@inproceedings{c699ca9c140b4e5dae686d04614d60a1,
title = "Music pattern discovery with variable Markov oracle: A unified approach to symbolic and audio representations",
abstract = "This paper presents a framework for automatically discovering patterns in a polyphonic music piece. The proposed framework is capable of handling both symbolic and audio representations. Chroma features are post-processed with heuristics stemming from musical knowledge and fed into the pattern discovery framework. The pattern-finding algorithm is based on Variable Markov Oracle. The Variable Markov Oracle data structure is capable of locating repeated suffixes within a time series, thus making it an appropriate tool for the pattern discovery task. Evaluation of the proposed framework is performed on the JKU Patterns Development Dataset with state of the art performance.",
author = "Wang, {Cheng i.} and Jennifer Hsu and Shlomo Dubnov",
note = "Publisher Copyright: {\textcopyright} Cheng-i Wang, Jennifer Hsu and Shlomo Dubnov.; 16th International Society for Music Information Retrieval Conference, ISMIR 2015 ; Conference date: 26-10-2015 Through 30-10-2015",
year = "2015",
month = jan,
day = "1",
language = "English",
series = "Proceedings of the 16th International Society for Music Information Retrieval Conference, ISMIR 2015",
publisher = "International Society for Music Information Retrieval",
pages = "176--182",
editor = "Meinard Muller and Frans Wiering",
booktitle = "Proceedings of the 16th International Society for Music Information Retrieval Conference, ISMIR 2015",
}