Comparison OF Wavelet Based Feature Extraction Methods for Speech/Music Discrimination

Yıl 2011, Cilt: 11 Sayı: 1, 1355 - 1362, 28.03.2012

Timur Düzenli Nalan Özkurt

Öz

The speech/music discrimination systems have gaining importance in several intelligent audio retrieval algorithms due to the increasing size of the multimedia sources in our daily lives. This study aims to propose a speech/music discrimination system which utilizes the advantages of the wavelet transform. Also, the performance of the discrete wavelet transform and the dual- tree wavelet transform has been compared with the conventional time, frequency and cepstral domain features used in speech/music discrimination. The speech and music samples collected from common databases, CD recording and internet radios have been classified with artificial neural networks with different feature sets. The principal component analysis has been applied to eliminate the correlated features before classification stage. Considering the number of vanishing moments and orthogonality, the best performance has been obtained with Daubechies8 wavelet among the other members of the Daubechies family. According to the results, the proposed feature set outperforms the traditional ones.

Keywords: Speech/music discrimination, Discrete wavelet transform, Dual-tree wavelet transform, Daubechies mother wavelet.

Anahtar Kelimeler

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Kaynakça

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• Nalan Özkurt received her B.S., M.S. and Ph.D. degree in Electrical
• Engineering from the Dokuz Eylul University, in 1994, 1998 and 2004, respectively. She is currently an assistant professor in the Department of Electrical Engineering at
• Yaşar University. Her research interests are wavelets, nonlinear static and dynamical systems, chaos. She is a member of Association of Electrical and Electronic Engineers of Turkey.
• Timur Düzenli received his B.S. in 2007 and his M.S. in 2010, both
• Electronics Engineering, from Dokuz Eylul University. He is currently a Ph.D. student at the same department. Her research interests are wavelets, time- frequency analysis, and digital communication systems. and