Probabilistic (k,l)-Context-Sensitive Grammar Inference with Gibbs Sampling Applied to Chord Sequences

Henrique Lopes, Alan Freitas

Abstract

Grammatical inference in computer music provides us with valuable models for fields such as algorithmic composition, style modeling, and music theory analysis. Grammars with higher accuracy can lead to models that improve the performance of various tasks in these fields. Recent studies show that Hidden Markov Models can outperform Markov Models in terms of accuracy, but there are no significant differences between Hidden Markov Models and Probabilistic Context-Free Grammars (PCFGs). This paper applies a Gibbs Sampling algorithm to infer Probabilistic (k,l)-Context-Sensitive Grammars (P(k,l)CSGs) and presents an application of P(k,l)CSGs to model the generation of chord sequences. Our results show Gibbs Sampling and P(k,l)CSGs can improve on PCFGs and the Metropolis-Hastings algorithm with perplexity values that are 48% lower on average (p-value 0.0026).

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Paper Citation


in Harvard Style

Lopes H. and Freitas A. (2021). Probabilistic (k,l)-Context-Sensitive Grammar Inference with Gibbs Sampling Applied to Chord Sequences.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 572-579. DOI: 10.5220/0010195905720579


in Bibtex Style

@conference{icaart21,
author={Henrique Lopes and Alan Freitas},
title={Probabilistic (k,l)-Context-Sensitive Grammar Inference with Gibbs Sampling Applied to Chord Sequences},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={572-579},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010195905720579},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Probabilistic (k,l)-Context-Sensitive Grammar Inference with Gibbs Sampling Applied to Chord Sequences
SN - 978-989-758-484-8
AU - Lopes H.
AU - Freitas A.
PY - 2021
SP - 572
EP - 579
DO - 10.5220/0010195905720579