is posted to social media. This entire process allows users to share their music projects with the world in just a few minutes.

[0244] The following describes the processing flow.

[0245] Step 1:

[0246] The user inputs lyric ideas as humming or text using their own device. The device converts the input audio into the appropriate digital format, while saving the text as digital data.

[0247] Step 2:

[0248] The terminal compresses the converted audio and text data and sends it to the server using a secure communication protocol.

[0249] Step 3:

[0250] The server passes the received audio data to a speech recognition engine, which analyzes the characteristics of the sound. Based on the analysis, a melody generation AI creates a musical pattern. Additionally, the text data is passed to a natural language processing engine, which generates lyrics appropriate to the context.

[0251] Step 4:

[0252] The server integrates the acquired melody and lyric data and uses music generation AI to complete the song. Instrument selection and arrangement are also handled automatically.

[0253] Step 5:

[0254] After the song is completed, the server hands it over to a video generation AI, which automatically generates a music video based on the song's style and lyrics.

[0255] Step 6:

[0256] The server performs content moderation on the generated content. This is a process that includes copyright checks and filtering of inappropriate content.

[0257] Step 7:

[0258] The server automatically uploads music and videos that pass the inspection to major social media and video platforms. This makes the works available to audiences worldwide.

[0259] Step 8:

[0260] The server notifies the user that the content has been successfully uploaded. The notification includes a link to the published work and information to check viewer reactions.

[0261] (Example 1)

[0262] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0263] Traditional methods of music and video production require specialized knowledge and skills, and are time-consuming and labor-intensive. Therefore, it is difficult for the average user to easily create and publish high-quality music and visual media, limiting the scope of creativity.

[0264] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0265] In this invention, the server includes means for acquiring information via an input device, means for analyzing the acquired information and generating music information, and means for generating visual information from the music information. This makes it possible for even ordinary users to easily generate music and videos and quickly publish them to a wide audience.

[0266] An "input device" is a physical or virtual interface used by a user to provide information.

[0267] "Information" refers to materials provided by users, such as audio or text data.

[0268] "Song information" refers to music data generated based on acquired information.

[0269] "Visual information" refers to video data generated based on music information.

[0270] "Evaluation and verification" is the process of automatically or manually checking that the generated data is appropriate and secure.

[0271] An "information and communication network" is a digital network where data is sent and received.

[0272] "Transmission" refers to the act of transferring generated data to a specified medium or platform.

[0273] A "melody" is a melodic line in generated music data, particularly one that is formed along with the pitch and temporal progression of notes.

[0274] In implementing this invention, the user utilizes a terminal such as a smartphone or PC. Information such as voice and text provided by the user is collected via the terminal's input device. The terminal converts this input data into a processable digital format, reduces unnecessary noise and adjusts the format, and then transmits it to the server.

[0275] The server receives the information and performs analysis using a generative AI model. This AI model receives instructions from the user regarding the style and emotion they intend to create based on the provided information. For example, by giving the AI ​​model the prompt "Generate an energetic and moving rock song," it can generate a melody and accompaniment that meets the request.

[0276] After the music information is generated, the server uses video generation AI to design the visual information. This is the process of creating video data that aligns with the generated music, based on a theme specified by the user. For example, based on a prompt such as "space-themed visual content," it generates visually appealing videos.

[0277] Finally, the generated music and visual information is evaluated and verified on the server. After confirming that there are no safety or copyright issues, it is automatically transmitted to the designated media platform via the information and communication network. This transmission process allows users to widely publish their creations in a short amount of time.

[0278] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0279] Step 1:

[0280] The user uses a smartphone or a PC to record voice data or input text data. The input device accurately acquires the voice or text provided by the user and converts it into a digital format. The input of this process is the user's voice or text information, and the output is digital audio or string data.

[0281] Step 2:

[0282] The terminal performs noise reduction on the acquired digital voice data to generate clear audio data. In the case of text data, the string format is adjusted. In this step, the input is the output data of Step 1, and the output is improved digital audio data or formatted text data.

[0283] Step 3:

[0284] The terminal transmits the adjusted digital audio data or text data to the server via the Internet. The input of this process is the output data of Step 2, and the output is the audio or text data transferred to the server.

[0285] Step 4:

[0286] The server inputs the received data into the generative AI model and generates music information reflecting the user's intention using a prompt sentence. For example, a prompt such as "Generate an energetic and moving rock song" is used. The input of this step is the data transferred in Step 3 and the prompt sentence, and the output is the generated music information.

[0287] Step 5:

[0288] The server uses the generated music information to create visual information using a video generation AI. The video generation AI generates video that matches the theme of the music. The input to this process is the music information from step 4, and the output is the corresponding visual information.

[0289] Step 6:

[0290] The server evaluates and verifies music and visual information to eliminate inappropriate content. The input is the data generated in steps 4 and 5, and the output is evaluated and safe content.

[0291] Step 7:

[0292] The server automatically uploads verified music and visual information to the configured media platform. The input is evaluated data, and the output is publicly available content.

[0293] Step 8:

[0294] The server sends a notification to the user that publication is complete and provides information such as the content viewing status. The input is the result of step 7, and the output is the notification to the user and the viewing data.

[0295] (Application Example 1)

[0296] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0297] Music production requires specialized knowledge and tools, making it difficult for many ordinary users to easily create and publish music and video content. Furthermore, the lack of efficient means to share generated content presents a challenge, as users face the challenge of having to expedite and make their creations widely available.

[0298] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0299] In this invention, the server includes means for acquiring voice or text data input from a user, means for analyzing the acquired data and generating music content, and means for generating visual content based on the music content. This makes it possible for users to easily create music and video content without specialized knowledge and to quickly publish it through an electronic communication network.

[0300] "User" refers to any person who uses the system of the present invention for the purpose of creating and sharing music and visual content.

[0301] "Audio or text data" refers to digital information, including melodies, lyrics, or related linguistic information, that are entered by the user.

[0302] "Music content" refers to songs and sound files generated based on audio or text data.

[0303] "Visual content" refers to video files and visual data generated based on music content.

[0304] "Means of checking in accordance with media science" refers to a function that automatically evaluates generated music and visual content according to appropriate content moderation standards to ensure legality and quality.

[0305] A "platform on an electronic communication network" refers to a digital infrastructure such as social networking services or video sharing services used to publish or distribute generated content online.

[0306] "Digitized voice information" refers to data obtained by analyzing voice data entered by a user in a digital format and converting it into a format that can be processed on a computer.

[0307] This invention constructs a system that facilitates the generation and publication of music and visual content. Users can use a mobile communication terminal such as a smartphone or a tablet terminal to send their own voice or input text data to the system. The terminal runs commonly available speech recognition software such as the Google Cloud Speech-to-Text API to convert the voice data obtained from the user into digitized voice information.

[0308] The server receives this digitized voice information and text data, and uses a generation AI model to generate music content. To generate music content, the API of OpenAI is used to compose appropriate melodies and acoustic patterns. Also, based on the generated music content, to generate visual content, AI such as DeepArt is utilized to create videos along with the emotions and themes of the music.

[0309] Furthermore, the server checks the generated music content and visual content in accordance with media science. After the check is completed, the server has the function of automatically transmitting these contents to a platform on an electronic communication network, specifically, an SNS or a video sharing service. As a result, users can widely publish their works in a short time.

[0310] As a specific example, a melody that a user came up with in the street can be recorded in the "Pocket Music Maker" app, and based on it, music and visual content can be immediately generated and posted on Instagram. Examples of prompt sentences when generating music include "Based on this text, please create a catchy melody with a pop tune. Please create a music that imagines the 'wind' that appears in the lyrics and a video that expresses it."

[0311] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0312] Step 1:

[0313] Users input voice or text data through an application using a smartphone or tablet. This input includes recordings or text entries of humming or lyrics. The device converts the input voice data into digitized speech information using the Google Cloud Speech-to-Text API. This makes the voice ready to be sent to the server in digital data format.

[0314] Step 2:

[0315] The server receives digitized audio information or text data sent from the terminal. Based on this input data, it generates music content using the OpenAI API. Specifically, a generation AI model analyzes the input data and arranges musical melodies and harmonies to produce a musical output.

[0316] Step 3:

[0317] Based on the generated music content, the server uses AI such as DeepArt to create visual content. Here, it generates videos that align with the emotional elements and themes of the music. The input is music content, and the output is video data that visually represents that music.

[0318] Step 4:

[0319] The server performs content moderation on the generated music and visual content. Specifically, it checks whether the generated content is legal and complies with media standards. The input is the generated music and video data, and the output is the checked data.

[0320] Step 5:

[0321] Verified music and visual content is automatically uploaded by the server to network platforms such as social networking services and video sharing services. The input here is moderated content data, and the output is the content published on the platform. Users can check the publication status of their work through a dedicated app.

[0322] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0323] This invention is a system that recognizes emotions from voice or text input provided by the user and reflects those emotions in the generation of music and video. This system utilizes an emotion engine to determine the user's intentions and emotional state, and adjusts the content based on the results to generate more personal and emotionally appealing works.

[0324] Users input ideas into the system using their smartphones or PCs, either by humming or writing them down as text. The device converts this input into an appropriate digital format and sends it to the server. The server analyzes the audio data using a speech recognition engine and extracts emotions from the user's voice and linguistic characteristics through an emotion engine.

[0325] The server adjusts the music generation process based on the extracted emotional data. Specifically, it incorporates emotional data into the selection of melody, tempo, and harmony. Meanwhile, emotions are also considered during the lyric generation process, and natural language processing is performed so that the content and structure of the lyrics change according to the emotions.

[0326] Once the music is complete, the server moves on to the video generation process, creating a video while reflecting emotional data in the mood and color of the visuals. In this way, content is produced in which emotions are consistently reflected in both the music and the visuals.

[0327] Furthermore, the completed content undergoes content moderation to ensure safety and copyright, and is then automatically uploaded to major social media and video platforms by the server. The server then notifies users that the content has been published and provides relevant information.

[0328] For example, if a user hums a tune while talking about an emotional experience they've had through a smartphone app, the server analyzes this using an emotion engine. If the emotion is recognized as "joy," it automatically generates a cheerful melody and positive lyrics, creating a music video with vibrant and hopeful visuals. This allows users to quickly distribute music projects that richly express their emotions.

[0329] The following describes the processing flow.

[0330] Step 1:

[0331] Users record themselves humming or input lyric ideas as text using their smartphone or PC. The device converts the audio into digital data and saves the text data accurately in the data format.

[0332] Step 2:

[0333] The terminal compresses the converted and stored audio and text data and sends it to the server using a secure communication protocol.

[0334] Step 3:

[0335] The server processes the received audio data through a speech recognition engine and sends the data, along with the melody, to an emotion engine to analyze the emotions in the user's voice. The emotion is identified based on the tone and pitch of the voice extracted from the audio.

[0336] Step 4:

[0337] The server applies a natural language processing engine to the text data to understand emotional keywords and context from the text. Here too, an emotion engine is used to identify the emotions embedded in the text.

[0338] Step 5:

[0339] The server generates music based on the identified emotions. It adjusts the tempo, tone, and instrumentation of the melody according to the emotion, and also reflects the emotion in the lyrics to coordinate the entire song.

[0340] Step 6:

[0341] After the song is completed, the server applies its emotional data to the video generation engine, using it to determine the atmosphere and color scheme of the music video. This results in the creation of visuals that match the emotions expressed.

[0342] Step 7:

[0343] The server checks the completed music and video data with a content moderation engine to ensure there are no copyright infringements or inappropriate elements. If there are no problems with this process, it proceeds to the next step.

[0344] Step 8:

[0345] The server automatically uploads verified content to major social media and video platform networks.

[0346] Step 9:

[0347] The server notifies the user that the generated content has been successfully uploaded. The user can then view the published content via the provided link.

[0348] (Example 2)

[0349] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0350] Traditional music and video production often fails to adequately reflect individual emotions and intentions during the creative process, making it difficult to generate highly personalized content. Furthermore, the copyright and security checks required for content uploads are cumbersome, necessitating automation. Moreover, the need to quickly share content that expresses one's emotions remains unmet.

[0351] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0352] In this invention, the server includes means for receiving audio or descriptive information from a user, means for generating music and video information using extracted emotional information, and means for reviewing the content of the generated music and video information. This makes it possible to quickly and automatically generate and share highly personalized content based on the emotions of individual users.

[0353] A "user" is the entity that inputs voice or written information into the system.

[0354] "Voice information" refers to data provided by users through voice.

[0355] "Descriptive information" refers to data provided by the user in text format.

[0356] "Emotional information" refers to data about emotions extracted from audio or written information.

[0357] "Music information" refers to data related to music that is generated based on emotional information.

[0358] "Visual information" refers to visual data generated based on music information.

[0359] "Content review" is the process of verifying whether the generated information is safe and appropriate.

[0360] A "communication network" is a network infrastructure used for sending and receiving information.

[0361] A "medium" is the platform to which the generated information is transmitted.

[0362] A description of embodiments for carrying out the present invention will be provided.

[0363] Users input voice or written information into the system using devices such as smartphones or personal computers. Specifically, they can record voice data or input text data using smartphone applications or desktop software. The devices are equipped with voice processing software for speech recognition and document editing software for text processing. For speech recognition, software is used to convert the voice data into digital audio file formats (WAV or MP3).

[0364] The device transmits the input voice or written information to the server via the internet. The server uses a speech recognition engine to convert the voice data into text and extracts the user's emotional information through an emotion engine. Sentiment analysis utilizes generative AI models to determine emotions from the user's voice tone and text. Various machine learning algorithms and AI models are used in this process.

[0365] Based on the extracted emotional information, a music generation engine generates musical information. This creates musical data with melodies, tempos, and harmonies based on emotions, and specific algorithms and modules (e.g., music generation software) can be used for music generation. Furthermore, a video generation engine generates video information based on the generated musical information. Video generation uses video processing algorithms to set the color tone and mood to match the emotions.

[0366] The completed music and video information is subjected to a content review process by the server. This process includes checking the safety of the content and verifying copyright. After the content passes the review, the server automatically sends the generated information to social media and video sharing platforms. This notifies users that the generated content has been published and provides them with relevant links.

[0367] For example, if a user uses a smartphone app to input a hummed tune while talking about an emotional experience they've had, the server analyzes it using an emotion engine. If the emotion is recognized as "joy," the server automatically generates a cheerful melody and positive lyrics, creating a music video with vibrant and hopeful visuals.

[0368] An example of a prompt message is: "Receive voice input from the user, analyze their emotions, and generate a joyful melody and lyrics, along with corresponding visuals."

[0369] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0370] Step 1:

[0371] Users input audio or written information using a smartphone or personal computer. Specific actions might include pressing a record button on the application to hum a tune or typing emotionally expressive text into a text input field. The output at this stage is the user's input data itself.

[0372] Step 2:

[0373] The device converts user voice input into digital audio files. It also uses speech recognition software to convert the voice data into text data. This conversion outputs clear digital data that can be used as a template.

[0374] Step 3:

[0375] The device sends digital data, either voice or text, to the server. Specifically, this involves uploading the data to the server's API endpoint via an HTTP request. The output is the digital data sent to the server.

[0376] Step 4:

[0377] The server further analyzes the received audio data using a speech recognition engine and converts it into text data. During this process, it analyzes the tone and linguistic features of the speech and extracts emotional information. The output is data that identifies the user's emotions.

[0378] Step 5:

[0379] The server uses emotional information to activate a music generation engine and generate music. It adjusts the melody, tempo, and harmony according to the emotion. Specifically, it generates a music pattern corresponding to the emotion. The output is the generated music file.

[0380] Step 6:

[0381] The server uses a video generation engine to create video information based on the generated music information. Visual effects and color tones are adjusted based on emotional information. Specifically, an appropriate video sequence is designed by AI. The output is video data.

[0382] Step 7:

[0383] The server then submits the completed music and video information to a content review process. This process checks copyright and content safety. Specifically, an AI model analyzes the content and confirms that there are no problems. The output is the final content that has passed the review.

[0384] Step 8:

[0385] The server automatically uploads the final content to social media and video platforms. This includes specific actions such as posting videos using each platform's API. The output is the content published on each platform.

[0386] (Application Example 2)

[0387] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0388] Conventional music and video generation systems have struggled to create content that reflects user emotions in real time. Furthermore, smoothly distributing the generated content over a network based on individual emotions has also been difficult. This has resulted in a limited user experience and the inability to quickly share personalized content that responds to emotions.

[0389] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0390] In this invention, the server includes means for acquiring voice or text input data from a user, means for analyzing the acquired input data and extracting emotions, and means for generating music data and video data based on the extracted emotions. This makes it possible to quickly generate personalized music and video content that reflects the user's emotions and distribute it over a network.

[0391] A "user" is an individual or organization that provides voice or text input data using the system.

[0392] "Emotion" refers to the mental or emotional state that a user expresses to the system through input data, and is information used for content generation.

[0393] "Music data" refers to information about a song generated based on the user's emotions, and is digital data that includes melody and lyrics.

[0394] "Video data" refers to visual content generated based on music data, and is a digital format of data where colors and moods are designed according to emotions.

[0395] "Content verification" is the process of confirming the safety and appropriateness of generated music and video data and preparing it for distribution.

[0396] "Digital media on information networks" refers to online platforms and services on which generated music and video data are distributed.

[0397] A "melody" is a major element of music, formed by the order and arrangement of sounds contained in musical data.

[0398] "Lyrics" are a portion of the text contained within music data, and are linguistic content generated based on the user's emotions.

[0399] The system that realizes this invention mainly consists of a server and a user terminal. The user inputs voice or text data using a terminal such as a smartphone or personal computer. This data is converted into a digital format by the terminal and transmitted to the server.

[0400] On the server side, a speech recognition engine is used to convert the input speech data into text, and emotions are extracted through an emotion analysis engine. Tools such as Google Speech-to-Text and IBM Watson Tone Analyzer are used in this process. The extracted emotions are then reflected in the generation of musical melodies and lyrics using a generative AI model. For example, OpenAI's GPT can be used for lyric generation.

[0401] Music generation uses music generation software such as Amper Music to create melodies based on emotions. Furthermore, video generation engines such as RunwayML are utilized to generate videos that respond to emotions. This results in content that consistently reflects the user's emotions.

[0402] The completed music and video data are verified for security and appropriateness through content verification tools before being distributed to digital media on the information network. After distribution, users are notified that the content has been uploaded and can share it on social media and other platforms.

[0403] As a concrete example, imagine a situation where a user "hums a tune while talking about their first hot air balloon experience." The server recognizes this as "excitement," generates a lively melody and lyrics that evoke a sense of freedom, and creates content that combines these with visuals of the balloon floating in the sky.

[0404] An example of a prompt for a generative AI model would be, "Generate lyrics that convey a sense of freedom, based on the emotions contained in this audio clip." This would allow users to easily create and share content that richly expresses their personal experiences.

[0405] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0406] Step 1:

[0407] The user inputs voice or text into a device such as a smartphone or computer. The input data is converted into a digital format by the device and sent to the server. In the case of voice input, the device's microphone records it, saves it as an audio file, and prepares it for the next processing step.

[0408] Step 2:

[0409] The server uses a speech recognition engine to convert the transmitted audio data into text. In this process, the audio data is taken as input and converted into text data format. This text data then becomes available for use in the next sentiment extraction step.

[0410] Step 3:

[0411] The server uses a sentiment analysis engine to extract emotions from text data. The input is text data, and the output is extracted emotion data. The sentiment analysis engine calculates linguistic features to identify emotions.

[0412] Step 4:

[0413] The server inputs emotional data into a generative AI model and generates corresponding lyrics. The input consists of emotional data and, in some cases, user prompts, and the output is the generated lyrics text. The generative AI model generates lyrics using language patterns corresponding to the emotions.

[0414] Step 5:

[0415] The server uses music generation software to create emotionally-based musical melodies. The input is emotional data, and the output is musical data containing the melody. The music generation software determines the appropriate tempo and scale to express the emotion.

[0416] Step 6:

[0417] The server uses a video generation engine to generate video data that matches the music data. The input is music data and emotion data, and the output is video data with set visual mood and color settings.

[0418] Step 7:

[0419] The server verifies the generated music and video data using a content verification tool. The input is music and video data, and the output after verification is content that has been approved for publication.

[0420] Step 8:

[0421] The server automatically distributes authorized music and video content to digital media on the information network. In this step, verified content is used as input, and the data is processed for distribution across multiple platforms.

[0422] Step 9:

[0423] The server notifies the user that the created content has been uploaded. The input is information about the distributed content, and the output is a notification sent to the user's terminal. This notification allows the user to confirm the publication of the content on the platform.

[0424] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0425] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0426] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0427] [Third Embodiment]

[0428] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0429] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0430] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0431] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0432] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0433] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0434] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0435] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0436] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0437] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0438] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0439] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0440] This invention provides a system that simplifies music production, enabling even users without specialized knowledge to generate and widely publish high-quality music content. This system efficiently processes audio or text data provided by the user and generates music and video.

[0441] Users input their humming or lyric ideas using devices such as smartphones or PCs. This allows users to easily take their first steps into music production. The device converts the input data into an appropriate format and sends it to the server. The server analyzes the received data and creates a finished song using an AI music generation engine.

[0442] For the generated music, the server utilizes video generation AI to visualize the musical themes and emotions, creating a music video. The generated content is then subjected to content moderation by the server, with automatic checks for safety and copyright.

[0443] The completed music and video data are automatically uploaded by the server to major social networking services and video platforms. This allows users to quickly and widely share their work. After publication, the server notifies the user that the upload is complete and provides information to view the publication results.

[0444] For example, if a user records and sends a humming tune via a smartphone app, the server analyzes the audio and generates a song with a specific melody pattern. Then, a video generation AI creates visual content that aligns with the song's theme, and the finished content is posted to social media. This entire process allows users to share their music projects with the world in just a few minutes.

[0445] The following describes the processing flow.

[0446] Step 1:

[0447] The user inputs lyric ideas as humming or text using their own device. The device converts the input audio into the appropriate digital format, while saving the text as digital data.

[0448] Step 2:

[0449] The terminal compresses the converted audio and text data and sends it to the server using a secure communication protocol.

[0450] Step 3:

[0451] The server passes the received audio data to a speech recognition engine, which analyzes the characteristics of the sound. Based on the analysis, a melody generation AI creates a musical pattern. Additionally, the text data is passed to a natural language processing engine, which generates lyrics appropriate to the context.

[0452] Step 4:

[0453] The server integrates the acquired melody and lyric data and uses music generation AI to complete the song. Instrument selection and arrangement are also handled automatically.

[0454] Step 5:

[0455] After the song is completed, the server hands it over to a video generation AI, which automatically generates a music video based on the song's style and lyrics.

[0456] Step 6:

[0457] The server performs content moderation on the generated content. This is a process that includes copyright checks and filtering of inappropriate content.

[0458] Step 7:

[0459] The server automatically uploads music and videos that pass the inspection to major social media and video platforms. This makes the works available to audiences worldwide.

[0460] Step 8:

[0461] The server notifies the user that the content has been successfully uploaded. The notification includes a link to the published work and information to check viewer reactions.

[0462] (Example 1)

[0463] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0464] Traditional methods of music and video production require specialized knowledge and skills, and are time-consuming and labor-intensive. Therefore, it is difficult for the average user to easily create and publish high-quality music and visual media, limiting the scope of creativity.

[0465] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0466] In this invention, the server includes means for acquiring information via an input device, means for analyzing the acquired information and generating music information, and means for generating visual information from the music information. This makes it possible for even ordinary users to easily generate music and videos and quickly publish them to a wide audience.

[0467] An "input device" is a physical or virtual interface used by a user to provide information.

[0468] "Information" refers to materials provided by users, such as audio or text data.

[0469] "Song information" refers to music data generated based on acquired information.

[0470] "Visual information" refers to video data generated based on music information.

[0471] "Evaluation and verification" is the process of automatically or manually checking that the generated data is appropriate and secure.

[0472] An "information and communication network" is a digital network where data is sent and received.

[0473] "Transmission" refers to the act of transferring generated data to a specified medium or platform.

[0474] A "melody" is a melodic line in generated music data, particularly one that is formed along with the pitch and temporal progression of notes.

[0475] In implementing this invention, the user utilizes a terminal such as a smartphone or PC. Information such as voice and text provided by the user is collected via the terminal's input device. The terminal converts this input data into a processable digital format, reduces unnecessary noise and adjusts the format, and then transmits it to the server.

[0476] The server receives the information and performs analysis using a generative AI model. This AI model receives instructions from the user regarding the style and emotion they intend to create based on the provided information. For example, by giving the AI ​​model the prompt "Generate an energetic and moving rock song," it can generate a melody and accompaniment that meets the request.

[0477] After the music information is generated, the server uses video generation AI to design the visual information. This is the process of creating video data that aligns with the generated music, based on a theme specified by the user. For example, based on a prompt such as "space-themed visual content," it generates visually appealing videos.

[0478] Finally, the generated music and visual information is evaluated and verified on the server. After confirming that there are no safety or copyright issues, it is automatically transmitted to the designated media platform via the information and communication network. This transmission process allows users to widely publish their creations in a short amount of time.

[0479] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0480] Step 1:

[0481] The user uses a smartphone or PC to record audio data or input text data. The input device accurately captures the audio or text provided by the user and converts it into a digital format. The input for this process is the user's audio or text information, and the output is digital audio or text data.

[0482] Step 2:

[0483] The terminal performs noise reduction on the acquired digital audio data to generate clear audio data. In the case of text data, it adjusts the string format. In this step, the input is the output data from step 1, and the output is the improved digital audio data or formatted text data.

[0484] Step 3:

[0485] The terminal sends the adjusted digital audio or text data to the server via the internet. The input to this process is the output data from step 2, and the output is the audio or text data transferred to the server.

[0486] Step 4:

[0487] The server inputs the received data into the generation AI model and uses prompt statements to generate song information that reflects the user's intent. For example, it might use the prompt "Generate an energetic and moving rock song." The input for this step is the data and prompt statements transferred in step 3, and the output is the generated song information.

[0488] Step 5:

[0489] The server uses the generated music information to create visual information using a video generation AI. The video generation AI generates video that matches the theme of the music. The input to this process is the music information from step 4, and the output is the corresponding visual information.

[0490] Step 6:

[0491] The server evaluates and verifies music and visual information to eliminate inappropriate content. The input is the data generated in steps 4 and 5, and the output is evaluated and safe content.

[0492] Step 7:

[0493] The server automatically uploads verified music and visual information to the configured media platform. The input is evaluated data, and the output is publicly available content.

[0494] Step 8:

[0495] The server sends a notification to the user that publication is complete and provides information such as the content viewing status. The input is the result of step 7, and the output is the notification to the user and the viewing data.

[0496] (Application Example 1)

[0497] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0498] Music production requires specialized knowledge and tools, making it difficult for many ordinary users to easily create and publish music and video content. Furthermore, the lack of efficient means to share generated content presents a challenge, as users face the challenge of having to expedite and make their creations widely available.

[0499] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0500] In this invention, the server includes means for acquiring voice or text data input from a user, means for analyzing the acquired data and generating music content, and means for generating visual content based on the music content. This makes it possible for users to easily create music and video content without specialized knowledge and to quickly publish it through an electronic communication network.

[0501] "User" refers to any person who uses the system of the present invention for the purpose of creating and sharing music and visual content.

[0502] "Audio or text data" refers to digital information, including melodies, lyrics, or related linguistic information, that are entered by the user.

[0503] "Music content" refers to songs and sound files generated based on audio or text data.

[0504] "Visual content" refers to video files and visual data generated based on music content.

[0505] "Means of checking in accordance with media science" refers to a function that automatically evaluates generated music and visual content according to appropriate content moderation standards to ensure legality and quality.

[0506] A "platform on an electronic communication network" refers to a digital infrastructure such as social networking services or video sharing services used to publish or distribute generated content online.

[0507] "Digitized voice information" refers to data obtained by analyzing voice data entered by a user in a digital format and converting it into a format that can be processed on a computer.

[0508] This invention constructs a system that facilitates the creation and publication of music and visual content. Users can send their voice or entered text data to the system using a mobile communication device such as a smartphone or tablet. The device runs commonly available speech recognition software, such as the Google Cloud Speech-to-Text API, to convert the voice data received from the user into digitized speech information.

[0509] The server receives this digitized audio and text data and generates music content using a generative AI model. OpenAI's API is used to create appropriate melodies and sound patterns for music content generation. Furthermore, based on the generated music content, AI such as DeepArt is used to create visual content that aligns with the emotions and themes of the song.

[0510] Furthermore, the server checks the generated music and visual content in accordance with media science standards. After the check is complete, the server has the functionality to automatically transmit this content to platforms on electronic communication networks, specifically social networking services and video sharing services. This allows users to widely publish their work in a short amount of time.

[0511] As a concrete example, users can record melodies they come up with while out and about using the "Pocket Music Maker" app, and then instantly generate music and visual content based on those recordings, which they can then post to Instagram. An example of a prompt message used when generating music might be: "Based on this text, please create an upbeat, catchy melody. Please create a song that evokes the image of 'wind' mentioned in the lyrics, and a video that expresses that."

[0512] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0513] Step 1:

[0514] Users input voice or text data through an application using a smartphone or tablet. This input includes recordings or text entries of humming or lyrics. The device converts the input voice data into digitized speech information using the Google Cloud Speech-to-Text API. This makes the voice ready to be sent to the server in digital data format.

[0515] Step 2:

[0516] The server receives digitized audio information or text data sent from the terminal. Based on this input data, it generates music content using the OpenAI API. Specifically, a generation AI model analyzes the input data and arranges musical melodies and harmonies to produce a musical output.

[0517] Step 3:

[0518] Based on the generated music content, the server uses AI such as DeepArt to create visual content. Here, it generates videos that align with the emotional elements and themes of the music. The input is music content, and the output is video data that visually represents that music.

[0519] Step 4:

[0520] The server performs content moderation on the generated music and visual content. Specifically, it checks whether the generated content is legal and complies with media standards. The input is the generated music and video data, and the output is the checked data.

[0521] Step 5:

[0522] Verified music and visual content is automatically uploaded by the server to network platforms such as social networking services and video sharing services. The input here is moderated content data, and the output is the content published on the platform. Users can check the publication status of their work through a dedicated app.

[0523] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0524] This invention is a system that recognizes emotions from voice or text input provided by the user and reflects those emotions in the generation of music and video. This system utilizes an emotion engine to determine the user's intentions and emotional state, and adjusts the content based on the results to generate more personal and emotionally appealing works.

[0525] Users input ideas into the system using their smartphones or PCs, either by humming or writing them down as text. The device converts this input into an appropriate digital format and sends it to the server. The server analyzes the audio data using a speech recognition engine and extracts emotions from the user's voice and linguistic characteristics through an emotion engine.

[0526] The server adjusts the music generation process based on the extracted emotional data. Specifically, it incorporates emotional data into the selection of melody, tempo, and harmony. Meanwhile, emotions are also considered during the lyric generation process, and natural language processing is performed so that the content and structure of the lyrics change according to the emotions.

[0527] Once the music is complete, the server moves on to the video generation process, creating a video while reflecting emotional data in the mood and color of the visuals. In this way, content is produced in which emotions are consistently reflected in both the music and the visuals.

[0528] Furthermore, the completed content undergoes content moderation to ensure safety and copyright, and is then automatically uploaded to major social media and video platforms by the server. The server then notifies users that the content has been published and provides relevant information.

[0529] For example, if a user hums a tune while talking about an emotional experience they've had through a smartphone app, the server analyzes this using an emotion engine. If the emotion is recognized as "joy," it automatically generates a cheerful melody and positive lyrics, creating a music video with vibrant and hopeful visuals. This allows users to quickly distribute music projects that richly express their emotions.

[0530] The following describes the processing flow.

[0531] Step 1:

[0532] Users record themselves humming or input lyric ideas as text using their smartphone or PC. The device converts the audio into digital data and saves the text data accurately in the data format.

[0533] Step 2:

[0534] The terminal compresses the converted and stored audio and text data and sends it to the server using a secure communication protocol.

[0535] Step 3:

[0536] The server processes the received audio data through a speech recognition engine and sends the data, along with the melody, to an emotion engine to analyze the emotions in the user's voice. The emotion is identified based on the tone and pitch of the voice extracted from the audio.

[0537] Step 4:

[0538] The server applies a natural language processing engine to the text data to understand emotional keywords and context from the text. Here too, an emotion engine is used to identify the emotions embedded in the text.

[0539] Step 5:

[0540] The server generates music based on the identified emotions. It adjusts the tempo, tone, and instrumentation of the melody according to the emotion, and also reflects the emotion in the lyrics to coordinate the entire song.

[0541] Step 6:

[0542] After the song is completed, the server applies its emotional data to the video generation engine, using it to determine the atmosphere and color scheme of the music video. This results in the creation of visuals that match the emotions expressed.

[0543] Step 7:

[0544] The server checks the completed music and video data with a content moderation engine to ensure there are no copyright infringements or inappropriate elements. If there are no problems with this process, it proceeds to the next step.

[0545] Step 8:

[0546] The server automatically uploads verified content to major social media and video platform networks.

[0547] Step 9:

[0548] The server notifies the user that the generated content has been successfully uploaded. The user can then view the published content via the provided link.

[0549] (Example 2)

[0550] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0551] Traditional music and video production often fails to adequately reflect individual emotions and intentions during the creative process, making it difficult to generate highly personalized content. Furthermore, the copyright and security checks required for content uploads are cumbersome, necessitating automation. Moreover, the need to quickly share content that expresses one's emotions remains unmet.

[0552] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0553] In this invention, the server includes means for receiving audio or descriptive information from a user, means for generating music and video information using extracted emotional information, and means for reviewing the content of the generated music and video information. This makes it possible to quickly and automatically generate and share highly personalized content based on the emotions of individual users.

[0554] A "user" is the entity that inputs voice or written information into the system.

[0555] "Voice information" refers to data provided by users through voice.

[0556] "Descriptive information" refers to data provided by the user in text format.

[0557] "Emotional information" refers to data about emotions extracted from audio or written information.

[0558] "Music information" refers to data related to music that is generated based on emotional information.

[0559] "Visual information" refers to visual data generated based on music information.

[0560] "Content review" is the process of verifying whether the generated information is safe and appropriate.

[0561] A "communication network" is a network infrastructure used for sending and receiving information.

[0562] A "medium" is the platform to which the generated information is transmitted.

[0563] A description of embodiments for carrying out the present invention will be provided.

[0564] Users input voice or written information into the system using devices such as smartphones or personal computers. Specifically, they can record voice data or input text data using smartphone applications or desktop software. The devices are equipped with voice processing software for speech recognition and document editing software for text processing. For speech recognition, software is used to convert the voice data into digital audio file formats (WAV or MP3).

[0565] The device transmits the input voice or written information to the server via the internet. The server uses a speech recognition engine to convert the voice data into text and extracts the user's emotional information through an emotion engine. Sentiment analysis utilizes generative AI models to determine emotions from the user's voice tone and text. Various machine learning algorithms and AI models are used in this process.

[0566] Based on the extracted emotional information, a music generation engine generates musical information. This creates musical data with melodies, tempos, and harmonies based on emotions, and specific algorithms and modules (e.g., music generation software) can be used for music generation. Furthermore, a video generation engine generates video information based on the generated musical information. Video generation uses video processing algorithms to set the color tone and mood to match the emotions.

[0567] The completed music and video information is subjected to a content review process by the server. This process includes checking the safety of the content and verifying copyright. After the content passes the review, the server automatically sends the generated information to social media and video sharing platforms. This notifies users that the generated content has been published and provides them with relevant links.

[0568] For example, if a user uses a smartphone app to input a hummed tune while talking about an emotional experience they've had, the server analyzes it using an emotion engine. If the emotion is recognized as "joy," the server automatically generates a cheerful melody and positive lyrics, creating a music video with vibrant and hopeful visuals.

[0569] An example of a prompt message is: "Receive voice input from the user, analyze their emotions, and generate a joyful melody and lyrics, along with corresponding visuals."

[0570] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0571] Step 1:

[0572] Users input audio or written information using a smartphone or personal computer. Specific actions might include pressing a record button on the application to hum a tune or typing emotionally expressive text into a text input field. The output at this stage is the user's input data itself.

[0573] Step 2:

[0574] The device converts user voice input into digital audio files. It also uses speech recognition software to convert the voice data into text data. This conversion outputs clear digital data that can be used as a template.

[0575] Step 3:

[0576] The device sends digital data, either voice or text, to the server. Specifically, this involves uploading the data to the server's API endpoint via an HTTP request. The output is the digital data sent to the server.

[0577] Step 4:

[0578] The server further analyzes the received audio data using a speech recognition engine and converts it into text data. During this process, it analyzes the tone and linguistic features of the speech and extracts emotional information. The output is data that identifies the user's emotions.

[0579] Step 5:

[0580] The server uses emotional information to activate a music generation engine and generate music. It adjusts the melody, tempo, and harmony according to the emotion. Specifically, it generates a music pattern corresponding to the emotion. The output is the generated music file.

[0581] Step 6:

[0582] The server uses a video generation engine to create video information based on the generated music information. Visual effects and color tones are adjusted based on emotional information. Specifically, an appropriate video sequence is designed by AI. The output is video data.

[0583] Step 7:

[0584] The server then submits the completed music and video information to a content review process. This process checks copyright and content safety. Specifically, an AI model analyzes the content and confirms that there are no problems. The output is the final content that has passed the review.

[0585] Step 8:

[0586] The server automatically uploads the final content to social media and video platforms. This includes specific actions such as posting videos using each platform's API. The output is the content published on each platform.

[0587] (Application Example 2)

[0588] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0589] Conventional music and video generation systems have struggled to create content that reflects user emotions in real time. Furthermore, smoothly distributing the generated content over a network based on individual emotions has also been difficult. This has resulted in a limited user experience and the inability to quickly share personalized content that responds to emotions.

[0590] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0591] In this invention, the server includes means for acquiring voice or text input data from a user, means for analyzing the acquired input data and extracting emotions, and means for generating music data and video data based on the extracted emotions. This makes it possible to quickly generate personalized music and video content that reflects the user's emotions and distribute it over a network.

[0592] A "user" is an individual or organization that provides voice or text input data using the system.

[0593] "Emotion" refers to the mental or emotional state that a user expresses to the system through input data, and is information used for content generation.

[0594] "Music data" refers to information about a song generated based on the user's emotions, and is digital data that includes melody and lyrics.

[0595] "Video data" refers to visual content generated based on music data, and is a digital format of data where colors and moods are designed according to emotions.

[0596] "Content verification" is the process of confirming the safety and appropriateness of generated music and video data and preparing it for distribution.

[0597] "Digital media on information networks" refers to online platforms and services on which generated music and video data are distributed.

[0598] A "melody" is a major element of music, formed by the order and arrangement of sounds contained in musical data.

[0599] "Lyrics" are a portion of the text contained within music data, and are linguistic content generated based on the user's emotions.

[0600] The system that realizes this invention mainly consists of a server and a user terminal. The user inputs voice or text data using a terminal such as a smartphone or personal computer. This data is converted into a digital format by the terminal and transmitted to the server.

[0601] On the server side, a speech recognition engine is used to convert the input speech data into text, and emotions are extracted through an emotion analysis engine. Tools such as Google Speech-to-Text and IBM Watson Tone Analyzer are used in this process. The extracted emotions are then reflected in the generation of musical melodies and lyrics using a generative AI model. For example, OpenAI's GPT can be used for lyric generation.

[0602] Music generation uses music generation software such as Amper Music to create melodies based on emotions. Furthermore, video generation engines such as RunwayML are utilized to generate videos that respond to emotions. This results in content that consistently reflects the user's emotions.

[0603] The completed music and video data are verified for security and appropriateness through content verification tools before being distributed to digital media on the information network. After distribution, users are notified that the content has been uploaded and can share it on social media and other platforms.

[0604] As a concrete example, imagine a situation where a user "hums a tune while talking about their first hot air balloon experience." The server recognizes this as "excitement," generates a lively melody and lyrics that evoke a sense of freedom, and creates content that combines these with visuals of the balloon floating in the sky.

[0605] An example of a prompt for a generative AI model would be, "Generate lyrics that convey a sense of freedom, based on the emotions contained in this audio clip." This would allow users to easily create and share content that richly expresses their personal experiences.

[0606] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0607] Step 1:

[0608] The user inputs voice or text into a device such as a smartphone or computer. The input data is converted into a digital format by the device and sent to the server. In the case of voice input, the device's microphone records it, saves it as an audio file, and prepares it for the next processing step.

[0609] Step 2:

[0610] The server uses a speech recognition engine to convert the transmitted audio data into text. In this process, the audio data is taken as input and converted into text data format. This text data then becomes available for use in the next sentiment extraction step.

[0611] Step 3:

[0612] The server uses a sentiment analysis engine to extract emotions from text data. The input is text data, and the output is extracted emotion data. The sentiment analysis engine calculates linguistic features to identify emotions.

[0613] Step 4:

[0614] The server inputs emotional data into a generative AI model and generates corresponding lyrics. The input consists of emotional data and, in some cases, user prompts, and the output is the generated lyrics text. The generative AI model generates lyrics using language patterns corresponding to the emotions.

[0615] Step 5:

[0616] The server uses music generation software to create emotionally-based musical melodies. The input is emotional data, and the output is musical data containing the melody. The music generation software determines the appropriate tempo and scale to express the emotion.

[0617] Step 6:

[0618] The server uses a video generation engine to generate video data that matches the music data. The input is music data and emotion data, and the output is video data with set visual mood and color settings.

[0619] Step 7:

[0620] The server verifies the generated music and video data using a content verification tool. The input is music and video data, and the output after verification is content that has been approved for publication.

[0621] Step 8:

[0622] The server automatically distributes authorized music and video content to digital media on the information network. In this step, verified content is used as input, and the data is processed for distribution across multiple platforms.

[0623] Step 9:

[0624] The server notifies the user that the created content has been uploaded. The input is information about the distributed content, and the output is a notification sent to the user's terminal. This notification allows the user to confirm the publication of the content on the platform.

[0625] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0626] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0627] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0628] [Fourth Embodiment]

[0629] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0630] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0631] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0632] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0633] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0634] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0635] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0636] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0637] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0638] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0639] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0640] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0641] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0642] This invention provides a system that simplifies music production, enabling even users without specialized knowledge to generate and widely publish high-quality music content. This system efficiently processes audio or text data provided by the user and generates music and video.

[0643] Users input their humming or lyric ideas using devices such as smartphones or PCs. This allows users to easily take their first steps into music production. The device converts the input data into an appropriate format and sends it to the server. The server analyzes the received data and creates a finished song using an AI music generation engine.

[0644] For the generated music, the server utilizes video generation AI to visualize the musical themes and emotions, creating a music video. The generated content is then subjected to content moderation by the server, with automatic checks for safety and copyright.

[0645] The completed music and video data are automatically uploaded by the server to major social networking services and video platforms. This allows users to quickly and widely share their work. After publication, the server notifies the user that the upload is complete and provides information to view the publication results.

[0646] For example, if a user records and sends a humming tune via a smartphone app, the server analyzes the audio and generates a song with a specific melody pattern. Then, a video generation AI creates visual content that aligns with the song's theme, and the finished content is posted to social media. This entire process allows users to share their music projects with the world in just a few minutes.

[0647] The following describes the processing flow.

[0648] Step 1:

[0649] The user inputs lyric ideas as humming or text using their own device. The device converts the input audio into the appropriate digital format, while saving the text as digital data.

[0650] Step 2:

[0651] The terminal compresses the converted audio and text data and sends it to the server using a secure communication protocol.

[0652] Step 3:

[0653] The server passes the received audio data to a speech recognition engine, which analyzes the characteristics of the sound. Based on the analysis, a melody generation AI creates a musical pattern. Additionally, the text data is passed to a natural language processing engine, which generates lyrics appropriate to the context.

[0654] Step 4:

[0655] The server integrates the acquired melody and lyric data and uses music generation AI to complete the song. Instrument selection and arrangement are also handled automatically.

[0656] Step 5:

[0657] After the song is completed, the server hands it over to a video generation AI, which automatically generates a music video based on the song's style and lyrics.

[0658] Step 6:

[0659] The server performs content moderation on the generated content. This is a process that includes copyright checks and filtering of inappropriate content.

[0660] Step 7:

[0661] The server automatically uploads music and videos that pass the inspection to major social media and video platforms. This makes the works available to audiences worldwide.

[0662] Step 8:

[0663] The server notifies the user that the content has been successfully uploaded. The notification includes a link to the published work and information to check viewer reactions.

[0664] (Example 1)

[0665] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0666] Traditional methods of music and video production require specialized knowledge and skills, and are time-consuming and labor-intensive. Therefore, it is difficult for the average user to easily create and publish high-quality music and visual media, limiting the scope of creativity.

[0667] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0668] In this invention, the server includes means for acquiring information via an input device, means for analyzing the acquired information and generating music information, and means for generating visual information from the music information. This makes it possible for even ordinary users to easily generate music and videos and quickly publish them to a wide audience.

[0669] An "input device" is a physical or virtual interface used by a user to provide information.

[0670] "Information" refers to materials provided by users, such as audio or text data.

[0671] "Song information" refers to music data generated based on acquired information.

[0672] "Visual information" refers to video data generated based on music information.

[0673] "Evaluation and verification" is the process of automatically or manually checking that the generated data is appropriate and secure.

[0674] An "information and communication network" is a digital network where data is sent and received.

[0675] "Transmission" refers to the act of transferring generated data to a specified medium or platform.

[0676] A "melody" is a melodic line in generated music data, particularly one that is formed along with the pitch and temporal progression of notes.

[0677] In implementing this invention, the user utilizes a terminal such as a smartphone or PC. Information such as voice and text provided by the user is collected via the terminal's input device. The terminal converts this input data into a processable digital format, reduces unnecessary noise and adjusts the format, and then transmits it to the server.

[0678] The server receives the information and performs analysis using a generative AI model. This AI model receives instructions from the user regarding the style and emotion they intend to create based on the provided information. For example, by giving the AI ​​model the prompt "Generate an energetic and moving rock song," it can generate a melody and accompaniment that meets the request.

[0679] After the music information is generated, the server uses video generation AI to design the visual information. This is the process of creating video data that aligns with the generated music, based on a theme specified by the user. For example, based on a prompt such as "space-themed visual content," it generates visually appealing videos.

[0680] Finally, the generated music and visual information is evaluated and verified on the server. After confirming that there are no safety or copyright issues, it is automatically transmitted to the designated media platform via the information and communication network. This transmission process allows users to widely publish their creations in a short amount of time.

[0681] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0682] Step 1:

[0683] The user uses a smartphone or PC to record audio data or input text data. The input device accurately captures the audio or text provided by the user and converts it into a digital format. The input for this process is the user's audio or text information, and the output is digital audio or text data.

[0684] Step 2:

[0685] The terminal performs noise reduction on the acquired digital audio data to generate clear audio data. In the case of text data, it adjusts the string format. In this step, the input is the output data from step 1, and the output is the improved digital audio data or formatted text data.

[0686] Step 3:

[0687] The terminal sends the adjusted digital audio or text data to the server via the internet. The input to this process is the output data from step 2, and the output is the audio or text data transferred to the server.

[0688] Step 4:

[0689] The server inputs the received data into the generation AI model and uses prompt statements to generate song information that reflects the user's intent. For example, it might use the prompt "Generate an energetic and moving rock song." The input for this step is the data and prompt statements transferred in step 3, and the output is the generated song information.

[0690] Step 5:

[0691] The server uses the generated music information to create visual information using a video generation AI. The video generation AI generates video that matches the theme of the music. The input to this process is the music information from step 4, and the output is the corresponding visual information.

[0692] Step 6:

[0693] The server evaluates and verifies music and visual information to eliminate inappropriate content. The input is the data generated in steps 4 and 5, and the output is evaluated and safe content.

[0694] Step 7:

[0695] The server automatically uploads verified music and visual information to the configured media platform. The input is evaluated data, and the output is publicly available content.

[0696] Step 8:

[0697] The server sends a notification to the user that publication is complete and provides information such as the content viewing status. The input is the result of step 7, and the output is the notification to the user and the viewing data.

[0698] (Application Example 1)

[0699] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0700] Music production requires specialized knowledge and tools, making it difficult for many ordinary users to easily create and publish music and video content. Furthermore, the lack of efficient means to share generated content presents a challenge, as users face the challenge of having to expedite and make their creations widely available.

[0701] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0702] In this invention, the server includes means for acquiring voice or text data input from a user, means for analyzing the acquired data and generating music content, and means for generating visual content based on the music content. This makes it possible for users to easily create music and video content without specialized knowledge and to quickly publish it through an electronic communication network.

[0703] "User" refers to any person who uses the system of the present invention for the purpose of creating and sharing music and visual content.

[0704] "Audio or text data" refers to digital information, including melodies, lyrics, or related linguistic information, that are entered by the user.

[0705] "Music content" refers to songs and sound files generated based on audio or text data.

[0706] "Visual content" refers to video files and visual data generated based on music content.

[0707] "Means of checking in accordance with media science" refers to a function that automatically evaluates generated music and visual content according to appropriate content moderation standards to ensure legality and quality.

[0708] A "platform on an electronic communication network" refers to a digital infrastructure such as social networking services or video sharing services used to publish or distribute generated content online.

[0709] "Digitized voice information" refers to data obtained by analyzing voice data entered by a user in a digital format and converting it into a format that can be processed on a computer.

[0710] This invention constructs a system that facilitates the creation and publication of music and visual content. Users can send their voice or entered text data to the system using a mobile communication device such as a smartphone or tablet. The device runs commonly available speech recognition software, such as the Google Cloud Speech-to-Text API, to convert the voice data received from the user into digitized speech information.

[0711] The server receives this digitized audio and text data and generates music content using a generative AI model. OpenAI's API is used to create appropriate melodies and sound patterns for music content generation. Furthermore, based on the generated music content, AI such as DeepArt is used to create visual content that aligns with the emotions and themes of the song.

[0712] Furthermore, the server checks the generated music and visual content in accordance with media science standards. After the check is complete, the server has the functionality to automatically transmit this content to platforms on electronic communication networks, specifically social networking services and video sharing services. This allows users to widely publish their work in a short amount of time.

[0713] As a concrete example, users can record melodies they come up with while out and about using the "Pocket Music Maker" app, and then instantly generate music and visual content based on those recordings, which they can then post to Instagram. An example of a prompt message used when generating music might be: "Based on this text, please create an upbeat, catchy melody. Please create a song that evokes the image of 'wind' mentioned in the lyrics, and a video that expresses that."

[0714] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0715] Step 1:

[0716] Users input voice or text data through an application using a smartphone or tablet. This input includes recordings or text entries of humming or lyrics. The device converts the input voice data into digitized speech information using the Google Cloud Speech-to-Text API. This makes the voice ready to be sent to the server in digital data format.

[0717] Step 2:

[0718] The server receives digitized audio information or text data sent from the terminal. Based on this input data, it generates music content using the OpenAI API. Specifically, a generation AI model analyzes the input data and arranges musical melodies and harmonies to produce a musical output.

[0719] Step 3:

[0720] Based on the generated music content, the server uses AI such as DeepArt to create visual content. Here, it generates videos that align with the emotional elements and themes of the music. The input is music content, and the output is video data that visually represents that music.

[0721] Step 4:

[0722] The server performs content moderation on the generated music and visual content. Specifically, it checks whether the generated content is legal and complies with media standards. The input is the generated music and video data, and the output is the checked data.

[0723] Step 5:

[0724] Verified music and visual content is automatically uploaded by the server to network platforms such as social networking services and video sharing services. The input here is moderated content data, and the output is the content published on the platform. Users can check the publication status of their work through a dedicated app.

[0725] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0726] This invention is a system that recognizes emotions from voice or text input provided by the user and reflects those emotions in the generation of music and video. This system utilizes an emotion engine to determine the user's intentions and emotional state, and adjusts the content based on the results to generate more personal and emotionally appealing works.

[0727] Users input ideas into the system using their smartphones or PCs, either by humming or writing them down as text. The device converts this input into an appropriate digital format and sends it to the server. The server analyzes the audio data using a speech recognition engine and extracts emotions from the user's voice and linguistic characteristics through an emotion engine.

[0728] The server adjusts the music generation process based on the extracted emotional data. Specifically, it incorporates emotional data into the selection of melody, tempo, and harmony. Meanwhile, emotions are also considered during the lyric generation process, and natural language processing is performed so that the content and structure of the lyrics change according to the emotions.

[0729] Once the music is complete, the server moves on to the video generation process, creating a video while reflecting emotional data in the mood and color of the visuals. In this way, content is produced in which emotions are consistently reflected in both the music and the visuals.

[0730] Furthermore, the completed content undergoes content moderation to ensure safety and copyright, and is then automatically uploaded to major social media and video platforms by the server. The server then notifies users that the content has been published and provides relevant information.

[0731] For example, if a user hums a tune while talking about an emotional experience they've had through a smartphone app, the server analyzes this using an emotion engine. If the emotion is recognized as "joy," it automatically generates a cheerful melody and positive lyrics, creating a music video with vibrant and hopeful visuals. This allows users to quickly distribute music projects that richly express their emotions.

[0732] The following describes the processing flow.

[0733] Step 1:

[0734] Users record themselves humming or input lyric ideas as text using their smartphone or PC. The device converts the audio into digital data and saves the text data accurately in the data format.

[0735] Step 2:

[0736] The terminal compresses the converted and stored audio and text data and sends it to the server using a secure communication protocol.

[0737] Step 3:

[0738] The server processes the received audio data through a speech recognition engine and sends the data, along with the melody, to an emotion engine to analyze the emotions in the user's voice. The emotion is identified based on the tone and pitch of the voice extracted from the audio.

[0739] Step 4:

[0740] The server applies a natural language processing engine to the text data to understand emotional keywords and context from the text. Here too, an emotion engine is used to identify the emotions embedded in the text.

[0741] Step 5:

[0742] The server generates music based on the identified emotions. It adjusts the tempo, tone, and instrumentation of the melody according to the emotion, and also reflects the emotion in the lyrics to coordinate the entire song.

[0743] Step 6:

[0744] After the song is completed, the server applies its emotional data to the video generation engine, using it to determine the atmosphere and color scheme of the music video. This results in the creation of visuals that match the emotions expressed.

[0745] Step 7:

[0746] The server checks the completed music and video data with a content moderation engine to ensure there are no copyright infringements or inappropriate elements. If there are no problems with this process, it proceeds to the next step.

[0747] Step 8:

[0748] The server automatically uploads verified content to major social media and video platform networks.

[0749] Step 9:

[0750] The server notifies the user that the generated content has been successfully uploaded. The user can then view the published content via the provided link.

[0751] (Example 2)

[0752] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0753] Traditional music and video production often fails to adequately reflect individual emotions and intentions during the creative process, making it difficult to generate highly personalized content. Furthermore, the copyright and security checks required for content uploads are cumbersome, necessitating automation. Moreover, the need to quickly share content that expresses one's emotions remains unmet.

[0754] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0755] In this invention, the server includes means for receiving audio or descriptive information from a user, means for generating music and video information using extracted emotional information, and means for reviewing the content of the generated music and video information. This makes it possible to quickly and automatically generate and share highly personalized content based on the emotions of individual users.

[0756] A "user" is the entity that inputs voice or written information into the system.

[0757] "Voice information" refers to data provided by users through voice.

[0758] "Descriptive information" refers to data provided by the user in text format.

[0759] "Emotional information" refers to data about emotions extracted from audio or written information.

[0760] "Music information" refers to data related to music that is generated based on emotional information.

[0761] "Visual information" refers to visual data generated based on music information.

[0762] "Content review" is the process of verifying whether the generated information is safe and appropriate.

[0763] A "communication network" is a network infrastructure used for sending and receiving information.

[0764] A "medium" is the platform to which the generated information is transmitted.

[0765] A description of embodiments for carrying out the present invention will be provided.

[0766] Users input voice or written information into the system using devices such as smartphones or personal computers. Specifically, they can record voice data or input text data using smartphone applications or desktop software. The devices are equipped with voice processing software for speech recognition and document editing software for text processing. For speech recognition, software is used to convert the voice data into digital audio file formats (WAV or MP3).

[0767] The device transmits the input voice or written information to the server via the internet. The server uses a speech recognition engine to convert the voice data into text and extracts the user's emotional information through an emotion engine. Sentiment analysis utilizes generative AI models to determine emotions from the user's voice tone and text. Various machine learning algorithms and AI models are used in this process.

[0768] Based on the extracted emotional information, a music generation engine generates musical information. This creates musical data with melodies, tempos, and harmonies based on emotions, and specific algorithms and modules (e.g., music generation software) can be used for music generation. Furthermore, a video generation engine generates video information based on the generated musical information. Video generation uses video processing algorithms to set the color tone and mood to match the emotions.

[0769] The completed music and video information is subjected to a content review process by the server. This process includes checking the safety of the content and verifying copyright. After the content passes the review, the server automatically sends the generated information to social media and video sharing platforms. This notifies users that the generated content has been published and provides them with relevant links.

[0770] For example, if a user uses a smartphone app to input a hummed tune while talking about an emotional experience they've had, the server analyzes it using an emotion engine. If the emotion is recognized as "joy," the server automatically generates a cheerful melody and positive lyrics, creating a music video with vibrant and hopeful visuals.

[0771] An example of a prompt message is: "Receive voice input from the user, analyze their emotions, and generate a joyful melody and lyrics, along with corresponding visuals."

[0772] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0773] Step 1:

[0774] Users input audio or written information using a smartphone or personal computer. Specific actions might include pressing a record button on the application to hum a tune or typing emotionally expressive text into a text input field. The output at this stage is the user's input data itself.

[0775] Step 2:

[0776] The device converts user voice input into digital audio files. It also uses speech recognition software to convert the voice data into text data. This conversion outputs clear digital data that can be used as a template.

[0777] Step 3:

[0778] The device sends digital data, either voice or text, to the server. Specifically, this involves uploading the data to the server's API endpoint via an HTTP request. The output is the digital data sent to the server.

[0779] Step 4:

[0780] The server further analyzes the received audio data using a speech recognition engine and converts it into text data. During this process, it analyzes the tone and linguistic features of the speech and extracts emotional information. The output is data that identifies the user's emotions.

[0781] Step 5:

[0782] The server uses emotional information to activate a music generation engine and generate music. It adjusts the melody, tempo, and harmony according to the emotion. Specifically, it generates a music pattern corresponding to the emotion. The output is the generated music file.

[0783] Step 6:

[0784] The server uses a video generation engine to create video information based on the generated music information. Visual effects and color tones are adjusted based on emotional information. Specifically, an appropriate video sequence is designed by AI. The output is video data.

[0785] Step 7:

[0786] The server then submits the completed music and video information to a content review process. This process checks copyright and content safety. Specifically, an AI model analyzes the content and confirms that there are no problems. The output is the final content that has passed the review.

[0787] Step 8:

[0788] The server automatically uploads the final content to social media and video platforms. This includes specific actions such as posting videos using each platform's API. The output is the content published on each platform.

[0789] (Application Example 2)

[0790] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0791] Conventional music and video generation systems have struggled to create content that reflects user emotions in real time. Furthermore, smoothly distributing the generated content over a network based on individual emotions has also been difficult. This has resulted in a limited user experience and the inability to quickly share personalized content that responds to emotions.

[0792] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0793] In this invention, the server includes means for acquiring voice or text input data from a user, means for analyzing the acquired input data and extracting emotions, and means for generating music data and video data based on the extracted emotions. This makes it possible to quickly generate personalized music and video content that reflects the user's emotions and distribute it over a network.

[0794] A "user" is an individual or organization that provides voice or text input data using the system.

[0795] "Emotion" refers to the mental or emotional state that a user expresses to the system through input data, and is information used for content generation.

[0796] "Music data" refers to information about a song generated based on the user's emotions, and is digital data that includes melody and lyrics.

[0797] "Video data" refers to visual content generated based on music data, and is a digital format of data where colors and moods are designed according to emotions.

[0798] "Content verification" is the process of confirming the safety and appropriateness of generated music and video data and preparing it for distribution.

[0799] "Digital media on information networks" refers to online platforms and services on which generated music and video data are distributed.

[0800] A "melody" is a major element of music, formed by the order and arrangement of sounds contained in musical data.

[0801] "Lyrics" are a portion of the text contained within music data, and are linguistic content generated based on the user's emotions.

[0802] The system that realizes this invention mainly consists of a server and a user terminal. The user inputs voice or text data using a terminal such as a smartphone or personal computer. This data is converted into a digital format by the terminal and transmitted to the server.

[0803] On the server side, a speech recognition engine is used to convert the input speech data into text, and emotions are extracted through an emotion analysis engine. Tools such as Google Speech-to-Text and IBM Watson Tone Analyzer are used in this process. The extracted emotions are then reflected in the generation of musical melodies and lyrics using a generative AI model. For example, OpenAI's GPT can be used for lyric generation.

[0804] Music generation uses music generation software such as Amper Music to create melodies based on emotions. Furthermore, video generation engines such as RunwayML are utilized to generate videos that respond to emotions. This results in content that consistently reflects the user's emotions.

[0805] The completed music and video data are verified for security and appropriateness through content verification tools before being distributed to digital media on the information network. After distribution, users are notified that the content has been uploaded and can share it on social media and other platforms.

[0806] As a concrete example, imagine a situation where a user "hums a tune while talking about their first hot air balloon experience." The server recognizes this as "excitement," generates a lively melody and lyrics that evoke a sense of freedom, and creates content that combines these with visuals of the balloon floating in the sky.

[0807] An example of a prompt for a generative AI model would be, "Generate lyrics that convey a sense of freedom, based on the emotions contained in this audio clip." This would allow users to easily create and share content that richly expresses their personal experiences.

[0808] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0809] Step 1:

[0810] The user inputs voice or text into a device such as a smartphone or computer. The input data is converted into a digital format by the device and sent to the server. In the case of voice input, the device's microphone records it, saves it as an audio file, and prepares it for the next processing step.

[0811] Step 2:

[0812] The server uses a speech recognition engine to convert the transmitted audio data into text. In this process, the audio data is taken as input and converted into text data format. This text data then becomes available for use in the next sentiment extraction step.

[0813] Step 3:

[0814] The server uses a sentiment analysis engine to extract emotions from text data. The input is text data, and the output is extracted emotion data. The sentiment analysis engine calculates linguistic features to identify emotions.

[0815] Step 4:

[0816] The server inputs emotional data into a generative AI model and generates corresponding lyrics. The input consists of emotional data and, in some cases, user prompts, and the output is the generated lyrics text. The generative AI model generates lyrics using language patterns corresponding to the emotions.

[0817] Step 5:

[0818] The server uses music generation software to create emotionally-based musical melodies. The input is emotional data, and the output is musical data containing the melody. The music generation software determines the appropriate tempo and scale to express the emotion.

[0819] Step 6:

[0820] The server uses a video generation engine to generate video data that matches the music data. The input is music data and emotion data, and the output is video data with set visual mood and color settings.

[0821] Step 7:

[0822] The server verifies the generated music and video data using a content verification tool. The input is music and video data, and the output after verification is content that has been approved for publication.

[0823] Step 8:

[0824] The server automatically distributes authorized music and video content to digital media on the information network. In this step, verified content is used as input, and the data is processed for distribution across multiple platforms.

[0825] Step 9:

[0826] The server notifies the user that the created content has been uploaded. The input is information about the distributed content, and the output is a notification sent to the user's terminal. This notification allows the user to confirm the publication of the content on the platform.

[0827] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0828] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0829] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0830] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0831] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0832] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0833] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0834] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0835] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0836] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0837] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0838] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0839] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0840] 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.

[0841] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0842] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0843] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0844] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0845] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0846] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0847] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0848] The following is further disclosed regarding the embodiments described above.

[0849] (Claim 1)

[0850] Means for obtaining voice or text input data from the user,

[0851] A means for analyzing the acquired input data and generating music data,

[0852] Means for generating video data based on the aforementioned music data,

[0853] A means for content moderating the generated music and video data,

[0854] A means for automatically uploading the aforementioned music data and video data to a medium on the network,

[0855] A system that includes this.

[0856] (Claim 2)

[0857] The system according to claim 1, further comprising means for notifying a user that generated music data and video data have been uploaded.

[0858] (Claim 3)

[0859] The system according to claim 1, further comprising means for converting acquired audio data into digital audio data, and means for generating a melody based on the digital audio data.

[0860] "Example 1"

[0861] (Claim 1)

[0862] Means for acquiring information via an input device,

[0863] A means for analyzing the acquired information and generating song information,

[0864] Means for generating visual information from the aforementioned music information,

[0865] A means for evaluating and verifying the generated music information and visual information,

[0866] Means for automatically transmitting the aforementioned music information and visual information to a medium on an information and communication network,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] The system according to claim 1, further comprising means for notifying a user that generated music information and visual information have been transmitted.

[0870] (Claim 3)

[0871] The system according to claim 1, further comprising means for converting acquired audio information into digital audio information, and means for generating a melody based on the digital audio information.

[0872] "Application Example 1"

[0873] (Claim 1)

[0874] A means of obtaining voice or text data input from the user,

[0875] A means for analyzing the acquired data and generating music content,

[0876] Means for generating visual content based on the aforementioned music content,

[0877] A means of checking generated music and visual content in accordance with media science,

[0878] Means for automatically transmitting the aforementioned music content and visual content to a platform on an electronic communication network,

[0879] A means to enable real-time content creation on devices accessible to users,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, comprising means for notifying the user that generated music content and visual content have been transmitted.

[0883] (Claim 3)

[0884] The system according to claim 1, further comprising means for converting acquired audio data into digitized audio information, means for generating music based on the audio information, and means for making user records directly accessible on a terminal.

[0885] "Example 2 of combining an emotion engine"

[0886] (Claim 1)

[0887] A means of receiving audio or written information from the user,

[0888] The means for analyzing the received information and extracting emotional information,

[0889] A means of generating musical information using extracted emotional information,

[0890] A means for generating video information based on generated music information,

[0891] A means for reviewing the content of generated music and video information,

[0892] A means for automatically transmitting the aforementioned music information and video information to a medium on a communication network,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, further comprising means for notifying the user that generated music information and video information has been transmitted.

[0896] (Claim 3)

[0897] The system according to claim 1, further comprising means for converting received audio information into a digital format, and means for creating a melody based on the digital format.

[0898] "Application example 2 when combining with an emotional engine"

[0899] (Claim 1)

[0900] Means for obtaining voice or text input data from the user,

[0901] A means for analyzing the acquired input data and extracting emotions,

[0902] A means of generating music data based on extracted emotions,

[0903] Means for generating video data based on the aforementioned music data,

[0904] A means for verifying the content of the generated music and video data,

[0905] A means for automatically distributing the aforementioned music data and video data to digital media on an information network,

[0906] A system that includes this.

[0907] (Claim 2)

[0908] The system according to claim 1, further comprising means for notifying a user that generated music data and video data have been delivered.

[0909] (Claim 3)

[0910] The system according to claim 1, further comprising means for converting acquired audio data into digital audio data, means for generating a melody based on the digital audio data, and means for generating lyrics based on extracted emotions. [Explanation of Symbols]

[0911] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining voice or text data input from the user, A means for analyzing the acquired data and generating music content, Means for generating visual content based on the aforementioned music content, A means of checking generated music and visual content in accordance with media science, Means for automatically transmitting the aforementioned music content and visual content to a platform on an electronic communication network, A means to enable real-time content creation on devices accessible to users, A system that includes this.

2. The system according to claim 1, further comprising means for notifying the user that generated music content and visual content have been transmitted.

3. The system according to claim 1, further comprising means for converting acquired audio data into digitized audio information, means for generating music based on the audio information, and means for making user records directly accessible on a terminal.

Images