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 :
بازگشت