Music compilation methods disclosed herein include providing a database. Data is stored therein associating a user with access credentials for a plurality of music streaming services. A first server is communicatively coupled with the database and with multiple third party servers each of which includes a music library associated with the user. A list is stored in the database listing audio tracks of the libraries. A play selector is displayed on a user interface of a computing device communicatively coupled with the first server. User selection of the play selector initiates playback of a sample set, the sample set including portions of audio tracks in the list. The sample set is determined based on contextual information gathered by the computing device, the contextual information not including any user selection. Music compilation systems disclosed herein include systems configured to carry out the music compilation methods.

An information processing apparatus according to the present disclosure includes: an acquisition unit that acquires music information; an extraction unit that extracts a plurality of types of feature amounts from the music information acquired by the acquisition unit; and a generation unit that generates information in which the plurality of types of feature amounts extracted by the extraction unit is associated with predetermined identification information as music feature information to be used as learning data in composition processing using machine learning.

An information processing apparatus according to the present disclosure includes: a storage unit that stores a plurality of pieces of music feature information in which a plurality of types of feature amounts extracted from music information is associated with predetermined identification information, the music feature information being used as learning data in composition processing using machine learning; a reception unit that receives instruction information transmitted from a terminal apparatus; an extraction unit that extracts the music feature information from the storage unit according to the instruction information; and an output unit that outputs presentation information of the music feature information extracted by the extraction unit.

A method for automatically generating an audio signal, the method comprising receiving a source audio signal analyzing the source audio signal to identify a musical parameter characteristic thereof obtaining a supplemental audio signal based on the identified musical parameter characteristic and combining the source audio signal and the supplemental audio signal to form an extended audio signal.

An arrangement generation method executed by a computer includes acquiring target musical piece data that include performance information that indicates a melody and a chord of at least a part of a musical piece and include meta information that indicates characteristics of at least the part of the musical piece, generating, from the acquired target musical piece data, by using a generative model trained by machine learning, arrangement data obtained by arranging the performance information in accordance with the meta information, and outputting the generated arrangement data.

An apparatus, method, and computer-readable storage medium that generate a harmonized musical piece. The method includes receiving a chord selection including a musical key and a scale selection, generating, within a digital audio work session, a chord progression sequence based on the received chord selection, in response to a detected chord selection change, modifying the chord progression sequence to include a chord progression corresponding to the chord selection change, setting the chord progression sequence as a master sequence, in response to detecting a second progression sequence within the digital audio work session, transmitting an identifier to the second progression sequence setting it as a slave sequence, and establishing a synchronized communication link between the master and the slave sequences such that changes made in the master sequence are automatically effectuated in the slave sequence, and combining the master sequence and the slave sequence to form a composed musical piece.

The invention generates progressive music in real-time for video games using random, seeded random, and manually input variables to affect melody, phrase length, harmonic chords and complexity, and percussive accompaniment. As the game is played, variables may be passed in that change the music to increase or decrease complexity and tension levels and to interpolate between styles. The generated music then progresses from stable, simple, and consonant to more tense, dissonant, and complex melodies, harmonies and rhythms, and back to the original stage as a musical resolution. Through variables controlling musical parameters, music may progressively change from the atonal region where there is no clear resolution or stability, to tonal, where there is only consonance and stability, and anywhere in between. These variables are assigned through a middleware or a game-engine setup that uses the current device as an audio source plugin, or manually coded into the individual video game.

A computer-implemented method of generating a musical composition containing a plurality of musical texture groups is disclosed. The method includes assembling musical texture groups from musical instrument components and associating therewith a tag expressing emotional textural connotation. The instrument components have musical textural classifiers selected from a set of pre-defined textural classifiers such that different instrument components may have a different subset of pre-defined textural classifiers. The textural classifiers within a texture group possess either no musical feature attribute or a single musical feature attribute and any number of musical accompaniment attributes. The method then generates at least one chord scheme to a narrative brief, to provide an emotional connotation to a series of events, the chord scheme generated by selecting and assembling Form Atoms. The final step includes applying a texture to the chord scheme to generate the musical composition reflecting the narrative brief.

A generative composition system reduces existing musical artefacts to constituent elements termed “Form Atoms”. These Form Atoms may each be of varying length and have musical properties and associations that link together through Markov chains. To provide myriad new composition, a set of heuristics ensures that musical textures between concatenated musical sections follow a supplied and defined briefing narrative for the new composition whilst contiguous concatenated Form Atoms are also automatically selected to see that similarities in respective and identified attributes of musical textures for those musical sections are maintained to maintain good musical form. Within the composition work, chord spacing and control are practiced to maintain musical sense in the new composition and a primitive heuristics structure maintains pitch and permits key transformation. The system provides signal analysis and music generation by allowing emotional connotations to be specified and reproduced from cross-referenced Form-Atoms.

A musical piece structure analysis method includes acquiring an acoustic signal of a musical piece, extracting a first feature amount indicating changes in tone from the acoustic signal of the musical piece, extracting a second feature amount indicating changes in chords from the acoustic signal of the musical piece, outputting a first boundary likelihood indicating likelihood of a constituent boundary of the musical piece from the first feature amount using a first learning model, outputting a second boundary likelihood indicating likelihood of the constituent boundary of the musical piece from the second feature amount using a second learning model, identifying the constituent boundary of the musical piece by performing weighted synthesis of the first boundary likelihood and the second boundary likelihood, and dividing the acoustic signal of the musical piece into a plurality of sections at the constituent boundary that has been identified.