DocumentCode :
2081481
Title :
Recognition algorithm of musical chord based on keynote-dependent HMM
Author :
Wei, Da-chuan
Author_Institution :
Sci. & Technol. Ind. Div., Jilin Archit. & Civil Eng. Inst., Changchun, China
fYear :
2011
fDate :
16-18 Dec. 2011
Firstpage :
2504
Lastpage :
2507
Abstract :
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 keynote-dependent 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.
Keywords :
audio signal processing; hidden Markov models; 6D vector; MIDI music corpus; feature vector; hidden Markov models; keynote dependent HMM; keynote independent model; music theory; musical chord recognition algorithm; recognition rate; tonal centroid; Feature extraction; Hidden Markov models; Multiple signal classification; Music; Signal processing algorithms; Training; Vectors; MIDI; keynote-dependent HMM; musical chord recognition; tonal centroid;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4577-1700-0
Type :
conf
DOI :
10.1109/TMEE.2011.6199730
Filename :
6199730
Link To Document :
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