DocumentCode
2695316
Title
Automatic chord recognition for music classification and retrieval
Author
Cheng, Heng-Tze ; Yang, Yi-Hsuan ; Lin, Yu-Ching ; Liao, I-Bin ; Chen, Homer H.
Author_Institution
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei
fYear
2008
fDate
June 23 2008-April 26 2008
Firstpage
1505
Lastpage
1508
Abstract
As one of the most important mid-level features of music, chord contains rich information of harmonic structure that is useful for music information retrieval. In this paper, we present a chord recognition system based on the N-gram model. The system is time-efficient, and its accuracy is comparable to existing systems. We further propose a new method to construct chord features for music emotion classification and evaluate its performance on commercial song recordings. Experimental results demonstrate the advantage of using chord features for music classification and retrieval.
Keywords
audio signal processing; emotion recognition; information retrieval; music; pattern classification; signal classification; N-gram model; automatic chord recognition; commercial song recordings; music classification; music emotion classification; music information retrieval; Hidden Markov models; Histograms; Information analysis; Laboratories; Mel frequency cepstral coefficient; Multimedia systems; Multiple signal classification; Music information retrieval; Statistics; Telecommunications; Chord; N-gram; music classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo, 2008 IEEE International Conference on
Conference_Location
Hannover
Print_ISBN
978-1-4244-2570-9
Electronic_ISBN
978-1-4244-2571-6
Type
conf
DOI
10.1109/ICME.2008.4607732
Filename
4607732
Link To Document