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Application of Wavelets in Speech Processing

Part of the SpringerBriefs in Electrical and Computer Engineering Book Series

DOI: 10.1007/978-3-319-02732-6

ISBN: 978-3-319-02731-9

Publisher: Springer International Publishing - Springer Journals

Dec 10, 2013

1 - 10 of 13 Chapters

Available

Introduction

Farouk, Mohamed Hesham

Pages: 1 –3

[As the wavelets gain wide applications in different fields, especially within the signal processing realm, this chapter will provide a survey on widespread employing of wavelets analysis in different applications of speech processing. Many speech processing algorithms and techniques still lack...
Available

Speech Production and Perception

Farouk, Mohamed Hesham

Pages: 5 –10

[The main objective of research in speech processing is directed toward finding techniques for extracting features, which robustly model a speech signal. Some of these features can be characterized by relatively simple models, while others may require more realistic models in both cases of speech...
Available

Wavelets, Wavelet Filters, and Wavelet Transforms

Farouk, Mohamed Hesham

Pages: 11 –19

[Spectral characteristics of speech are known to be particularly useful in describing a speech signal such that it can be efficiently reconstructed after coding or identified for recognition. Wavelets are considered one of such efficient methods for representing the spectrum of speech signals....
Available

Speech Enhancement and Noise Suppression

Farouk, Mohamed Hesham

Pages: 21 –24

[Wavelet analysis has been widely used for noise suppression in signals. The multiresolution properties of wavelet analysis reflect the frequency resolution of the human ear. The wavelet transform (WT) can be adapted to distinguish noise in speech through its properties in the time and frequency...
Available

Speech Quality Assessment

Farouk, Mohamed Hesham

Pages: 25 –26

[The wavelet packet analysis can be used to improve a perceptual-based objective speech quality measure. In this measure, the critical bands of auditory system can be approximated by a predefined wavelet packet (PWP) tree structure.]
Available

Speech Recognition

Farouk, Mohamed Hesham

Pages: 27 –29

[Wavelet analysis can be used to improve the speech recognition performance through two approaches. In the first approach, it can be used as the back-end to remove noise and consequently the recognition process may perform better. In the second approach, wavelet-based features can be added to...
Available

Emotion Recognition from Speech

Farouk, Mohamed Hesham

Pages: 31 –32

[Like speech recognition, emotion recognition can benefit from the merits of wavelet analysis in feature extraction or mapping functions.]
Available

Speaker Recognition

Farouk, Mohamed Hesham

Pages: 33 –35

[MFCC features are widely used in speaker recognition. However, MFCC is not suitable for identifying a speaker since they should be located in high frequency regions, while the Mel scale gets coarser in the higher frequency bands. The speaker individual information, which is nonuniformly...
Available

Spectral Analysis of Speech Signal and Pitch Estimation

Farouk, Mohamed Hesham

Pages: 37 –39

[Wavelet transform (WT) provides a way to explore the characteristics of nonstationary speech signals. Both time and frequency analysis can be conducted by WT. The tree structure of WP analysis can be customized to the critical bands of human hearing giving better spectral estimation for speech...
Available

Speech Coding, Synthesis, and Compression

Farouk, Mohamed Hesham

Pages: 41 –42

[WT-based coding allows for the control of frequency resolution to closely match the response of the human auditory system. The inherent shaping of the wavelet synthesis filter and a controlled bit allocation to the wavelet coefficients help to minimize the perceptually significant noise due to...

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