DocumentCode :
605817
Title :
Audio retrieval using timbral feature
Author :
Kumar, R.C.P. ; Chandy, D.A.
Author_Institution :
Dept. of Electron. & Commun. Eng., Karunya Univ., Coimbatore, India
fYear :
2013
fDate :
25-26 March 2013
Firstpage :
222
Lastpage :
226
Abstract :
The increase in availability of music information demands for the development of tools for audio retrieval. Audio information retrieval implicates the retrieval of similar audio files based on the feature. Feature extraction is one of the important tasks where the entire retrieval system relies on. In this work, audio information retrieval has been performed on GTZAN datasets using Delta Mel-Frequency Cepstral Coefficients (MFCC) feature which is a kind of timbre feature. The results obtained for the various stages of feature extraction and retrieval performance plot has been presented. The average precision and recall values obtained are 78.67% and 58.02%, respectively.
Keywords :
cepstral analysis; content-based retrieval; feature extraction; music; GTZAN datasets; MFCC feature; audio information retrieval; audio retrieval tools; delta melfrequency cepstral coefficient feature; feature based audio file retrieval; feature extraction; music information demand availability; timbral feature; Databases; Feature extraction; Filter banks; Mel frequency cepstral coefficient; Multiple signal classification; Music; Vectors; Audio Retrieval; Feature Extraction; MFCC; Mel filter bank; Timbral Feature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Trends in Computing, Communication and Nanotechnology (ICE-CCN), 2013 International Conference on
Conference_Location :
Tirunelveli
Print_ISBN :
978-1-4673-5037-2
Type :
conf
DOI :
10.1109/ICE-CCN.2013.6528497
Filename :
6528497
Link To Document :
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