A controller for real-time visual display of music includes a music analysis module and a display control module. The music analysis module receives an audio input, determines human perceived musical structures, human felt affect and emotion as a function of the audio input, and outputs a signal corresponding to the determined structure, affect and emotion. The display control module is operatively coupled to the music analysis module and receives the signal and controls a visual display as a function thereof to express the determined musical structure, affect and emotion in a visual manner.

A method includes displaying a user interface of a digital audio workstation, which includes a first region for generating a composition. The first region includes a first compositional segment that has been added to the composition by a user. Based on the first compositional segment, one or more recommended predefined compositional segments are identified and displayed in a second region. The method includes receiving the selection of a second compositional segment. The method includes adding the compositional segment to the composition.

Methods, apparatus, systems and articles of manufacture are disclosed methods and apparatus for audio equalization based on variant selection. An example apparatus includes a processor to obtain training data, the training data including a plurality of reference audio signals each associated with a variant of music and organize the training data into a plurality of entries based on the plurality of reference audio signals, a training model executor to execute a neural network model using the training data, and a model trainer to train the neural network model by updating at least one weight corresponding to one of the entries in the training data when the neural network model does not satisfy a training threshold.

A method for recognizing a song, including: acquiring a target song segment and transforming the target song segment to generate a corresponding first spectrum map; generating a multi-dimensional first feature vector according to the first spectrum map and a preset neural network model; acquiring second feature vectors of pre-stored songs, wherein one pre-stored song is divided into a plurality of pre-stored song segments, one pre-stored song segment corresponds to one second feature vector, and the first feature vector and the second feature vectors have the same number of dimensions; calculating similarities between the first feature vector and the second feature vectors, and determining a maximum similarity; and determining that the target song segment and a pre-stored song corresponding to the maximum similarity are different versions of the same song in response to the maximum similarity being greater than a preset threshold.

A method for training one or more AI models for generating audio scores accompanying visual datasets includes obtaining training data comprising a plurality of audiovisual datasets and analyzing each of the plurality of audiovisual datasets to extract multiple visual features, textual features, and audio features. The method also includes correlating the multiple visual features and textual features with the multiple audio features via a machine learning network. Based on the correlations between the visual features, textual features, and audio features, one or more AI models are trained for composing one or more audio scores for accompanying a given dataset.

The present disclosure provides method and apparatus for providing personalized songs in automated chatting. A message may be received in a chat flow. Personalized lyrics of a user may be generated based at least on a personal language model of the user in response to the message. A personalized song may be generated based on the personalized lyrics. The personalized song may be provided in the chat flow.

Disclosed herein are computer-implemented method, system, and computer-readable storage-medium embodiments for implementing template-based excerpting and rendering of multimedia performances technologies. An embodiment includes at least one computer processor configured to retrieve a first content instance and corresponding first metadata. The first content instance may include a first plurality of structural elements, with at least one structural element corresponding to at least part of the first metadata. The first content instance may be transformed by a rendering engine running on the at least one computer processor and/or transmitted to a content-playback device.

Systems and methods for visualizations of music may include one or more processors which receive an audio input, and compute a simulation of a human auditory periphery using the audio input. The processor(s) may generate one or more visual patterns on a visual display, according to the simulation, the one or visual patterns synchronized to the audio input.

An electronic musical instrument includes an operation unit that receives a user performance; and at least one processor. wherein the at least one processor performs the following: in accordance with a user operation specifying a chord on the operation unit, obtaining lyric data of a lyric and obtaining a plurality of pieces of waveform data respectively corresponding to a plurality of pitches indicated by the specified chord; inputting the obtained lyric data to a trained model that has been trained and learned singing voices of a singer so as to cause the trained model to output acoustic feature data in response thereto; synthesizing each of the plurality of pieces of waveform data with the acoustic feature data so as to generate a plurality of pieces of synthesized waveform data; and outputting a polyphonic synthesized singing voice based on the generated plurality of pieces of synthesized waveform data.

In implementations of searching for music, a music search system can receive a music search request that includes a music file including music content. The music search system can also receive a selected musical attribute from a plurality of musical attributes. The music search system includes a music search application that can generate musical features of the music content, where a respective one or more of the musical features correspond to a respective one of the musical attributes. The music search application can then compare the musical features that correspond to the selected musical attribute to audio features of audio files, and determine similar audio files to the music file based on the comparison of the musical features to the audio features of the audio files.