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Analysing symbolic music with probabilistic grammars

Abdallah, Samer and Gold, Nicolas and Marsden, Alan (2016) Analysing symbolic music with probabilistic grammars. In: Computational music analysis. Springer, pp. 157-189. ISBN 9783319259291

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Abstract

Recent developments in computational linguistics offer ways to approach the analysis of musical structure by inducing probabilistic models (in the form of grammars) over a corpus of music. These can produce idiomatic sentences from a probabilistic model of the musical language and thus offer explanations of the musical structures they model. This chapter surveys historical and current work in musical analysis using grammars, based on computational linguistic approaches. We outline the theory of probabilistic grammars and illustrate their implementation in Prolog using PRISM. Our experiments on learning the probabilities for simple grammars from pitch sequences in two kinds of symbolic musical corpora are summarized. The results support our claim that probabilistic grammars are a promising framework for computational music analysis, but also indicate that further work is required to establish their superiority over Markov models.

Item Type: Contribution in Book/Report/Proceedings
Subjects:
Departments: Faculty of Arts & Social Sciences > Lancaster Institute for the Contemporary Arts
ID Code: 75618
Deposited By: ep_importer_pure
Deposited On: 14 Sep 2015 16:12
Refereed?: Yes
Published?: Published
Last Modified: 21 Sep 2017 02:43
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/75618

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