Automatic feature weighting in automatic transcription of specified part in polyphonic music

Katsutoshi Itoyama*, Tetsuro Kitahara, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno

*この研究の対応する著者

研究成果: Conference contribution

抄録

We studied the problem of automatic music transcription (AMT) for polyphonic music. AMT is an important task for music information retrieval because AMT results enable retrieving musical pieces, high-level annotation, demixing, etc. We attempted to transcribe a part played by an instrument specified by users (specified part tracking). Only two timbre models are required in the specified part tracking to identify the specified musical instrument even when the number of instruments increases. This transcription is formulated into a time-series classification problem with multiple features. We furthermore attempted to automatically estimate weights of the features, because the importance of these features varies for each musical signal. We estimated quasi-optimal weights of the features using a genetic algorithm for each musical signal. We tested our AMT system using trio stereo musical signals. Accuracies with our feature weighting method were 69.8% on average, whereas those without feature weighting were 66.0%.

本文言語English
ホスト出版物のタイトルISMIR 2006 - 7th International Conference on Music Information Retrieval
ページ172-175
ページ数4
出版ステータスPublished - 2006 12 1
外部発表はい
イベント7th International Conference on Music Information Retrieval, ISMIR 2006 - Victoria, BC, Canada
継続期間: 2006 10 82006 10 12

出版物シリーズ

名前ISMIR 2006 - 7th International Conference on Music Information Retrieval

Conference

Conference7th International Conference on Music Information Retrieval, ISMIR 2006
国/地域Canada
CityVictoria, BC
Period06/10/806/10/12

ASJC Scopus subject areas

  • 音楽
  • 情報システム

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