189 results about "Generative music" patented technology

The invention relates to an intelligent MV generation method, system and device based on AIGC and a medium, and belongs to the technical field of artificial intelligence content generation. The method comprises the following steps: receiving an original music file input by a user and a user instruction; performing audio preprocessing on the original music file to generate a standardized audio signal, and mapping a user instruction into a semantic vector; rhythm features and emotion features are extracted, music feature vectors are generated and subjected to feature alignment with semantic vectors, and an initial key frame sequence is generated based on a diffusion model; performing particle effect density dynamic adjustment and shot switching point generation on the initial key frame sequence, outputting an enhanced key frame sequence, performing optical flow frame insertion and long time sequence prediction, and generating an optimized video frame sequence; and performing block parallel rendering on the optimized video frame sequence according to the target platform parameters to generate an MV file and metadata. According to the invention, deep fusion of audio and visual contents can be realized, and high-quality video contents can be generated according to individual demands of users.

The invention relates to the technical field of natural language processing and medical treatment, can be applied to scenes of daily music creation, psychological medical treatment and the like, and discloses a knowledge graph-based music generation method, device and equipment and a medium, and the method comprises the steps: obtaining demand information, analyzing the demand information according to a preset knowledge graph to construct knowledge connotation mapping, generating a music constraint condition according to the knowledge connotation mapping; generating melody, rhythm and harmony based on the music constraint conditions; and performing music fusion on the melody, the rhythm and the harmony to generate a target music work. Music can be automatically generated, and the creation requirement of a user for a specific music type is met.

The invention relates to the technical field of artificial intelligence and multimedia interaction, and discloses an AI music rhythm-based dance movement real-time generation system, which comprises a music rhythm extraction module used for extracting rhythm time and intensity characteristics of input music and generating music rhythm distribution; the dance movement generation module generates initial dance movement distribution according to the extracted music rhythm distribution and is used for generating the initial dance movement distribution based on a pre-trained deep learning model; and the dynamic synchronization module is used for calculating a mapping relation between music rhythm distribution and dance movement distribution through a dynamic optimal transmission method. According to the technical scheme, dynamic optimal transmission and variational optimization are combined, the technical effect of high-precision alignment of actions and music rhythms is achieved by optimizing the synchronization relation between music rhythm distribution and dance action distribution, the problem of mismatching of actions and music in a complex music rhythm change scene is solved, and the accuracy of the movement and the music is improved. And the dancing action is more natural and smoother.

Methods and systems are disclosed to facilitate creating the sensation of vibrotactile movement on the body of a user. Vibratory motors are used to generate a haptic language for music or other stimuli that is integrated into wearable technology. The disclosed system in certain embodiments enables the creation of a family of devices that allow people such as those with hearing impairments to experience sounds such as music or other input to the system. For example, a “sound vest” or other wearable array transforms musical input to haptic signals so that users can experience their favorite music in a unique way, and can also recognize auditory or other cues in the user's real or virtual reality environment and convey this information to the user using haptic signals.

Systems and methods for procedural media generation, such as generating musical variations and figures, are described. The systems and methods utilize continuous-value data representing structural parameters of rhythm and temporal dynamics to enable dynamic adjustment to musical patterns, intelligent routing, pattern morphing, and real-time feedback. Further features include context-aware effects, adaptive pattern evolution, and multimodal synchronization, thereby providing tools for music composition, performance, and audio production, among other applications.

The embodiment of the invention provides a music generation method, a music generation device, electronic equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring a classical literature text and a real-time hotspot text; then extracting sentiment features of the classical literature text to obtain sentiment features of the literature text, and extracting sentiment features of the real-time hot text to obtain sentiment features of the hot text; and performing feature fusion on the literature text emotion features and the hot text emotion features to obtain comprehensive emotion features. And then obtaining a target music element from a preset music material according to the comprehensive emotion feature and the classical literature text, and generating a music description text according to the target music element. And then acquiring a scene prompt instruction and generating target music according to the music description text and the scene prompt instruction. According to the embodiment of the invention, high-quality music meeting user requirements can be generated.

The invention provides a generative music closed-loop regulation and control method and system based on a reinforcement learning model. The method comprises the steps that 1, parameters are initialized; step 2, acquiring brain wave information; step 3, processing the acquired brain wave information; 4, storing the processed brain wave information, and judging the data volume gt in a database; if M is true, training and updating the decision module, and then entering the step 5; otherwise, directly entering the step 5; 5, a decision module performs closed-loop regulation and control decision making; step 6, a music closed-loop regulation and control module carries out closed-loop regulation and control on a corresponding music playing strategy; 7, a music playing module plays music; and 8, collecting the brain wave information again, and determining whether to enter the step 3 or not by the user state acquisition module according to whether the user reaches the target state or not. Different regulation and control technologies are designed, so that the user can reach a certain target state more efficiently and quickly, and the method can be applied to the fields of aiding sleep, improving attention and the like.

Implementations relate to utilizing generative model(s) (GM(s)) to generate musical content that includes at least lyrical content and music composition content. Processor(s) of a system can: receive user input associated with a client device of a user that includes a request for the musical content, generate the musical content, and cause the musical content to be audibly rendered at the client device. In some implementations, the processor(s) can cause a single GM to process GM input (including at least the user input) to generate GM output and can determine the lyrical content and the music composition content based on the GM output. In other implementations, the processor(s) can cause multiple GMs to process respective GM inputs (each including at least the user input) to generate respective GM outputs and can determine the lyrical content and the music composition content based on the respective GM outputs.

The invention provides a subconsciousness development music generation method based on subconsciousness hierarchical coding, and the method comprises the following steps: obtaining subconsciousness hierarchical features of a user, and constructing a subconsciousness hierarchical coding model based on the subconsciousness hierarchical features of the user; collecting real-time physiological and behavior data of a user, and inputting the real-time physiological and behavior data into the subconsciousness hierarchical coding model to generate personalized music parameters; modulating the personalized music parameters by using a multi-mode coding technology; according to a real-time feedback dynamic adjustment coding strategy, subconsciousness development music adaptive to the current state of the user is output, and the current dominant subconsciousness level is accurately judged by comprehensively collecting real-time physiological data and subconsciousness layering information of the user. According to the method, the problem of inaccurate subconsciousness layered recognition in the past is solved, so that coding can be performed in a targeted manner according to the characteristics of different layers when music is generated.

The embodiment of the present application discloses a method, device and computer-readable storage medium for generating music reviews, wherein the method comprises: obtaining a fusion feature vector of a target music, the fusion feature vector being composed of a concatenation of a lyrics feature vector of the target music and an audio feature vector of the target music; obtaining a preset vocabulary, the preset vocabulary including a plurality of preset vocabulary characters; determining the probability of each vocabulary character in the preset vocabulary generating each comment character in the comment text of the target music according to the fusion feature vector of the target music; obtaining the comment text of the target music based on the probability of each vocabulary character generating each comment character in the comment text. The present application can improve the quality of generating music reviews.

A music generation method and apparatus, a device, and a storage medium. The method comprises: presenting an editing interface, the editing interface comprising a lyric editing control (310); in response to a selection of first lyric content in the lyric editing control, presenting a set of candidate lyric content, the set of candidate lyric content being generated on the basis of context information associated with the lyric editing control (320); determining target lyric on the basis of a selection of second lyric content in the set of candidate lyric content (330); and in response to receiving a music generation request, providing music content generated on the basis of the target lyric (340). The method can improve the lyric editing efficiency in a music generation process, thereby improving the music generation efficiency.

The embodiment of the invention provides a training method of a music generation model and a music generation method and device, and relates to the technical field of artificial intelligence, and the training method of the music generation model comprises the steps: obtaining sample data; the sample data comprises sample note data, sample image data and label information; the label information is used for representing style types corresponding to the sample note data and the sample image data; inputting the sample data into a neural network model for music generation to obtain predicted note data of the sample data; and determining a model loss function of the neural network model according to the predicted note data and the sample data, and performing iterative training on the neural network model based on the model loss function to obtain a music generation model. The music generation model depends on the note data and the image data with the specific style type at the same time in the training stage, so that when the trained music generation model generates music, high-quality music matched with the style type of the given image can be generated.

The disclosure relates to generating audio-based and / or audiovisual-based music content using a generative model. Implementations relate to generating music content comprising at least lyric content and music authoring content using a generative model (GM). A processor of a system may: receive user input associated with a client device of a user, the user input including a request for music content; generating music content; and causing the music content to be audibly rendered at the client device. In some implementations, a processor may cause a single GM to process a GM input, including at least a user input, to generate a GM output, and may determine lyric content and music authoring content based on the GM output. In other implementations, a processor may cause a plurality of GMs to process respective GM inputs (each GM input including at least a user input) to generate respective GM outputs, and may determine lyric content and music authoring content based on the respective GM outputs.

1. Name of this design: Music journal function interactive area for generating and personalizing a music journal on an electronic device. 2. Purpose of this design: An electronic device. 3. The key design features of this product are: the parts in the graphical user interface, and the parts not marked with dotted lines are the parts for which protection is required. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 3 is designated as the basic design. 6. Purpose of the graphical user interface: The overall interface is used to generate music journal covers, display journal covers, personalize journal styles, select journal theme templates, share and download, etc.; certain parts of the interface are used for interactive functions such as generating music journal covers, personalizing journal styles, selecting journal theme templates, sharing and downloading, etc. 7. Human-computer interaction method of graphical user interface: In the main view of Design 1, users can click the "Edit Template" control to enter the journal editing page; they can click to select any template option in the floating layer to switch the template theme; they can click any control at the bottom of the floating layer to perform corresponding operations, such as: download cover, share, etc.; they can also click the "Done" control to save the journal cover. In the main view of Design 2, users can click any category label in the overlay to switch editing items; they can click any option in the overlay to switch theme templates; and they can click any control at the top of the interface to perform corresponding operations, such as: exiting the editing page, moving forward / backward one step, saving and setting, etc. Design 3 uses the same human-computer interaction method as Design 2, allowing users to switch fonts by clicking any option in the overlay. Design 4 uses the same human-computer interaction method as Design 2, allowing users to click on any option in the overlay to switch the background. In the main view of Design 5, users can click any category label in the overlay to switch editing items; they can click any option in the overlay to switch sticker styles, click the "Sticker Management" control to customize stickers; and they can also click any control at the top of the interface to perform corresponding operations, such as: exiting the editing page, moving forward / backward one step, saving and setting, etc. Design 6 uses the same human-computer interaction method as Design 5. Users can click on the selected sticker element on the right to perform corresponding editing operations, drag the sticker options in the floating layer on the left to sort them, or click "Collapse Layer" to collapse the floating layer.

To produce music suitable for a user and to provide the user with the music.SOLUTION: The RAG system 20 includes a reception section 21 that receives user information including at least biological information of a user and information relating to preference of music of the user, a determination section 22 that determines a concept relating to music production based on the user information, a generation section 23 that generates a prompt for instructing production of music based on the concept, and an inputting section 24 that controls a generative AI model 31 that produces music based on the prompt generated by the generation section 23.SELECTED DRAWING: Figure 1

The present disclosure provides a generation device having a plurality of operators that receive a user operation that causes generation of a sound. The generation device includes: at least one first operator arranged in a first region and configured to receive a first user operation that causes generation of a rhythm sound signal; at least one second operator arranged in a second region and configured to receive a second user operation that causes generation of a melody sound signal; and at least one third operator arranged in a third region and configured to receive a third user operation that causes a sound effect to be applied to a synthesized sound signal of the generated rhythm sound signal and the generated melody sound signal. The first region, the second region, and the third region are different regions of the generation device from each other.

The present application relates to apparatus and methods for cellular composition. Embodiments of the invention provide systems, methods and apparatus for real-time cellular composition / generation of music using cells (i.e. short musical motifs), wherein the cellular composition relies on user data.

The present application discloses a method for generating a music video, including: classifying the target audio by using a first network model to obtain the audio category corresponding to the target audio; performing track separation processing on the target audio by using a second network model to obtain a plurality of separated tracks; generating the harmonics and shock waves of each of the separated tracks, and generating an audio feature vector for each audio frame based on the harmonics and shock waves of each of the separated tracks; generating an increment of the audio feature vector for each audio frame based on the audio feature vector for each audio frame; processing the increment of the audio feature vector for each audio frame by using a third network model corresponding to the audio category to obtain a video frame corresponding to each audio frame; and performing synthesis processing on the video frames corresponding to each audio frame to generate a target dynamic video. The present application also provides a computer-readable storage medium and an electronic device. The solution of the present application can efficiently generate a music video associated with the target audio type, and the generated music video can match the audio features.

The present disclosure relates to a music generation method, electronic device, storage device and product, and relates to the field of computer technology. The music generation method includes: displaying a first message sent by a user in a dialogue interface between a user and an intelligent agent; generating music features corresponding to one or more music elements based on the first message; determining prompt information according to the music features; generating music based on the prompt information; and displaying the music sent by the intelligent agent to the user. The embodiments of the present disclosure improve the efficiency and flexibility of generating music.

A music generation method and a related device are applied to the technical field of computers. According to the method, the music consistent with the scene where the vehicle is located can be generated based on the input information and the artificial intelligence content generation model, richness, creativity and uniqueness of the generated music can be improved, more accurate and convenient experience is brought to a user, and the requirements of people for intelligence and entertainment of the vehicle are met. Moreover, in the music generation process, the first speed data of the vehicle or the first acceleration data of the vehicle is used, so that the accuracy of the obtained first scene description text can be improved, the first scene description text better conforms to the first scene where the vehicle is located, the subsequent generation of music better conforming to the first scene where the vehicle is located is facilitated, and the user experience is improved. The immersion of the user can be improved, and the user experience is improved.

The invention discloses a neonatal precise music treatment system based on amplitude integrated electroencephalogram awakening signals and a use method thereof. The neonatal precise music treatment system comprises a collection module, a customized music treatment content design module, an automatic closed-loop module and a safety guarantee module. The collection module is used for collecting the electrooculogram, the heart rate, the pulse oxyhemoglobin saturation and the amplitude integrated electroencephalogram, screening out an amplitude integrated electroencephalogram awakening signal according to the electrooculogram, the heart rate and preset three-level grabbing logic, and then obtaining the level of the amplitude integrated electroencephalogram awakening signal and the level of the brain function state; the customized music treatment content design module is used for generating music according to a preset source material library, the level of the amplitude integrated electroencephalogram awakening signal and the brain function state level; the automatic closed-loop module is used for controlling playing and stopping of music; and the safety guarantee module is used for controlling the volume and stopping working when the amplitude integrated electroencephalogram awakening signal is interrupted. According to the method and the device, the accuracy of awakening signal grabbing is improved.

The invention discloses a gait-based artificial intelligence music generation device, which comprises a sensor assembly arranged on the foot of a user, comprising a pressure sensing device and an inertia sensing module and used for collecting data related to the movement of the user; the computing electronic device is coupled with the sensor assembly in a communication manner, receives the data related to the movement of the user, analyzes the data related to the movement by using a gait analysis module to obtain gait parameters of the user, and then extracts movement-related rhythm parameters in the gait parameters of the user by using a rhythm parameter extraction module; and the AI music generation module is coupled with the computing electronic device in a communication manner and is used for receiving the motion-related rhythm parameters of the user, converting the motion-related rhythm parameters into corresponding rhythm numbers, treble and bass and gentle and gentle sounds, and adding melody by utilizing an AI algorithm to generate a piece of music and outputting the music.

A multi-modal based automatic music generation device according to an embodiment of present invention comprises an embedding extraction module configured to generate an input embedding vector from input information received from a user terminal, a stem search module configured to select a reference stem based on the input embedding vector and select a plurality of similar stems based on the input embedding vector and an embedding vector included in the reference stem, a reference section generation module configured to create a reference section by editing and mixing the plurality of similar stems and a music generation module configured to generate music in song units by generating a plurality of audio sections based on the reference section.

To provide a system including means for selecting the optimum combination on the basis of what is desired and means for a plurality of tasks, the system being applicable for all people including people without specialized knowledge of AI and allowing all people to realize their potential.SOLUTION: The system includes: means for selecting the optimum combination from a plurality of generation AIs on the basis of what is desired, which is input; and means for a plurality of tasks including generation of sentences, generation of images, generation of music, brain storming of a project idea.SELECTED DRAWING: Figure 1

Disclosed techniques relate to user control of generative music. In some embodiments, a computing system generates a musical plan based on both conversational inputs (e.g., using a large-language model (LLM)) and non-conversational inputs (e.g., via a traditional user interface) to a hybrid interface. The computing system may generate an initial version of the musical plan based on the LLM context and update the context and plan based on various types of user input via the hybrid interface. Disclosed techniques may advantageously allow guided user control over generative music systems.

System, process and device configurations are provided for user preference customized generation of gaming music. A method can include detecting at least one user preference for gaming music, determining a game state, and generating gaming music based on the at least one user preference and the game state. Customization of audio and gaming music can have a large impact on a gaming experience. Musical preferences may be collected for users to generate dynamic music and to improve gaming system ability to generate a customized experience. Musical preferences can include one or more of genres, specific song titles, indications of preferred types of music, music identified for certain gaming activities, user feedback, and country of origin. Music may be generated based on emotional cues of a game scene. Music may be controlled to be more prominent or less obtrusive to a game state.

A computer-implemented method for algorithmic generation of musical compositions may include (i) receiving, as a first input set, a set of musical compositions composed by a composer, (ii) receiving, as a second input set, metadata related to at least one musical composition, (iii) training a generative machine learning model on the first input set and the second input set, and (iv) producing, by the generative machine learning model, a new musical composition that is based at least in part on the first input set and the second input set. Various other methods, systems, and computer-readable media are also disclosed.

The invention relates to the technical field of artificial intelligence, in particular to an AI-based music creation puzzle guessing system which comprises a data acquisition module, a music generation module, a music analysis module, a music processing module and a music optimization module. The data acquisition module is used for collecting music data of different years, regions and styles and input data of a user; the music generation module preprocesses music data, constructs a generation model and generates an initial music note sequence; the music analysis module analyzes the initial sequence extraction features and constructs a classification model to judge music attributes; the music processing module performs semantic analysis on input data, calculates similarity between a semantic matching result and a music attribute tag, and calculates a difficulty adjustment coefficient in combination with input time; and the music optimization module adjusts the initial difficulty level according to the difficulty adjustment coefficient, and further adjusts and generates model parameters to obtain a target model. The music creation difficulty can be dynamically adjusted according to the input data of the user, and personalized music guessing experience is achieved.