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