A wavelet based approach for speaker identification from degraded speech.

A.  Shafik; S. M.  Elhalafawy; S. M.  Diab; B.  Sallam; M. F. E.  Abdel-Samie

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A wavelet based approach for speaker identification from degraded speech.

Author(s)

A. Shafik Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt

S. M. Elhalafawy Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt

S. M. Diab Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt

B. Sallam Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt

M. F. E. Abdel-Samie Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt

Abstract

This paper presents a robust speaker identification method from degraded speech signals. This method is based on the Mel-frequency cepstral coefficients (MFCCs) for feature extraction from the degraded speech signals and the wavelet transform of these signals. It is known that the MFCCs based speaker identification method is not robust enough in the presence of noise and telephone degradations. So, the feature extraction from the wavelet transform of the degraded signals adds more speech features from the approximation and detail components of these signals which assist in achieving higher identification rates. Neural Networks are used in the proposed method for feature matching. The Comparison study between the proposed method and the traditional MFCCs based feature extraction method from noisy speech signals and telephone degraded speech signals with additive white Gaussian noise (AWGN) and colored noise shows that the proposed method improves the recognition rates computed at different degradation cases.

Publication Details

Page(s) 52-58

DOI DOI not available

Published Journal: International Journal of Communication Networks and Information Security, Volume: 1, Issue: 3, Year: 2009

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