Volume 8 Number 4 (Apr. 2013)
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JSW 2013 Vol.8(4): 916-923 ISSN: 1796-217X
doi: 10.4304/jsw.8.4.916-923

Keynote-Dependent HMM Based Musical Chord Recognition Method

Da-chuan Wei
Science and Technology Industry Division, Jilin Architectural and Civil Engineering Institute, Changchun, China

Abstract—Chord sequences and chord boundary is the midlevel performance of the music signal compactness and robustness. Automatic chord recognition is very attractive to researchers in the field of music information retrieval. To improve accuracy of musical chord recognition algorithm, in this study, the importance of keynote was fully considered. According to the music theory, 24 keynotes were defined. For each keynote, a Hidden Markov model was established, which is called keynote-dependent HMM. And then, a recognition algorithm of music chord based on keynotedependent HMM was proposed. In this algorithm, use MIDI music corpus to train the keynote-dependent HMM, and to improve the recognition rate and facilitate the calculation, a 6-dimensional vector of tonal centroid is used as the feature vector. The experimental results showed that the proposed keynote-dependent HMM had better recognition effect than that of keynote-independent model.

Index Terms—Musical chord recognition, keynotedependent HMM, MIDI, tonal centroid.


Cite: Da-chuan Wei, "Keynote-Dependent HMM Based Musical Chord Recognition Method," Journal of Software vol. 8, no. 4, pp. 916-923, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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