Polyphonic music classification on symbolic data using dissimilarity functions

Yoko Anan, kohei hatano, Hideo Bannai, Masayuki Takeda, Ken Satoh

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

5 引用 (Scopus)

抜粋

This paper addresses the polyphonic music classification problem on symbolic data. A new method is proposed which converts music pieces into binary chroma vector sequences and then classifies them by applying the dissimilarity-based classification method TWIST proposed in our previous work. One advantage of using TWIST is that it works with any dissimilarity measure. Computational experiments show that the proposed method drastically outperforms SVM and k-NN, the state-of-the-art classification methods.

元の言語英語
ホスト出版物のタイトルProceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012
ページ229-234
ページ数6
出版物ステータス出版済み - 2012
イベント13th International Society for Music Information Retrieval Conference, ISMIR 2012 - Porto, ポルトガル
継続期間: 10 8 201210 12 2012

その他

その他13th International Society for Music Information Retrieval Conference, ISMIR 2012
ポルトガル
Porto
期間10/8/1210/12/12

All Science Journal Classification (ASJC) codes

  • Music
  • Information Systems

フィンガープリント Polyphonic music classification on symbolic data using dissimilarity functions' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Anan, Y., hatano, K., Bannai, H., Takeda, M., & Satoh, K. (2012). Polyphonic music classification on symbolic data using dissimilarity functions. : Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012 (pp. 229-234)