A STUDY ON SPEECH SIGNAL PROCESSING USING WAVELET TRANSFORMS

• Main Authors: Ren-Jie Huang, 黃仁杰
• Other Authors: Ching-Kuen Lee
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/38015308061785996576

碩士 === 大同大學 === 通訊工程研究所 === 94 === 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.