Real-time Adaptive Concepts in Acoustics: Blind Signal Separation and Multichannel Echo Cancellation

159 Pages·2001·11.05 MB·English

by  Daniel W. E. Schobben Ph. D (auth.)

Real-time Adaptive Concepts in Acoustics
Real-time Adaptive
Concepts in Acoustics
Blind Signal Separation and
Multichannel Echo Cancellation
by
Daniel W.E. Schobben, Ph. D.
Philips Research Laboratories
SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.
A C.I.P. Catalogue record for this book is available from the Library of Congress.
ISBN 978-94-010-3857-7 ISBN 978-94-010-0812-9 (eBook)
DOI 10.1007/978-94-010-0812-9
Additional material to this book can be downloaded from http://extras.springer.com
Printed on acid-free paper
AII Rights Reserved
© 2001 Springer Science+Business Media Dordrecht
Originally published by Kluwer Academic Publishers in 2001
No part of the material protected by this copyright notice may be reproduced or
utilized in any form or by any means, electronic or mechanical,
including photocopying, recording or by any information storage and
retrieval system, without written permission from the copyright owner.
Contents
List of Figures ix
Preface
Xl
Part I Background and Introduction
1. INTRODUCTION 3
1.1 Motivation 3
1.2 Transparent Communication 4
1.3 Multichannel Signal Processing Concepts 6
1.4 Applications 8
1.5 Acoustics and Speech 9
1.6 Outline 11
1.7 Notation 13
2. ARRAY PROCESSING TECHNIQUES 15
2.1 Beamforming 15
2.2 Blind Deconvolution 20
2.3 Detection of Multiple Signals 21
2.4 Inverse Room Acoustics 22
2.5 Noise Cancellation 26
3. EFFICIENT FILTERING USING FFTS 29
3.1 FIR Filters 30
3.2 Block Based FIR Filters 32
3.3 Low Delay Frequency Domain FIR Filters 36
3.4 Conclusions 44
v
VI REAL-TIME ADAPTIVE CONCEPTS IN ACOUSTICS
Part II Acoustic Echo Cancellation
4. AN EFFICIENT ADAPTIVE FILTER IMPLEMENTATION 47
4.1 An Introduction to Adaptive Filters 47
4.2 Time Domain Adaptive Filters 49
4.3 Block Frequency Domain Adaptive Filter 51
4.4 Efficient Computation of the FFTs 54
4.5 Efficient Computation of the Update Part 56
4.6 Conclusions 57
5. EFFICIENT MULTICHANNEL RLS 59
5.1 Introduction 59
5.2 Filter Part 61
5.3 Multichannel RLS Update 62
5.4 Inverting the Covariation Matrix 65
5.5 Algorithm Overview 65
5.6 Computational Complexity 66
5.7 Experiments 67
Part III Blind Signal Separation
6. BLIND SIGNAL SEPARATION, AN OVERVIEW 75
6.1 Overview of Existing Methods 75
6.2 Indeterminacies 80
6.3 Frequency Domain Approaches 83
6.4 Discussion 86
7. A BLIND SIGNAL SEPARATION ALGORITHM 87
7.1 Introduction 87
7.2 Optimization Criterion 88
7.3 Frequency Domain Approach 91
7.4 Convolution Constraint 93
7.5 Time-Frequency Compliance 94
7.6 Normalization 96
7.7 Algorithm Overview 97
7.8 Implementation Details 98
7.9 Experiments 98
7.10 Computational Complexity 103
7.11 Conclusions 105
8. JOINT BLIND SIGNAL SEPARATION AND ECHO
CANCELLATION 107
8.1 Introduction 107
8.2 Derivation 109
Contents VB
8.3 Algorithm Overview 111
8.4 Experiments 112
8.5 Conclusions 113
9. BLIND SIGNAL SEPARATION ALGORITHM EVALUATION 115
9.1 Introduction 115
9.2 On the Difficulty of Blind Signal Separation 116
9.3 Recording Setups and Performance Measures 118
9.4 Data Sets 121
10. CONCLUSIONS 125
10.1 Main Contributions 125
10.2 Open Issues 126
10.3 Suggestions for Future Research 126
Appendices 129
A Efficient Beamforming 129
Al Introduction 129
A2 Linear Sensor Array Beamforming 129
A3 Interpolation Beamforming 131
A4 Polyphase Decomposition 131
AS Comparison of Computational Complexity 132
A6 Example of Computational Complexity 133
A7 Conclusions 133
B. Indeterminacies of Convolutive BSS based on Decorrelation 137
B.1 Convolutive BSS Indeterminacies 137
B.2 Rank of the Source Correlation Matrix 138
B.3 Real World Data Considerations 139
C. Computational Complexity of CoBliSS 141
C.1 Fast Fourier Transforms 141
C.2 Correlation Update 141
C.3 Weight Update 142
C.4 Filtering 142
C.5 Normalization 142
D. Efficient computation of windowed FFTs 145
D.1 Efficient Computation of Windowed (I)FFTs 145
D.2 Efficient Recursive FFTs of Overlapping Data 146
E. Contents of the Compact Disc 149
F. Glossary 151
References 153
Index 159
List of Figures
1.1 Teleconferencing setup 5
2.1 Side-lobe canceler 18
2.2 Beam-pattern of the main beam in a 5 element array 19
2.3 Beam-patterns of the 4 auxiliary beams in a 5 element array 20
2.4 Single-channel blind deconvolution 20
2.5 Blind deconvolution system 23
2.6 Conventional adaptive filter (top) and filtered-x equiv-
alence (bottom) 27
3.1 Relation between processing delay and processor load 32
3.2 Example illustrating the overlap-add method for one
data segment 33
3.3 Matlab routine explaining overlap-add 34
3.4 Example illustrating the overlap-add method for an in-
finite length signal 35
3.5 FIR filter implemented using the overlap-save method
in the frequency domain 37
3.6 Segmented FIR filter implemented using the overlap-
save method in the frequency domain 38
3.7 Matlab routine explaining overlap-save 39
3.8 Example illustrating the overlap-save method for one
data segment 39
3.9 Example illustrating the overlap-save method for an in-
finite length signal 40
3.10 Relative MIPS loss when segmenting a filter in 2P parts 41
3.11 Matlab program for greedy filter structure optimization 44
4.1 Signal estimation and system identification 48
4.2 Acoustic echo canceler 48
4.3 Block frequency domain adaptive filter 54
4.4 BFDAF update part 55
IX
x REAL-TIME ADAPTIVE CONCEPTS IN ACOUSTICS
4.5 Equivalent of BFDAF update part 57
5.1 Multichannel acoustic echo cancellation 61
5.2 Acoustic impulse responses from the sound sources to
the microphone 69
5.3 Microphone signal (top) and residual signal (bottom)
after stereo echo cancellation 69
5.4 Power of the microphone signal and the residual signal
after stereo echo cancellation 70
5.5 Microphone signal (top) and residual signal (bottom)
using two independent echo cancelers 70
5.6 Power of the microphone signal and the residual signal
using two independent echo cancelers 71
6.1 Cascaded mixing/unmixing of two sources 77
7.1 Cascaded mixingiunmixing system 88
7.2 The instantaneously mixed signals Xl and X2, the source
signals 81 and 82 and the recovered signals, 0.0-0.25 seconds 100
7.3 The instantaneously mixed signals Xl and X2, the source
signals 81 and 82 and the recovered signals, 0.9-1.0 seconds 101
7.4 Recording setup 102
7.5 Overall complexity of the CoBliSS algorithm as a func-
tion of the number of microphones J and the transform
size M, with is = 44.1kHz 104
7.6 Overall complexity ('*') and the complexity due to the
FFTs ('+') of the CoBliSS algorithm as a function of
the number of microphones J and the transform size
M, with is = 44.1kHz 105
8.1 Echo cancellation followed by blind signal separation 108
8.2 Mixing, unmixing and control system 109
A.1 Wave front incident to a linear array 130
A.2 Data interpolation 130
A.3 Interpolation beamformer 133
A.4 Beamformer equivalent 134
A.5 Interpolation filter (a), polyphase decomposed filter (b),
polyphase equivalent (c) and compacted polyphase equiv-
alent (d) 134
A.6 Beam-pointing patterns for all synchronous directions
for a 7 sensor array that is interpolated 20 times 135
Preface
This book deals with two topics; blind signal separation and multichannel acous
tic echo cancellation. Both have received a lot of interest in literature lately.
For multichannel echo cancellation this interest is mainly technology driven
by the mass introduction of multichannel audio communication systems and
speech recognition systems. Pioneering work on blind signal separation for
audio applications has been published less than a decade ago. The topic has
been booming ever since for the obvious reasons explained below.
Blind Signal Separation
The problem that is solved by blind signal separation is a magical one. This
is especially true for acoustical applications where microphones for example
pickup a mixture of various speech signals which are contaminated by room
acoustics. The goal is to retrieve the independent speech signals without having
knowledge of either (properties ot) the speech signals or the acoustical transfer
functions. The numerous applications that can be based on this technology
include voice control and teleconferencing.
In 1995 the paper by Bell and Sejnowski, 1995a was published which gave
both a theoretical background and reported promising results when working on
real-world audio signals. This is one of the early publications that motivated
many researchers to join the quest for the holy grail that is called blind signal
separation.
Echo Cancellation
Echo cancellation is a well known technique that was developed about three
decades ago. Its application can be found in any product that has both a mi
crophone and a loudspeaker, the purpose of the echo canceler being to cancel
the contribution of the loudspeaker signal to the microphone signal. It has been
widely used in many consumer products over the last decade now that this tech-
Xl
xii REAL-TIME ADAPTIVE CONCEPTS IN ACOUSTICS
nology has become economic to implement. Just when most aspects of echo
cancellation have been studied intensively a new problem arises with the intro
duction of multichannel sound systems; that of multichannel echo cancellation.
DANIEL SCHOBBEN