A musical piece inference device includes an electronic controller configured to execute a data acquisition module, an inference module, and an output module. The data acquisition module is configured to acquire target data including an input token sequence that is arranged to indicate at least a part of a musical piece and includes a plurality of bar-line/beat tokens arranged to indicate bar-line/beat positions of at least the part of the musical piece. The bar-line/beat positions are positions of bar lines of at least the part of the musical piece, positions of beats of at least the part of the musical piece, or both. The inference module is configured to, by using a trained inference model, generate an output token sequence indicating a result of an inference with respect to the musical piece from the input token sequence. The output module is configured to output the result of the inference.

A method, system, and medium for affective music recommendation and composition. A listener's current affective state and target affective state are identified, and an audio stream, such as a music playlist, is generated with the intent of effecting a controlled trajectory of the listener's affective state from the current state to the target state. The audio stream is generated by a machine learning system trained using data from the listener and/or other users indicating the effectiveness of specific audio segments, or audio segments having specific features, in effecting the desired affective trajectory. The audio stream is presented to the user as an auditory stimulus. The machine learning system may be updated based on the affective state changes induced in the listener after exposure to the auditory stimulus. Over time, the machine learning system gains a robust understanding of the relationship between music and human affect, and thus the machine learning system may also be used to compose, master, and/or adapt music configured to induce specific affective responses in listeners.

In a synthesizer 1, the highest note number is set from the allowed Oct width and the lowest note number of a sound production part in a setting table 11e, and if the note number of an Arp note memory 12b is not between the lowest note number and the highest note number, the note number of one octave unit is added to or subtracted from the note number of the Arp note memory 12b. Consequently, the note number of the Arp note memory 12b is corrected to the pitch range between the lowest note number and the highest note number, and thus can be corrected to the sound production pitch range of the timbre of the sound production part, and arpeggios can be outputted using sounds that are more appropriate for an instrument of said timbre.

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.

An information processing method is an information processing method including generating an output track by using an input track including a plurality of first information elements provided over a certain period or a certain section and a learned model (21), in which the output track includes a first track that is a same track as the input track or a changed track, and a second track including a plurality of second information elements provided over the certain period or the certain section, and the learned model (21) is a learned model generated by using training data so as to output output data corresponding to the output track when input data corresponding to the first track is input.

The disclosure provides an automatic performance apparatus, an automatic performance method, and a non-transitory computer readable medium. Notes to be sounded are stored in chronological order for each beat position which is a sound generation timing in a performance pattern. A probability of generating sound at the beat position is stored for each beat position in a sound generation probability pattern. According to the probability stored in the sound generation probability pattern, it is determined whether to generate sound or not for each beat position of the performance pattern.

A music information generating device, including: a block color name recognizing part which selects and determines, from among plural color names which are made to correspond to plural ranges of color attribute value having been set beforehand, a color name corresponding to the representative-color of the block as a block color name of the block, by recognizing to which range of the color attribute value the representative-color of the block belongs, where the plural color names have been made or are going to be made to correspond to the plural sound-source names having been stored; and a diagram music-score generating unit which selects, based on a criterion having been set beforehand, a designated block from among the blocks having been arranged in lattice shape, and thereby generates a diagram music-score.

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 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 support maintenance of musical form. Independent aspects of the disclosure further ensure that, within the composition work, such as a media product or a real-time audio stream, chord spacing determination and control are practiced to maintain musical sense in the new composition. Further, a structuring of primitive heuristics operates to maintain pitch and permit key transformation. The system and its functionality provides signal analysis and music generation through allowing emotional connotations to be specified and reproduced from cross-referenced Form-Atoms.

Provided is an automatic music playing control device that provides an instruction of playing music, the control device implementing natural music playing capable of expressing the timing and voicing in live music playing of a musical instrument by a player. The automatic music playing control device includes at least one processor, and the at least one processor selects a voicing pattern corresponding to a combination of the probabilistically-selected number of sounds to be emitted and a decided voicing type corresponding to a range from among a plurality of voicing patterns based on a scale decided according to the tune and chords of a music piece and instructs a sound source to emit a chord voiced based on the selected voicing pattern.