Application of Wavelets in Speech Processing

96 Pages·2018·2.71 MB·English

by  Mohamed Hesham Farouk (auth.)

SPRINGER BRIEFS IN ELECTRICAL AND
COMPUTER ENGINEERING  SPEECH TECHNOLOGY
Mohamed Hesham Farouk
Application
of Wavelets
in Speech
Processing

Second Edition
123
SpringerBriefs in Electrical and Computer
Engineering
Speech Technology
Series editor
Amy Neustein, Fort Lee, NJ, USA
Editor’s Note
The authors of this series have been hand-selected. They comprise some of the most
outstanding scientists—drawn from academia and private industry—whose research
is marked by its novelty, applicability, and practicality in providing broad based
speech solutions. The SpringerBriefs in Speech Technology series provides the
latest findings in speech technology gleaned from comprehensive literature reviews
and empirical investigations that are performed in both laboratory and real life
settings. Some of the topics covered in this series include the presentation of real
life commercial deployment of spoken dialog systems, contemporary methods of
speech parameterization, developments in information security for automated
speech, forensic speaker recognition, use of sophisticated speech analytics in call
centers, and an exploration of new methods of soft computing for improving human-
computer interaction. Those in academia, the private sector, the self service industry,
law enforcement, and government intelligence, are among the principal audience
for this series, which is designed to serve as an important and essential reference
guide for speech developers, system designers, speech engineers, linguists and
others. In particular, a major audience of readers will consist of researchers and
technical experts in the automated call center industry where speech processing is a
key component to the functioning of customer care contact centers.
Amy Neustein, Ph.D., serves as Editor-in-Chief of the International Journal of
Speech Technology (Springer). She edited the recently published book “Advances in
Speech Recognition: Mobile Environments, Call Centers and Clinics” (Springer
2010), and serves as quest columnist on speech processing for Womensenews.
Dr. Neustein is Founder and CEO of Linguistic Technology Systems, a NJ-based
think tank for intelligent design of advanced natural language based emotion-
detection software to improve human response in monitoring recorded conversations
of terror suspects and helpline calls. Dr. Neustein’s work appears in the peer review
literature and in industry and mass media publications. Her academic books, which
cover a range of political, social and legal topics, have been cited in the Chronicles
of Higher Education, and have won her a pro Humanitate Literary Award. She
serves on the visiting faculty of the National Judicial College and as a plenary
speaker at conferences in artificial intelligence and computing. Dr. Neustein is a
member of MIR (machine intelligence research) Labs, which does advanced work in
computer technology to assist underdeveloped countries in improving their ability
to cope with famine, disease/illness, and political and social affliction. She is a
founding member of the New York City Speech Processing Consortium, a newly
formed group of NY-based companies, publishing houses, and researchers dedicated
to advancing speech technology research and development.
More information about this series at http://www.springer.com/series/10043
Mohamed Hesham Farouk
Application of Wavelets
in Speech Processing
Second Edition
Mohamed Hesham Farouk
Department of Engineering, Math and Physics
Cairo University, Faculty of Engineering
Giza, Egypt
ISSN 2191-8112 ISSN 2191-8120 (electronic)
SpringerBriefs in Electrical and Computer Engineering
ISSN 2191-737X ISSN 2191-7388 (electronic)
SpringerBriefs in Speech Technology
ISBN 978-3-319-69001-8 ISBN 978-3-319-69002-5 (eBook)
https://doi.org/10.1007/978-3-319-69002-5
Library of Congress Control Number: 2017958884
© The Author(s) 2014, 2018
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To the soul of my mother
Preface
This is a new edition of the title Application of Wavelets in Speech Processing
published in 2014. All chapters of previous edition have been revised in this work.
The sequence of topics is rearranged taking into consideration the dependency
among topics such that the information flow through book chapters becomes
smoother. More subjects have been added in the current edition reflecting advances
in using wavelet analysis for speech processing and its widespread applications.
Organization of the Book
The chapters of this book have been structured such that each one is self-contained
and can be read separately. Each chapter is concerned with a specific application of
wavelets in speech technology. Every module in a chapter surveys the literature in
this topic such that the use of wavelets in the work is explained and experimental
results of proposed method are then discussed. Chapter 1 introduces the topic of
speech processing, while Chap. 2 discusses processes for speech production and
different approaches in modeling of a speech signal. Chapter 3, thereafter, explains
how wavelets can describe and model many features of a speech signal. Applications
of wavelet transform (WT) in speech processing are the subjects of subsequent
chapters. Collectively, the power of WT in estimating spectral characteristics of
speech is explained in Chap. 4 showing how elements of such spectrum can be
derived like pitch and formants. Chapter 5 confers the problem of speech activity
detection and signal separation based on features extracted from WT. Enhancement
and noise cancellation is revised in Chap. 6 showing how WT improves the process.
The problem of speech recognition is discussed in Chap. 7 in view of the provided
powerful features obtained by a wavelet analysis. Another recognition problem is
considered in Chap. 8 discussing the identification of a speaker from his voice.
Additionally, a similar topic on emotion recognition through wavelet features in an
utterance is elucidated in Chap. 9. Another key application of speech is discussed in
Chap. 10 showing how speech signal can be decoded and synthesized using a
vii
viii Preface
low-dimensional features domain. Also, the assessment of speech quality based on
WT coefficients is surveyed and explained in Chap. 11. Chapter 12 has been added
in this edition to examine how nonlinear features can be extracted from a speech
signal by WT. Furthermore, Chap. 13 hits critical application of speech signal in
security and steganography. More arguments on clinical diagnosis are discussed in
Chap. 14 through wavelet features of speech recorded from a patient.
Acknowledgment
The author would like to thank the editorial board of the SpringerBriefs series for
letting him prepare this monograph and for their continuous cooperation during the
preparation of the work. Thanks should also go to my colleagues at the Engineering
Physics Department, Bahira Elsebelgy, Ph.D., and M. El-Gohary, M.Sc., for helping
in proofreading.
Giza, Egypt Mohamed Hesham Farouk
Contents
1 Introduction ............................................................................................ 1
1.1 History and Definition of Speech Processing ................................. 1
1.2 Applications of Speech Processing ................................................. 2
1.3 Recent Progress in Speech Processing ............................................ 2
1.4 Wavelet Analysis as an Efficient Tool for Speech Processing ........ 3
References ................................................................................................ 4
2 Speech Production and Perception ....................................................... 5
2.1 Speech Production Process ............................................................. 5
2.2 Classification of Speech Sounds ..................................................... 6
2.3 Speech Production Modeling .......................................................... 7
2.4 Speech Perception Modeling .......................................................... 8
2.5 Intelligibility and Speech Quality Measures ................................... 9
References ................................................................................................ 10
3 Wavelets, Wavelet Filters, and Wavelet Transforms ........................... 11
3.1 Short-Time Fourier Transform (STFT) ........................................... 11
3.2 Multiresolution Analysis and Wavelet Transform ........................... 12
3.3 Wavelets and Bank of Filters .......................................................... 14
3.4 Wavelet Families ............................................................................. 15
3.5 Wavelet Packets ............................................................................... 16
3.6 Undecimated Wavelet Transform .................................................... 18
3.7 The Continuous Wavelet Transform (CWT) ................................... 18
3.8 Wavelet Scalogram .......................................................................... 19
3.9 Empirical Wavelets ......................................................................... 19
References ................................................................................................ 20
4 Spectral Analysis of Speech Signal and Pitch Estimation .................. 23
4.1 Spectral Analysis ............................................................................. 23
4.2 Formant Tracking and Estimation ................................................... 24
4.3 Pitch Estimation .............................................................................. 25
References ................................................................................................ 27
ix
x Contents
5 Speech Detection and Separation ......................................................... 29
5.1 Voice Activity Detection ................................................................. 29
5.2 Segmentation of Speech Signal ...................................................... 30
5.3 Source Separation of Speech .......................................................... 31
References ................................................................................................ 33
6 Speech Enhancement and Noise Suppression ..................................... 35
6.1 Thresholding Schemes .................................................................... 36
6.2 Thresholding on Wavelet Packet Coefficients ................................ 37
6.3 Enhancement on Multitaper Spectrum ............................................ 38
References ................................................................................................ 39
7 Speech Recognition ................................................................................ 41
7.1 Signal Enhancement and Noise
Cancellation for Robust Recognition .............................................. 41
7.2 Wavelet-Based Features for Better Recognition ............................. 42
7.3 Hybrid Approach ............................................................................. 43
7.4 Wavelet as an Activation Function for Neural
Networks in ASR ............................................................................ 44
References ................................................................................................ 45
8 Speaker Identification ............................................................................ 47
8.1 Wavelet-Based Features for Speaker Identification ........................ 48
8.2 Hybrid Feature Sets for Speaker Identification ............................... 49
References ................................................................................................ 49
9 Emotion Recognition from Speech ....................................................... 51
9.1 Wavelet-Based Features for Emotion Recognition ......................... 51
9.2 Combined Feature Set for Better Emotion Recognition ................. 53
9.3 WNN for Emotion Recognition ...................................................... 54
References ................................................................................................ 54
10 Speech Coding, Synthesis, and Compression ...................................... 57
10.1 Speech Synthesis ........................................................................... 57
10.2 Speech Coding and Compression ................................................. 58
10.3 Real-Time Implementation of DWT-Based
Speech Compression ..................................................................... 58
References ............................................................................................... 59
11 Speech Quality Assessment ................................................................... 61
11.1 Wavelet-Packet Analysis ............................................................... 61
11.2 Discrete Wavelet Transform .......................................................... 63
References ............................................................................................... 64
12 Scalogram and Nonlinear Analysis of Speech ..................................... 65
12.1 Wavelet-Based Nonlinear Features ............................................... 65
12.2 Wavelet Scalogram Analysis ......................................................... 66
12.3 Nonlinear and Chaotic Components in Speech Signal ................. 67
References ............................................................................................... 69