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URN etd-0814106-141229 Statistics This thesis had been viewed 2873 times. Download 1926 times. Author Ren-Jie Huang Author's Email Address No Public. Department Communication Engineering Year 2005 Semester 2 Degree Master Type of Document Master's Thesis Language English Page Count 77 Title A STUDY ON SPEECH SIGNAL PROCESSING USING WAVELET TRANSFORMS Keyword speech wavelet wavelet speech Abstract The wavelet transform is one of the most exciting developments of the last decade. Wavelet theory provides a unified framework for a number of techniques which had been developed independently for various signal processing applications. Due to the wavelet representation has characteristics of the efficient time-frequency localization and the multi-resolution analysis; the wavelet transforms are suitable for processing the non-stationary signals such as speech. Based on the Wavelet framework, this thesis develops three wavelet-based speech signal processing algorithms including voice active detection (VAD), consonant/vowel (C/V) segmentation, and pitch detection.
The first part is the wavelet-based voice active detection algorithm on a frame by frame basis. Experimental results show that the proposed VAD algorithm is capable of outperforming to the VAD of Enhanced Full Rate GSM-based system and can operate reliably in noisy environments (SNR=0dB). Then, this thesis makes use of wavelet transform and energy profile to indicate the C/V segmentation point and is no need to set any predetermined threshold. It is shown that the C/V the segmentation point can be accurately pointed out with a low computation complexity. Final, In the light of the properties of wavelet transform and circular average magnitude difference function, a new pitch detection algorithm is proposed. The simulation results show that new method can detect the pitch period accurately when other methods can‘t when SNR is in 0dB.
Advisor Committee Ching-Kuen Lee - advisor
Files Date of Defense 2006-07-28 Date of Submission 2006-08-14