Benesty / Chen / Huang Noise Reduction in Speech Processing

2009
ISBN: 978-3-642-00296-0
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 2, 230 Seiten

Reihe: Springer Topics in Signal Processing

Noise is everywhere and in most applications that are related to audio and speech, such as human-machine interfaces, hands-free communications, voice over IP (VoIP), hearing aids, teleconferencing/telepresence/telecollaboration systems, and so many others, the signal of interest (usually speech) that is picked up by a microphone is generally contaminated by noise. As a result, the microphone signal has to be cleaned up with digital signal processing tools before it is stored, analyzed, transmitted, or played out. This cleaning process is often called noise reduction and this topic has attracted a considerable amount of research and engineering attention for several decades. One of the objectives of this book is to present in a common framework an overview of the state of the art of noise reduction algorithms in the single-channel (one microphone) case. The focus is on the most useful approaches, i.e., filtering techniques (in different domains) and spectral enhancement methods. The other objective of Noise Reduction in Speech Processing is to derive all these well-known techniques in a rigorous way and prove many fundamental and intuitive results often taken for granted. This book is especially written for graduate students and research engineers who work on noise reduction for speech and audio applications and want to understand the subtle mechanisms behind each approach. Many new and interesting concepts are presented in this text that we hope the readers will find useful and inspiring.

Autoren/Hrsg.

Benesty, Jacob

Chen, Jingdong

Huang, Yiteng

Cohen, Israel

Inhaltsverzeichnis

1;Preface;6
2;Contents;8
3;1 Introduction;12
3.1;1.1 Noise Reduction in Speech Processing;12
3.2;1.2 The Paradigm for Noise Reduction;17
3.3;1.3 A Brief History of Noise Reduction Research;18
3.4;1.4 Organization of the Book;21
3.5;1.5 Some Notes to the Reader;24
4;2 Problem Formulation;25
4.1;2.1 In the Time Domain;25
4.2;2.2 In the Frequency Domain;26
4.3;2.3 In the Karhunen-Lo`eve Expansion (KLE) Domain;28
4.4;2.4 Summary;30
5;3 Performance Measures;31
5.1;3.1 Signal-to-Noise Ratio;31
5.2;3.2 Noise-Reduction Factor;34
5.3;3.3 Speech-Distortion Index;35
5.4;3.4 Speech-Reduction Factor;37
5.5;3.5 Discussion;38
6;4 Mean-Squared Error Criterion;40
6.1;4.1 In the Time Domain;40
6.2;4.2 In the Frequency Domain;41
6.3;4.3 In the KLE Domain;43
6.4;4.4 Summary;45
7;5 Pearson Correlation Coefficient;46
7.1;5.1 Correlation Coefficient Between Two Random Variables;46
7.2;5.2 Correlation Coefficient Between Two Random Vectors;47
7.3;5.3 Frequency-Domain Versions;48
7.4;5.4 KLE-Domain Versions;48
7.5;5.5 Summary;49
8;6 Fundamental Properties;50
8.1;6.1 In the Time Domain;50
8.2;6.2 In the Frequency Domain;55
8.3;6.3 In the KLE Domain;59
8.4;6.4 Summary;66
9;7 Optimal Filters in the Time Domain;67
9.1;7.1 Wiener Filter;67
9.2;7.2 Tradeoff Filters;72
9.3;7.3 Subspace Approach;75
9.4;7.4 Experiments;76
9.5;7.5 Summary;83
10;8 Optimal Filters in the Frequency Domain;85
10.1;8.1 Wiener Filter;85
10.2;8.2 Parametric Wiener Filter;89
10.3;8.3 Tradeoff Filter;90
10.4;8.4 Experiments;94
10.5;8.5 Summary;102
11;9 Optimal Filters in the KLE Domain;103
11.1;9.1 Class I;103
11.2;9.2 Class II;113
11.3;9.3 Experiments;119
11.4;9.4 Summary;129
12;10 Optimal Filters in the Transform Domain;130
12.1;10.1 Generalization of the KLE;130
12.2;10.2 Performance Measures;134
12.3;10.3 MSE Criterion;138
12.4;10.4 PCC and Fundamental Properties;139
12.5;10.5 Examples of Filter Design;145
12.6;10.6 Experiments;153
12.7;10.7 Summary;159
13;11 Spectral Enhancement Methods;160
13.1;11.1 Problem Formulation;160
13.2;11.2 Performance Measures;162
13.3;11.3 MSE Criterion;166
13.4;11.4 Signal Model;168
13.5;11.5 Signal Estimation;169
13.6;11.6 Spectral Variance Model;173
13.7;11.7 Spectral Variance Estimation;177
13.8;11.8 Summary of Spectral Enhancement Algorithm;181
13.9;11.9 Experimental Results;183
13.10;11.10 Summary;188
14;12 A Practical Example: Multichannel Noise Reduction for Voice Communication in Spacesuits;190
14.1;12.1 Problem Description;190
14.2;12.2 Problem Analysis;193
14.3;12.3 Suggested Algorithms;199
14.4;12.4 Algorithm Validation;210
14.5;12.5 Summary;224
14.6;Acknowledgments;225
15;References;226
16;Index;234