Abstract
We use stochastic deterministic finite automata to model musical styles: a same automaton can be used to classify new melodies but also to generate them. Through grammatical inference these automata are learned and new pieces of music can be parsed. We show that this works by proposing promising classification results.
This work was supported in part by the IST Programme of the European Community, under the Pascal Network of Excellence, IST-2002-506778. This publication only reflects the authors’ views.
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de la Higuera, C., Piat, F., Tantini, F. (2006). Learning Stochastic Finite Automata for Musical Style Recognition. In: Farré, J., Litovsky, I., Schmitz, S. (eds) Implementation and Application of Automata. CIAA 2005. Lecture Notes in Computer Science, vol 3845. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11605157_31
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DOI: https://doi.org/10.1007/11605157_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31023-5
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