Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/9823
Title: Certain explorations on speech enhancement techniques for automatic speaker recognition in noisy environment
Researcher: Sumithra M G
Guide(s): Thanushkodi K
Keywords: Automatic Speaker Recognizer
Time adaptive discrete wavelet thresholding
Speech enhancement technique
Upload Date: 11-Jul-2013
University: Anna University
Completed Date: 01/06/2011
Abstract: This Thesis presents a detailed study on speech enhancement algorithm to provide robustness to the Automatic Speaker Recognizer (ASR) in real-life noisy conditions. The main objective of this work is to attenuate the noise component of a noisy speech in order to enhance the quality of the speech processing devices and make them more robust under noisy conditions using wavelet based algorithms and to carry out a comprehensive evaluation and comparison of their performances on speaker recognition task. In this Thesis two new single channel wavelet based speech enhancement methods and a noise robust automatic speaker recognition are developed and reported.. Firstly, a technique using Time Adaptive Discrete Wavelet Thresholding (TADWT) based on Bionic Wavelet Transform (BWT) is proposed. In this approach discrete BWT is used for speech enhancement task, the adaptive nature of the BWT is captured by introducing a time varying linear factor at each scale over time and modified soft thresholding function is used for denoising. This method also provides a good auditory representation (sufficient frequency resolution), good perceptual quality of speech and low computational load. In this thesis, basic spectral subtraction (SS), iterative Wiener filtering (IWF), Ephraim Malah filtering (EMF), Bionic wavelet based thresholding (BWT) techniques and Perceptual wavelet packet transform (PWPT) have been used as baseline methods for speech enhancement tests. Performance evaluation of proposed methods is made based on segmental signal to noise ratio (SSNR), signal to noise ratio (SNR), Itakura-Saito (IS) distance measure and minimum mean square error (MMSE) for the objective speech quality evaluation. The average recognition accuracy of the system is improved while incorporating SE methods as preprocessor while comparing with the recognition rate obtained for degraded speech.
Pagination: xxviii, 177p.
URI: http://hdl.handle.net/10603/9823
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificates.pdf530.9 kBAdobe PDFView/Open
03_abstract.pdf19.8 kBAdobe PDFView/Open
04_acknowledgement.pdf14.21 kBAdobe PDFView/Open
05_contents.pdf68.16 kBAdobe PDFView/Open
06_chapter 1.pdf86.94 kBAdobe PDFView/Open
07_chapter 2.pdf83.02 kBAdobe PDFView/Open
08_chapter 3.pdf5.51 MBAdobe PDFView/Open
09_chapter 4.pdf7.83 MBAdobe PDFView/Open
10_chapter 5.pdf1.67 MBAdobe PDFView/Open
11_chapter 6.pdf28.15 kBAdobe PDFView/Open
12_references.pdf42.02 kBAdobe PDFView/Open
13_publications.pdf24.51 kBAdobe PDFView/Open
14_vitae.pdf13.18 kBAdobe PDFView/Open
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