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

Katsutoshi Itoyama, Tetsuya Ogata, Hiroshi G. Okuno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages58-67
Number of pages10
Volume7345 LNAI
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012 - Dalian
Duration: 2012 Jun 92012 Jun 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7345 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012
CityDalian
Period12/6/912/6/12

Fingerprint

Viterbi algorithm
Chord or secant line
Acoustics
Modulation
Acoustic waves
Maximum a Posteriori Estimation
Viterbi Algorithm
Posterior Probability
Sound
Music
Experimental Results

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Itoyama, K., Ogata, T., & Okuno, H. G. (2012). Automatic chord recognition based on probabilistic integration of acoustic features, bass sounds, and chord transition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7345 LNAI, pp. 58-67). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7345 LNAI). https://doi.org/10.1007/978-3-642-31087-4_7

Automatic chord recognition based on probabilistic integration of acoustic features, bass sounds, and chord transition. / Itoyama, Katsutoshi; Ogata, Tetsuya; Okuno, Hiroshi G.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7345 LNAI 2012. p. 58-67 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7345 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Itoyama, K, Ogata, T & Okuno, HG 2012, Automatic chord recognition based on probabilistic integration of acoustic features, bass sounds, and chord transition. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7345 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7345 LNAI, pp. 58-67, 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Dalian, 12/6/9. https://doi.org/10.1007/978-3-642-31087-4_7
Itoyama K, Ogata T, Okuno HG. Automatic chord recognition based on probabilistic integration of acoustic features, bass sounds, and chord transition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7345 LNAI. 2012. p. 58-67. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-31087-4_7
Itoyama, Katsutoshi ; Ogata, Tetsuya ; Okuno, Hiroshi G. / Automatic chord recognition based on probabilistic integration of acoustic features, bass sounds, and chord transition. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7345 LNAI 2012. pp. 58-67 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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