@inproceedings{d1cfecc0bfe74f93b2842e44a02371f0,
title = "The clustering of expressive timing within a phrase in classical piano performances by Gaussian mixture models",
abstract = "In computational musicology research, clustering is a common approach to the analysis of expression. Our research uses mathematical model selection criteria to evaluate the performance of clustered and non-clustered models applied to intra-phrase tempo variations in classical piano performances. By engaging different standardisation methods for the tempo variations and engaging different types of covariance matrices, multiple pieces of performances are used for evaluating the performance of candidate models. The results of tests suggest that the clustered models perform better than the non-clustered models and the original tempo data should be standardised by the mean of tempo within a phrase.",
keywords = "Classical piano performance, Intra-phrase tempo, Model analysis, Model selection criteri",
author = "Shengchen Li and Black, {Dawn A.A.} and Plumbley, {Mark D.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 11th International Symposium on Computer Music Multidisciplinary Research, CMMR 2015 ; Conference date: 16-06-2015 Through 19-06-2015",
year = "2016",
doi = "10.1007/978-3-319-46282-0_21",
language = "English",
isbn = "9783319462813",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "322--345",
editor = "Richard Kronland-Martinet and Mitsuko Aramaki and S{\o}lvi Ystad",
booktitle = "Music, Mind, and Embodiment - 11th International Symposium, CMMR 2015, Revised Selected Papers",
}