Obeebo Labs Ltd.

California Institute of Technology

D-wave Systems Inc.

Colin P Williams

Gregory Gabrenya

Jonathan P Dowling

Jeremy P Hilton

Giovanni Della Rossa

Robert M Gingrich

Computer-based systems, devices, and methods for automatically generating aesthetic chord progressions and key modulations in musical compositions are described. Known harmonic relationships are expanded upon to produce a much richer set of harmonic transition probability models compared to conventional music theory, and these models are leveraged by a computer-based musical composition system to generate new musical compositions and variations of existing musical compositions. Techniques for enabling a computer-based musical composition system to automatically determine when to introduce a key modulation, what key to module to, and what chord progression(s) to use within the new key are all described.

Computer-based systems, devices, and methods for generating aesthetic chord progressions and key modulations in musical compositions

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.

Systems, devices, and methods for assigning mood labels to musical compositions

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).

Systems, devices, and methods for musical catalog amplification services

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, and methods for computer-generated musical compositions

Systems, devices, and methods for encoding the harmonic structure of a musical composition in a digital data structure are described. Tonal and rhythmic commonalities are identified across the musical bars that make up a musical composition. Individual bars of the musical composition are each analyzed to characterize their respective harmonic fingerprints in various forms, and the respective harmonic fingerprints are compared to sort the musical bars into harmonic equivalence categories. Isomorphic mappings between hierarchical data structures that encode the musical composition based on musicality and harmony, respectively, are also described. The systems, devices, and methods for encoding the harmonic structure of a musical composition in a digital data structure have broad applicability in computer-based composition and variation of music.

Systems, devices, and methods for harmonic structure in digital representations of music

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.

Systems, devices, and methods for varying digital representations of music

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.

Systems, devices, and methods for computer-generated musical note sequences

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.

Systems, devices, and methods for decoupling note variation and harmonization in computer-generated variations of music data objects

Systems, devices, and methods for segmenting musical compositions are described. Discrete, musically-coherent segments (such as intro, verse, chorus, bridge, solo, and the like) of a musical composition are identified. Distance measures are used to evaluate whether each bar of a musical composition is more like the bars that directly precede it or more like the bars that directly succeed it, and each respective series of musically similar bars is assigned to the same respective segment. Large changes in the distance measure(s) between adjacent bars may be used to identify boundaries between abutting musical segments. Computer systems and computer program products for implementing segmentation are also described. The results of segmentation may advantageously be applied in computer-based composition of music and musical variations, as well as in other applications involving labelling, characterizing, or otherwise processing music.

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Colin P Williams