DocumentCode :
3348395
Title :
Content based audio classification and retrieval using joint time-frequency analysis
Author :
Esmaili, S. ; Krishnan, Sridhar ; Raahemifar, K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, Ont., Canada
Volume :
5
fYear :
2004
fDate :
17-21 May 2004
Abstract :
We present an audio classification and retrieval technique that exploits the non-stationary behavior of music signals and extracts features that characterize their spectral change over time. Audio classification provides a solution to incorrect and inefficient manual labelling of audio files on computers by allowing users to extract music files based on content similarity rather than labels. In our technique, classification is performed using time-frequency analysis and sounds are classified into 6 music groups consisting of rock, classical, folk, jazz and pop. For each 5 second music segment, the features that are extracted include entropy, centroid, centroid ratio, bandwidth, silence ratio, energy ratio, and location of minimum and maximum energy. Using a database of 143 signals, a set of 10 time-frequency features are extracted and an accuracy of classification of around 93% using regular linear discriminant analysis or 92.3% using the leave-one-out method is achieved.
Keywords :
audio signal processing; content-based retrieval; entropy; feature extraction; music; pattern classification; signal classification; time-frequency analysis; audio classification; audio file labelling; audio retrieval; bandwidth; centroid ratio; content based retrieval; energy ratio; entropy; feature extraction; leave-one-out method; linear discriminant analysis; maximum energy location; minimum energy location; music groups; music signals; silence ratio; time-frequency analysis; Bandwidth; Content based retrieval; Entropy; Feature extraction; Labeling; Linear discriminant analysis; Multiple signal classification; Music information retrieval; Spatial databases; Time frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-8484-9
Type :
conf
DOI :
10.1109/ICASSP.2004.1327198
Filename :
1327198
Link To Document :
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