18 results about "Generative music" patented technology

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 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.

Methods, systems, and apparatus for generating outputs using machine learning models conditioned on inputs, including computer programs encoded on a computer storage medium. In one aspect, a method includes: receiving inputs that include at least (i) a musical input audio signal representing music and (ii) a vocal input audio signal representing a vocal sample of a particular speaker; obtaining text data representing lyrics; obtaining a plurality of audio lexical units; obtaining a plurality of text lexical units; obtaining an output audio signal representing music by providing a model input, including at least the plurality of audio lexical units and the plurality of text lexical units, as input to a machine learning model; and providing an output audio signal generated by the machine learning model representing music including lyrics sung by a particular speaker from the input audio signal.

An electronic device includes a plurality of operators and outputs a musical tone. The electronic device includes a hardware processor configured to deform a timbre waveform, which is a basic waveform representing a timbre of the musical tone being output, based on a setting value according to an operation on each of the operators; generate the musical tone based on the deformed timbre waveform and pitch information that is input; and output the generated musical tone.

This provides a method for creating sounds that can be generated based on videos, making music suitable for industrial use. [Solution] The method for creating sound involves the device identifying motion features, which are characteristics of the movement of objects in the video, and requesting the AI ​​to generate music where the time between similar motion features is used as the unit of time, with each unit of time being a beat.

Embodiments are disclosed for music generation. The method may include receiving a text input describing music to be generated by a neural network and obtaining an initial noise laten. The neural network generates a music spectrogram based on the initial noise latent and the text input. One or more features are extracted from the music spectrogram. A loss is determined based on the one or more features from the music spectrogram and one or more target features of a target output. An optimized noise latent is obtained based on the loss and a new music spectrogram is generated using the optimized noise latent.

The problem that this invention aims to solve is to provide a technology that can generate sheet music for music games that can reproduce songs through user operation. [Solution] To solve the above problems, the present invention provides a music game system for generating sheet music for a music game from a music sound source, wherein the music game system comprises a part separation unit, a beat detection unit, an onset detection unit, and a sheet music generation unit, wherein the part separation unit separates music parts based on the music sound source and acquires music part information, the beat detection unit detects beat information based on the music sound source, the onset detection unit detects onset information for each music part based on the music part information, and the sheet music generation unit generates sheet music data in which note objects for the music game are arranged based on the beat information and the onset information.

A method for generating music, the method comprising: determining a genre of the music; determining a rule for generating the music based on the genre, wherein the rule specifies a structure of the music; selecting a plurality of samples from a database; modifying the plurality of samples based on the structure; assembling the plurality of modified samples into a plurality of tracks based on the structure; and mastering the plurality of tracks to generate the music, wherein the structure comprises at least one of tempo of the music, key of the music, bar number of the music, tracks included in the music and instruments used in the music.

The application provides an automatic music description generation method, including the following steps: step 1, collecting music and text data; step 2, constructing a music description generation model MuTeNet; the music description generation model includes a music and text codec; the music and text codec includes a music codec, namely a music encoder and a music decoder, and a text codec, namely a text encoder and a text decoder; step 3, pre-training the music and text codec in the music description generation model; step 4, preparing training data, inputting into the pre-trained music description generation model, and training; the training data are music and paired text descriptions; and step 5, inputting music into the trained model to generate a text description of the music, and completing automatic music description generation.

This invention provides a method for instructing an AI to identify motion features—characteristics of the movement of objects within a video—and to generate music where the time between similar motion features is used as the unit of time, with each unit of time being a beat. [Solution] The method involves a device identifying motion features, which are characteristics of the movement of objects in a video, and generating music in which the beats are the unit times that appear relatively frequently among two or more unit times resulting from similar motion features.

The problem that this invention aims to solve is to provide a technology that can generate sheet music for music games that can reproduce songs through user operation. [Solution] To solve the above problems, the present invention provides a music game system for generating sheet music for a music game from a music sound source, wherein the music game system comprises a part separation unit, a beat detection unit, an onset detection unit, and a sheet music generation unit, wherein the part separation unit separates music parts based on the music sound source and acquires music part information, the beat detection unit detects beat information based on the music sound source, the onset detection unit detects onset information for each music part based on the music part information, and the sheet music generation unit generates sheet music data in which note objects for the music game are arranged based on the beat information and the onset information.

This provides a method for creating industrially usable music based on video. [Solution] A method for creating sound, wherein the device identifies motion features, which are characteristics of the movement of objects in a video, and requests the AI ​​to generate music in which the time between similar motion features is used as the unit time, and the unit time is used as the beat.

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.

This invention discloses a real-time music generation and audio-visual linkage method and system based on speech feature analysis, including: acquiring user speech and verifying its validity; extracting acoustic features such as fundamental frequency, energy, and rhythm from valid speech, mapping them to music composition parameters such as mode, tempo, note density, and dynamics; generating structured music data based on the music composition parameters and rendering and playing it; analyzing the audio signal during playback in real time, extracting the beat signal and full-band RMS power; controlling particle emission density, diffusion speed, and glow brightness based on the beat signal, and controlling the color shift of the screen based on the cumulative phase of the full-band RMS power, driving the visual content to dynamically and synchronously change with the music. This invention achieves real-time generation of personalized music based on user speech features, and uses the generated music to drive the visuals, forming an immersive interactive experience with deep audio-visual linkage; the entire process is performed locally, without a network, meeting the requirements of real-time response and stable offline operation.

This invention relates to the field of personalized recommendation technology, specifically to a method, system, device, and medium for personalized music content push, comprising the following steps: collecting user playlists to generate a behavioral feature matrix, then filtering songs according to playback duration and interaction behavior, generating real genre tags and filtering irrelevant songs to obtain a preference matrix, assigning weighted cumulative ranking to song tags, and generating a music recommendation list based on preference tags from the music library. In this invention, multi-dimensional interaction and content attribute data are collected based on user playlists to construct a refined behavioral feature system. Invalid interference and non-preference-related content are eliminated through dual data filtering, reducing the proportion of noise samples from the source. Combined with the playback ratio and interaction type, differentiated weights are assigned, and related content tags are used to complete the weighted cumulative ranking, accurately anchoring the user's real music aesthetic preferences, significantly improving the matching degree between recommended content and the user's real listening needs, and optimizing the accuracy of music push and user experience.

The application discloses a brain TV listens to a kind of music generation method for fine-grained emotion recognition based on multi-modal fusion, comprising: collecting multi-modal physiological and audio-visual signals, and performing millisecond-level time alignment;Feature extraction is carried out on the electroencephalogram mode and audio-visual mode;Emotion features are fused through cross-modal attention, and emotion state output is calculated;Emotion-music mapping is constructed to generate initial music parameters;Personalized music strategy is generated using reinforcement learning, and music is generated according to the personalized music strategy;Play music and collect physiological feedback in real time, calculate emotion offset;Adjust the music parameters according to the emotion offset until the final personalized music generation strategy is determined and the music generation result is output.The application can continuously improve the effectiveness of the personalized music emotion regulation method in real use scenarios, so that the system becomes more and more suitable for the emotion characteristics and reaction patterns of specific users in long-time and multiple interactions, and finally realizes fine, stable and self-adaptive emotion regulation effect.