Computer-based systems, devices, and methods for assigning mood labels to musical compositions are described. A mood classifier is trained based on mood-labeled musically-coherent segments of musical compositions and subsequently applied to automatically assign mood labels to musically-coherent segments of musical compositions. In both cases, the musically-coherent segments are generated using automated segmentation algorithms.

Computer-based systems, devices, and methods for generating variations of musical compositions are described. Musical compositions stored in digital media include one or more music data object(s) that encode notes. A first set of notes is characterized and a transformation is applied to replace at least one note in the first set of notes with at least one note in a second set of notes. The transformation may explore or call upon the full range of musical notes available without being constrained by conventions of musicality and harmony. For each particular note in the second set of notes that replaces a note in the first set of notes, whether the particular note is in musical harmony with other notes in the music data object is separately assessed and, if not, the particular note is adjusted to bring it into musical harmony with other notes in the music data object.

Computer-based systems, devices, and methods for generating musical compositions are described. A population of musical compositions stored in digital media are each segmented to produce abridged samples. The samples are analyzed to identify “parent” compositions that best exhibit or evoke a particular desired quality. The parent compositions are cross-bred to generate a set of child compositions which are similarly segmented and analyzed. The child compositions that best exhibit or evoke the particular desired quality are re-cast as parent compositions from which another generation of child compositions are bred. Mutations in the form of musical variations are inserted in at least some iterations and the process is repeated until at least one child composition that satisfies some exit criterion is returned.

Computer-based systems, devices, and methods for generating musical note sequences are described. One or more musical composition(s) stored in digital media include one or more data object(s) that encode notes and/or note sequences. At least one note sequence is processed to form a time-ordered sequence of parallel notes, which is analyzed to determine a k-back probability transition matrix for the at least one note sequence. An attribute, such as a style, of the at least one note sequence is thus encoded and used to generate new note sequences that embody a similar attribute or style. In some implementations, the at least one note sequence may include a concatenated set of note sequences representative of a particular library of musical compositions.

Described herein are techniques for synthesizing waves (e.g., audio waveforms) at various frequencies. For example, techniques described herein may be used to render musical notes by generating audio waveforms. According to some embodiments, the techniques generate a wave table for an audio waveform based on a set of partial waveforms. The system determines a set of notes with a corresponding entry in the wave table and determines a set of partials for each note. The system renders, for each note, an associated waveform comprising the associated number of partials for the note from the set of partial waveforms.

The present disclosure relates to a system and method for matching performance with score. The method may include acquiring performance information in a preset time period, wherein the performance information is related to a musical device. The method may also include analyzing the performance information and obtaining a played music score in the preset time period, wherein the played music score contains the performance information. The method may further include comparing the played music score with one or more standard music scores. The method may still further include identifying a standard music score from the one or more standard music score based on the comparison of the played music score with the one or more standard music scores, wherein a matching degree between the played music score and the identified standard music score reaches a preset value.

A method including: receiving a music input; determining values of musical parameters based on the input; generating a spatial representation of the music input based on the values; and at a plurality of haptic actuators defining a spatial distribution, cooperatively producing a haptic output based on the spatial representation. A method including: mechanically coupling haptic actuators defining a multidimensional array to a user; receiving a music input; generating a spatial representation of the music input defined on a multidimensional space, wherein the multidimensional space and the multidimensional array have equal dimensionality; and, for each haptic actuator: based on the haptic actuator location within the multidimensional array, determining a corresponding location within the multidimensional space; based on a value of the spatial representation associated with the corresponding location, determining an actuation intensity; and controlling the haptic actuator to actuate based on the actuation intensity.

Computer-based systems, devices, and methods for generating variations of musical compositions are described. Musical compositions stored in digital media include one or more music data object(s) that encode notes. A first set of notes is characterized and a transformation is applied to replace at least one note in the first set of notes with at least one note in a second set of notes. The transformation may explore or call upon the full range of musical notes available without being constrained by conventions of musicality and harmony. For each particular note in the second set of notes that replaces a note in the first set of notes, whether the particular note is in musical harmony with other notes in the music data object is separately assessed and, if not, the particular note is adjusted to bring it into musical harmony with other notes in the music data object.

Computer-based systems, devices, and methods for generating musical note sequences are described. One or more musical composition(s) stored in digital media include one or more data object(s) that encode notes and/or note sequences. At least one note sequence is processed to form a time-ordered sequence of parallel notes, which is analyzed to determine a k-back probability transition matrix for the at least one note sequence. An attribute, such as a style, of the at least one note sequence is thus encoded and used to generate new note sequences that embody a similar attribute or style. In some implementations, the at least one note sequence may include a concatenated set of note sequences representative of a particular library of musical compositions.

Methods, systems and apparatus to characterize audio using transchromagrams are disclosed. An example apparatus includes a transchromagram generator to generate a data structure based on a set of transition matrices corresponding to a plurality of time frames of audio data, the data structure indicative of probabilities that first musical notes will transition to second musical notes, a database controller to prompt a database to store the data structure within the audio data, and a notification manager to generate, based on a comparison between query audio data and the stored data structure of the audio data, a notification identifying at least one characteristic of the query audio data.