Automatic chord recognition based on probabilistic integration of acoustic features, bass sounds, and chord transition

Katsutoshi Itoyama, Tetsuya Ogata, Hiroshi G. Okuno

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

We have developed a method that identifies musical chords in polyphonic musical signals. As musical chords mainly represent the harmony of music and are related to other musical elements such as melody and rhythm, we should be able to recognize chords more effectively if this interrelationship is taken into consideration. We use bass pitches as clues for improving chord recognition. The proposed chord recognition system is constructed based on Viterbi-algorithm- based maximum a posteriori estimation that uses a posterior probability based on chord features, chord transition patterns, and bass pitch distributions. Experimental results with 150 Beatles songs that has keys and no modulation showed that the recognition rate was 73.7% on average.

本文言語English
ホスト出版物のタイトルAdvanced Research in Applied Artificial Intelligence - 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Proceedings
ページ58-67
ページ数10
DOI
出版ステータスPublished - 2012
外部発表はい
イベント25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012 - Dalian, China
継続期間: 2012 6 92012 6 12

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7345 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012
CountryChina
CityDalian
Period12/6/912/6/12

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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