A method and apparatus for the creation and playback of music and/or sound, so that sound sequences are generated that vary from one playback to another playback. In one embodiment, during composition creation, artist(s) may define how the composition may vary from playback to playback using visually interactive display(s). The artist's definition may be embedded into a composition dataset. During playback, a composition data set may be processed by a playback device and/or a playback program, so that each time the composition is played-back a unique version may be generated. Variability during playback may include: the variable selection of alternative sound segment(s); variable editing of sound segment(s) during playback processing; variable placement of sound segment(s) during playback processing; the spawning of group(s) of alternative sound segments from initiating sound segment(s); and the combining and/or mixing of alternative sound segments in one or more sound channels. MIDI-like variable compositions and the variable use of sound segments comprised of a timed sequence of MIDI-like commands are also disclosed.

Systems, devices, and methods for encoding digital representations of musical compositions are described. Various components of a musical composition that are defined in modern music theory, such as notes and bars, are encoded as respective hierarchically-dependent data objects in a data file. The hierarchically-dependent data objects encode the musical composition in a tree-like data structure with modular nodes and adjustable relationships between nodes. Note start times and beat start times are encoded independently of one another and characterized by a timing relationship that captures the expressiveness imbued when notes and beats are not precisely synchronized. Musical variations that preserve the timing relationship between the notes and beats of the original composition are also generated and encoded.

Musical catalog amplification services that leverage or deploy a computer-based musical composition system are described. The computer-based musical composition system employs algorithms and, optionally, artificial intelligence to generate new music based on analyses of existing music. The new music may be wholly distinctive from, or may include musical variations of, the existing music. Rights in the new music generated by the computer-based musical composition system are granted to the rights holder(s) of the existing music. In this way, the musical catalog(s) of the rights holder(s) is/are amplified to include additional music assets. The computer-based musical composition system may be tuned so that the new music sounds more like, or less like, the existing music of the rights holder(s). Revenues generated from the new music are shared between the musical catalog amplification service provider and the rights holder(s).

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.

Systems, devices, media, and methods are presented for playing audio sounds, such as music, on a portable electronic device using a digital color image of a note matrix on a map. A computer vision engine, in an example implementation, includes a mapping module, a color detection module, and a music playback module. The camera captures a color image of the map, including a marker and a note matrix. Based on the color image, the computer vision engine detects a token color value associated with each field. Each token color value is associated with a sound sample from a specific musical instrument. A global state map is stored in memory, including the token color value and location of each field in the note matrix. The music playback module, for each column, in order, plays the notes associated with one or more the rows, using the corresponding sound sample, according to the global state map.

Disclosed is a method for simulating a musical phrase, wherein the musical phrase includes a sequence of notes, the method comprising generating timbral fingerprints associated with a sample library that comprises recordings of a plurality of notes in a plurality of intensities, using a linear predictive coding technique, wherein the timbral fingerprints relate to the plurality of intensities of the plurality of notes; determining an origin intensity for the musical phrase, wherein the origin intensity is one intensity selected from amongst the plurality of intensities; and simulating each note in the sequence of notes, by morphing a recording of each note in the origin intensity according to timbral fingerprints of the note in the plurality of intensities, for simulating the musical phrase.

A processor-based method of producing a generative musical composition is disclosed herein. The method includes the step of receiving a briefing narrative which describes a musical journey by referencing a plurality of emotional descriptions related to a plurality of musical sections. The generative musical composition is assembled with regard to the briefing narrative through the selection and concatenation of Form Atoms with tags that align with the emotional descriptions related to the musical sections. The Form Atoms, which have compositional nature aligned with the emotional descriptions and self-contained constructional properties representative of the historical corpus of music, are then selected and substituted into the generative composition. The method further involves the step of generating the musical composition by mapping musical transition between selectively chosen Form Atoms to reflect pre-established transitions between Form Atoms and groups Form Atoms that have been identified to have similar tags but different constructional properties.

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.