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Using Multidimensional Sequences For Improvisation In The OMax Paradigm

Abstract

Automatic music improvisation systems based on the OMax paradigm use training over a one-dimensional sequence to generate original improvisations. Different systems use different heuristics to guide the improvisation but none of these benefits from training over a multidimensional sequence. We propose a system creating improvisation in a closer way to a human improviser where the intuition of a context is enriched with knowledge. This system combines a probabilistic model taking into account the multidimen-sional aspect of music trained on a corpus, with a factor oracle. The probabilistic model is constructed by interpolating sub-models and represents the knowledge of the system, while the factor oracle (structure used in OMax) represents the context. The results show the potential of such a system to perform better navigation in the factor oracle, guided by the knowledge on several dimensions.
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Dates and versions

hal-01346797 , version 1 (19-07-2016)

Identifiers

  • HAL Id : hal-01346797 , version 1

Cite

Ken Déguernel, Emmanuel Vincent, Gérard Assayag. Using Multidimensional Sequences For Improvisation In The OMax Paradigm. 13th Sound and Music Computing Conference, Aug 2016, Hamburg, Germany. ⟨hal-01346797⟩
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