The automatic performance device includes a storage part for storing a plurality of performance patterns, a performance part for playing a performance on the basis of a performance pattern stored in the storage part, an input part for inputting performance information through an input device that receives a performance operation of a user, and a selection part for selecting a performance pattern being a maximum likelihood estimation from the plurality of performance patterns stored in the storage part on the basis of the performance information input to the input part.

A musical audio composition is generated based on a content library. The library is a collection of sequences and instruments. Sequences are partial musical compositions, while instruments are groups of audio samples. Instruments are made of audio data and musical data describing the events recorded in the audio. The process begins by reading the library. A new chain is created. A succession of sequences are selected to create a series of segments in the chain. The events in the selected sequences determine the selection of instruments. Algorithms determine the final arrangements and exact modulations of source audio to target outputs. The source audio are modulated, mixed and output as a stream of audio data. Finally the selections and events of the finished segment are output as metadata. An unlimited number of segments can be fabricated in series, each building and evolving from the preceding segments in the chain.

Embodiments of the present invention provide for the composition of new music based on analysis of unprocessed audio, which may be in the form of melodic hums and rhythmic taps. As a result of this analysismusic information retrieval or MIRmusical features such as pitch and tempo are output. These musical features are then used by a composition engine to generate a new and socially co-created piece of content represented as an abstraction. This abstraction is then used by a production engine to produce audio files that may be played back, shared, or further manipulated.

Provided are a method and apparatus for determining an audio, an electronic device, and a storage medium. The method includes: a chord corresponding to an input audio is determined in response to receiving the input audio; at least one to-be-selected arrangement style is determined according to the chord and/or a melody attribute of the input audio; at least one to-be-selected arrangement template associated with a target arrangement style is displayed based on a trigger operation to the at least one to-be-selected arrangement style; and a target audio is played based on a trigger operation to the at least one to-be-selected arrangement template.

The present disclosure relates to a song generation method, apparatus and system, and a storage medium. The song generation method includes acquiring a target lyric text input by a user; aligning the target lyric text with a singing melody of an initial song, to determine correspondence between text units in the target lyric text and notes in the singing melody, wherein the singing melody is a singing melody of initial lyrics in the initial song; performing voice synthesis on the target lyric text based on the correspondence between the text units in the target lyric text and the notes in the singing melody, to obtain a singing voice singing the target lyric text with the singing melody; and combining the singing voice with an accompaniment audio of the initial song to generate a target song.

According to an embodiment, there is provided a system and method for automatic AI-based song construction based on ideas of a user. It provides and benefits from a combination of expert knowledge resident in an expert engine which contains rules for a musically correct song generation and machine learning in an AI-based audio loop selection engine for the selection of fitting audio loops from a database of audio loops. Additionally, in some embodiments there is provided a method of energy-based song construction where the tracks of a multi-track work are balanced depending on the desired output volume level of the final project.

According to an embodiment, there is provided a system and method for automatic AI-based song construction based on ideas of a user. It provides and benefits from a combination of expert knowledge resident in an expert engine which contains rules for a musically correct song generation and machine learning in an AI-based audio loop selection engine for the selection of fitting audio loops from a database of audio loops. Additionally, in some embodiments there is provided a method of energy-based song construction where the tracks of a multi-track work are balanced depending on the desired output volume level of the final project.

A first computer implements an audio mash-up computer program with a remote computer providing back-end operations via a data communications network. A graphical user interface on the first computer runs an audio mash-up computer program that provides digital content on the graphical user interface for identifying a plurality of respective audio sources of audio segments to combine into an output audio file. The graphical user interface is configured for displaying the respective audio sources as representative blocks of source data and allows a user to engage in arranging the representative blocks into lanes of respective audio tracks displayed on the graphical user interface. By combining the respective audio tracks into the output audio file according to an arrangement of the representative blocks as displayed in the lanes of respective audio tracks, the output audio file is configured for playing the respective audio tracks according to the arrangement.

The present disclosure relates to an apparatus, system, and method that allow non-musicians to compose and perform a musical composition. Although some existing electronic devices can provide a virtual environment to compose and play musical sound digitally, manipulating such a virtual environment can be difficult and may require specific software expertise, as well as knowledge of music theory. The present disclosure provides a platform that facilitates the creation of a musical composition without such software expertise or knowledge of music theory. The platform models a musical composition as a simultaneous playback of one or more musical contents. The platform allows players to control or modify one or more of the plurality of musical contents to generate or synthesize a musical composition.

A method and system for analyzing patterns in the relationships of notes of an input piece of music. The method comprises generating a set of the most frequently occurring note pitches in ascending pitch order that matches an interval pattern, and detecting out-of-key pitches that lie outside of this internal pattern. One or more potential key sequence bifurcations are identified which represent a list of possible key sequences according to forwards and backwards analysis. By finding patterns of repetition in the chordal sequences that may be generated according to these key sequence bifurcations, a key sequence that allows the most frequently recurring chord sequences may be chosen. Chord sequences may be analyzed by using ghost chords, temporary harmonic structures that are created, updated and finalized over time according to a combination of essential and inessential note fragments. The method further comprises identifying non-harmony pitches according to the analyzed chord sequence.