116 results about "Generative music" patented technology

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.

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.

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.

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.

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.

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.

An object of a system according to an embodiment is to improve a user's walking experience by automatically generating music according to a walking speed.SOLUTION: A system includes a step counting part, a BPM determination part, a musical piece generation part, and a tempo adjustment part. The step counting unit measures a walking speed using a step counting function of the smartphone. The BPM determining unit determines the BPM based on the data measured by the step counting unit. The music generation unit generates music on the basis of the BPM determined by the BPM determination unit. The tempo adjusting unit increases or decreases the BPM according to the user's desire.SELECTED DRAWING: Figure 1

This invention discloses a music search method and system based on big data. It obtains sentiment characteristics by processing user historical playback data using a Natural Language Processing (NLP) model; acquires real-time semantic features based on real-time user input search context data using a BRET model; dynamically adjusts the matching weights of audio features, sentiment characteristics, and real-time semantic features using a reinforcement learning model; adjusts the feature weights based on the matching results to obtain fused features; inputs the fused features into an MTNN multi-task neural network, fuses the outputs of each branch through an attention mechanism to generate a music matching score, and generates a music recommendation list based on the music matching score. This improves the user search experience and platform conversion efficiency.

The invention discloses a symbol music generation method based on texture perception and adaptive representation alignment. The method is characterized by comprising the steps of conditional decoupling and extraction of multi-scale music element features, conditional coding, texture perception FLUX music model construction, adaptive representation alignment, MIDI file generation and the like. Compared with the prior art, the method has the advantages that the structural advantage and multi-scale information of the symbol music are fully utilized, the texture consistency, chord accuracy and style controllability of the generated music are remarkably improved, the training and reasoning cost is reduced, and the generalization ability and practicability of the model are further improved. Through the three-in-one design of'conditional decoupling, texture perception diffusion and self-adaptive expression alignment ', the problems of semantic loss, inconsistent texture, uncontrollable chord and the like caused by neglecting of internal association of music in a traditional method are effectively solved, and the method is efficient, reliable and easy to implement and has good application prospects in the fields of automatic composition, interactive music creation and the like.

The application discloses a music road surface sound field effect evaluation device, which comprises a collecting device and a computer electrically connected with the collecting device; the collecting device comprises a microphone set and a multi-channel data collection card; the computer comprises an analysis module and an evaluation module; the analysis module performs principal component analysis and generates a music signal relation graph and an ideal sound signal relation graph; the evaluation module compares the music signal relation graph with the ideal sound signal relation graph, and generates a four-dimensional evaluation result of frequency, loudness, tone and noise by comprehensively outputting a noise evaluation unit, an objective music evaluation unit and a subjective tone evaluation unit; the evaluation module calculates a comprehensive evaluation index; in addition, the application also discloses an evaluation method based on the device, solves the defect that the dynamic change of a sound field in a continuous playing process of a music piece cannot be captured in the prior art, can restore the dynamic rhythm of the music piece, makes the evaluation result more accurate, and realizes more comprehensive and more objective comprehensive evaluation on music road surface design and construction effect.

The invention relates to the technical field of artificial intelligence and music, and discloses an AI automatic accompaniment system and method based on multi-modal emotion recognition, and the system comprises a multi-modal signal collection module which is used for synchronously collecting visual and audio signals of a user; the multi-modal emotion calculation engine is used for processing the signal, dynamically weighting and fusing visual and audio emotion features through a feature fusion unit based on an attention mechanism, and outputting a comprehensive emotion vector; the AI music dynamic generation module is used for generating accompaniment audio matched with the emotion of the comprehensive emotion vector and the user audio in real time through a generative music model under the condition of the comprehensive emotion vector and the user audio; and an audio mixing and outputting module. According to the method, the robustness of emotion recognition is improved through multi-modal fusion, accompaniment highly coordinated with the emotion state of a player can be dynamically generated, more natural and expressive man-machine interaction playing experience is achieved, and the method is suitable for the fields of music performance, education, treatment and the like.

A computer system including a server having a processor and a memory, the memory having a video database and a music database, the video database storing at least one video file having a plurality of video file markers, and the music database storing at least one music file having a plurality of music file markers, wherein the server receives and decodes encoded data from computer readable code, identifies and retrieves from the music database a music file based on the decoded data, synchronizes the retrieved music file with one of the video files by aligning the video file markers of the video file with the music file markers for the retrieved music file to produce a synchronized video-music file, and transmits the synchronized video-music file to a display, wherein the video file markers are generated for each video file and the music file markers are generated for each music file.

A method for playing music in a motor vehicle, said method being implemented by a processor and comprising the real-time steps of: collecting (201) motor vehicle traffic parameters including steering wheel angle and speed; generating (203) music using the collected parameters as input parameters; and playing (205) the generated music. A music playing device and a motor vehicle comprising the device are also described. Figure to be published with the abbreviation: Fig 2

The invention discloses a music creation control cue word generation method, system and device and a medium, and the method specifically comprises the steps: based on multi-mode creation demand data, determining a melody intention through analyzing voice humming, determining an emotion intensity parameter through analyzing voice intonation, and generating a cue word according to the emotion intensity parameter; extracting keywords of styles, themes and emotions in combination with a natural language processing technology to form multi-modal features; inputting the multi-modal features into a pre-constructed music knowledge graph for associated query and intention refining, and generating music control cues; distributing the music control prompt words to a multi-agent collaborative cluster to generate a music element set; and driving a music generation model to synthesize a music work according to the music element set, and dynamically adjusting an association weight of a music knowledge graph or a decision parameter of a multi-agent collaborative cluster in combination with user feedback data. According to the method and the device, accurate and personalized music creation control cue word generation is realized, and the quality of music creation and the user satisfaction are improved.

An object of a system according to an embodiment is to automatically generate a musical piece based on an atmosphere or an emotion of a photograph and enable a user to easily share or save the musical piece.SOLUTION: A system includes a photograph upload unit, an analysis unit, a music generation unit, and a sharing unit. The photograph upload unit uploads a photograph stored in the user's smartphone. The analysis unit analyzes an atmosphere and a hue of the photograph uploaded by the photograph upload unit, and an emotion and a scene felt from the subject. The musical piece generation unit generates a musical piece on the basis of a result analyzed by the analysis unit. The sharing unit allows the user to share the music generated by the music generation unit on social media or stores the music as a personal commemoration.SELECTED DRAWING: Figure 1

A computer-implemented method for algorithmic generation of musical compositions may include (i) receiving a musical composition and listener preference data associated with at least one listener, (ii) extracting from the musical composition a first set of tracks and a second set of tracks, (iii) generating, by at least one generative machine learning model, based at least in part on the listener preference data, a new set of tracks, and (iv) combining, by a music production model, the first set of tracks extracted from the musical composition with the new set of tracks generated by the generative machine learning model to create a new musical composition based at least in part on the listener preference data. Various other methods, systems, and computer-readable media are also disclosed.

The progressively adaptive generative "smart" instrument for personalized human motion-based musical compositions and sonification of the present invention is an algorithm / apparatus / device for neurorehabilitation, therapy, and performance using human motion to generate music or data sonification by integrating computer vision (CV) with adaptive musical instrumentation. The present invention provides a real-time generative music engine and framework that integrates digital symbolic representations of music, audio inputs or files, text or voice-prompts, audio inputs or files, and / or musical artifacts. Further, the present invention includes access to a database that stores and catalogs the elements which can be used to guide or generate a personalized musical composition or sonified output, integrating CV and the generative framework, developing a modular "development" style framework, developing progressively adaptive mappings for personalized / customized user interactions with motion-based musical composition and sonified motion, and correlating music and motion data in a digital analytics platform.

A system is provided.SOLUTION: A system comprising: means for generating music for music therapy using a generation AI; means for inputting information on symptoms and preferences of patients; means for transmitting the input information to the generation AI; means for receiving music generated by the generation AI and distributing the music to terminals; and means for storing the music in the terminals of the patients and reproducing the music.SELECTED DRAWING: Figure 1

The invention discloses a college student subject anxiety intervention system based on music therapy and auricular point stimulation, and relates to the technical field of psychological intervention and health management. The system comprises a data acquisition module, an evaluation analysis module, an intervention strategy generation module, a music intervention module, an auricular point stimulation module and an effect feedback module. The data acquisition module is used for acquiring physiological signals of college students, test taking related information and anxiety self-evaluation data; the evaluation analysis module constructs an anxiety grade evaluation model based on the collected data to determine an anxiety grade; the intervention strategy generation module matches a corresponding music therapy and an auricular point stimulation scheme according to the anxiety level; the music intervention module plays personalized music, and the auricular point stimulation module realizes accurate and safe auricular point electrical stimulation through a flexible electrode; the effect feedback module collects physiological signals and subjective feelings in intervention in real time, and dynamically adjusts an intervention scheme. The method combines two therapies to realize individual accurate intervention of anxiety taken by college students, is remarkable in effect and high in safety, and can be widely applied to the field of college psychological health education.

A system is provided.SOLUTION: A system comprising: means for receiving a specific request from a user; means for setting a parameter based on the received request; means for invoking a generative model that generates music using the set parameter; and means for providing the generated music to the user.SELECTED DRAWING: Figure 1

The application discloses a choreography intelligent recommendation method and a matching system, which first extracts the mel-frequency cepstral coefficient and the beat signal of audio to generate music context features, and constructs a dancer skill vector in combination with a dancer body parameter; inputs the music features, the dancer features and an existing primitive sequence into a Transformer decoder to output a first probability distribution of action primitives; then, with the aid of a compatibility encoder, the compatibility of action conversion is calculated, the probability distribution is corrected, a new action primitive is sampled, and a complete primitive sequence is generated through cyclic iteration. Finally, a fluency network is used to score multiple sequences, an optimal sequence is selected, and the optimal sequence is converted into skeletal motion data by relying on an action primitive dictionary. The application effectively solves the problems of harsh action connection and action not meeting the body conditions of dancers in the existing choreography scheme.

Embodiments are disclosed for music generation. The method may include receiving a music prompt and one or more time-varying controls. A text-to-music generative model may generate a representation of music. The text-to-music generative model comprises a pretrained conditional generative model and an adapter control branch. The text-to-music generative model has been fine-tuned to generate the representation of music based on the music prompt and the one or more time-varying controls. The representation of music is converted to music audio and the music audio is output.

The embodiment of the invention relates to a method, device and equipment for generating music, a medium and a program product. The method comprises: based on demonstration music for a music media item, determining a first tone for the music media item and a reference pitch of the music media item, the demonstration music at least comprising lyrics and melody; performing timbre conversion on the reference audio of the lyrics sung with the second timbre by using a first machine learning model to obtain a first audio of the lyrics sung with the first timbre; based on the reference pitch and the demonstration music, using a second machine learning model to generate a second audio including musical instrument playing content, the musical instrument playing content corresponding to the lyrics; and generating a music media item based on the first audio and the second audio.