Neural network music composition by prediction
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|Michael C. Mozer|
|Exploring the benefits of psychophysical constraints and multiscale processing. In algorithmic music composition, a simple technique involves selecting notes sequentially according to a transition table that specifies the probability of the next note as a function of the previous context. Mozer describes an extension of this transition table approach using a recurrent autopredictive connectionist network called CONCERT. CONCERT is trained on a set of pieces with the aim of extracting stylistic regularities. CONCERT can then be used to compose new pieces. A central ingredient of CONCERT is the incorporation of psychologically grounded representations of pitch, duration, and harmonic structure.|
|Resource Types:||Articles, Topic Tools Miscellaneous|
|Math Topics:||Algorithms, Music|
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