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Microphone Arrays_ Signal Processing Techniques and Applications.pdf
1 Constant Directivity Beamforming
1.1 Introduction
1.2 Problem Formulation
1.3 Theoretical Solution
1.3.1 Continuous sensor
1.3.2 Beam-shaping function
1.4 Practical Implementation
1.4.1 Dimension-reducing parameterization
1.4.2 Reference beam-shaping filter
1.4.3 Sensor placelllent
1.4.4 SUllllllary of illlplelllentation
1.5 Examples
1.6 Conclusions
2 Superdirective Microphone Arrays
2.1 Introduction
2.2 Evaluation of Beamformers
2.2.1 Array-Gain
2.2.2 Beampattern
2.2.3 Directivity
2.2.4 Front-to-Back Ratio
2.2.5 White Noise Gain
2.3 Design of Superdirective Beamformers
2.3.1 Delay-and-Sum Beamformer
2.3.2 Design for spherical isotropic noise
2.3.3 Design for Cylindrical Isotropic Noise
2.3.4 Design for an Optimal Front-to-Back Ratio
2.3.5 Design for Measured Noise Fields
2.4 Extensions and Details
2.4.1 Alternative Form
2.4.2 Comparison with Gradient Microphones
2.5 Conclusion
3 Post-Filtering Techniques
3.1 Introduction
3.2 Multi-channel Wiener Filtering in Subbands
3.2.1 Derivation of the Optimum Solution
3.2.2 Factorization of the Wiener Solution
3.2.3 Interpretation
3.3 Algorithms for Post-Filter Estimation
3.3.1 Analysis of Post-Filter Algorithms
3.3.2 Properties of Post-Filter Algorithms
3.3.3 A New Post-Filter Algorithm
3.4 Performance Evaluation
3.4.1 Simulation System
3.4.2 Objective Measures
3.4.3 Simulation Results
3.5 Conclusion
4 Spatial Coherence Functions for Differential Microphones in Isotropic NoiseFields
4.1 Introduction
4.2 Adaptive Noise Cancellation
4.3 Spherically Isotropic Coherence
4.4 Cylindrically Isotropic Fields
4.5 Conclusions
5 Robust Adaptive Beamforming
5.1 Introduction
5.2 Adaptive Beamformers
5.3 Robustness Problem in the GJBF
5.4 Robust Adaptive Microphone Arrays - Solutionsto Steering-Vector Errors
5.4.1 LAF-LAF Structure
5.4.2 CCAF-LAF Structure
5.4.3 CCAF-NCAF Structure
5.4.4 CCAF-NCAF Structure with an AMC
5.5 Software Evaluation of a Robust AdaptiveMicrophone Array
5.5.1 Simulated Anechoic Environment
5.5.2 Reverberant Environment
5.6 Hardware Evaluation of a Robust AdaptiveMicrophone Array
5.6.1 Implementation
5.6.2 Evaluation in a Real Environment
5.7 Conclusion
6 GSVD-Based Optimal Filtering forMulti-Microphone Speech Enhancement
6.1 Introduction
6.2 GSVD-Based Optimal Filtering Technique
6.2.1 Optimal Filter Theory
6.2.2 General Class of Estimators
6.2.3 Symmetry Properties for Time-Series Filtering
6.3 Performance of GSVD-Based Optimal Filtering
6.3.1 Simulation Environment
6.3.2 Spatial Directivity Pattern
6.3.3 Noise Reduction Performance
6.3.4 Robustness Issues
6.4 Complexity Reduction
6.4.1 Linear Algebra Techniques for Computing GSVD
6.4.2 Recursive and Approximate GSVD-Updating Algorithms
6.4.3 Downsampling Techniques
6.4.4 Simulations
6.4.5 Computational Complexity
6.5 Combination with ANC Postprocessing Stage
6.5.1 Creation of Speech and Noise References
6.5.2 Noise Reduction Performance of ANC PostprocessingStage
6.5.3 Comparison with Standard Beamforming Techniques
6.6 Conclusion
7 Explicit Speech Modeling for MicrophoneArray Applications
7.1 Introduction
7.2 Model-Based Strategies
7.2.1 Example 1: A Frequency-Domain Model-Based Algorithm
7.2.2 Example 2: A Time-Domain Model-Based Algorithm
Michael Brandstein . Darren Ward (Eds.)
Microphone Arrays
Signal Processing
Techniques and Applications
With 149 Figures
Springer
Series Editors
Prof. Dr.-Ing. ARILD LACROIX
Johann-Wolfgang-Goethe-Universitiit
Institut ftir angewandte Physik
Robert-Mayer-Str. 2-4
D-60325 Frankfurt
Prof. Dr.-Ing.
ANASTAS lOS VENETSANOPOULOS
University of Toronto
Dept. of Electrical and Computer Engineering
10 King's College Road
M5S 3G4 Toronto, Ontario
Canada
Editors
Prof. MICHAEL BRANDSTEIN
Harvard University,
Div. of Eng. and Applied Scciences
33 Oxford Street
MA 02138 Cambridge
USA
e-mail: msb@hrl.harvard.edu
Dr. DARREN WARD
Imperial College, Dept. of Electrical Engineering
Exhibition Road
SW7 2AZ London
GB
e-mail: d.ward@ic.ac.uk
ISBN 978-3-642-07547-6
DOl 10.1007/978-3-662-04619-7
ISBN 978-3-662-04619-7 (eBook)
Cip data applied for
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this publication or parts thereof is permitted only under the provisions of the German Copyright Law
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Springer-Verlag Berlin Heidelberg GmbH.
Violations are liable for prosecution act under German Copyright Law.
http://www.springer.de
© Springer-Verlag Berlin Heidelberg 2001
Originally published by Springer-Verlag Berlin Heidelberg New York in 2001
Softcover reprint of tbe hardcover 1st edition 2001
The use of general descriptive names, registered names, trademarks, etc. in this publication does not
imply, even in the absence of a specific statement, that such names are exempt from the relevant
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Typesetting: Camera-ready copy by authors
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Preface
The study and implementation of microphone arrays originated over 20 years
ago. Thanks to the research and experimental developments pursued to the
present day, the field has matured to the point that array-based technology
now has immediate applicability to a number of current systems and a vast
potential for the improvement of existing products and the creation of future
devices.
In putting this book together, our goal was to provide, for the first time,
a single complete reference on microphone arrays. We invited the top re
searchers in the field to contribute articles addressing their specific topic(s)
of study. The reception we received from our colleagues was quite enthusi
astic and very encouraging. There was the general consensus that a work
of this kind was well overdue. The results provided in this collection cover
the current state of the art in microphone array research, development, and
technological application.
This text is organized into four sections which roughly follow the major
areas of microphone array research today. Parts I and II are primarily the
oretical in nature and emphasize the use of microphone arrays for speech
enhancement and source localization, respectively. Part III presents a num
ber of specific applications of array-based technology. Part IV addresses some
open questions and explores the future of the field.
Part I concerns the problem of enhancing the speech signal acquired by
an array of microphones. For a variety of applications, including human
computer interaction and hands-free telephony, the goal is to allow users to
roam unfettered in diverse environments while still providing a high quality
speech signal and robustness against background noise, interfering sources,
and reverberation effects. The use of microphone arrays gives one the oppor
tunity to exploit the fact that the source of the desired speech signal and the
noise sources are physically separated in space. Conventional array process
ing techniques, typically developed for applications such as radar and sonar,
were initially applied to the hands-free speech acquisition problem. However,
the environment in which microphone arrays is used is significantly different
from that of conventional array applications. Firstly, the desired speech signal
has an extremely wide bandwidth relative to its center frequency, meaning
that conventional narrowband techniques are not suitable. Secondly, there
VI
Preface
is significant multi path interference caused by room reverberation. Finally,
the speech source and noise signals may located close to the array, meaning
that the conventional far-field assumption is typically not valid. These dif
ferences (amongst others) have meant that new array techniques have had
to be formulated for microphone array applications. Chapter 1 describes the
design of an array whose spatial response does not change appreciably over
a wide bandwidth. Such a design ensures that the spatial filtering performed
by the array is uniform across the entire bandwidth of the speech signal. The
main problem with many array designs is that a very large physical array is
required to obtain reasonable spatial resolution, especially at low frequencies.
This problem is addressed in Chapter 2, which reviews so-called superdirec
tive arrays. These arrays are designed to achieve spatial directivity that is
significantly higher than a standard delay-and-sum beamformer. Chapter 3
describes the use of a single-channel noise suppression filter on the output
of a microphone array. The design of such a post-filter typically requires in
formation about the correlation of the noise between different microphones.
The spatial correlation functions for various directional microphones are in
vestigated in Chapter 4, which also describes the use of these functions in
adaptive noise cancellation applications. Chapter 5 reviews adaptive tech
niques for microphone arrays, focusing on algorithms that are robust and
perform well in real environments. Chapter 6 presents optimal spatial filter
ing algorithms based on the generalized singular-value decomposition. These
techniques require a large number of computations, so the chapter presents
techniques to reduce the computational complexity and thereby permit real
time implementation. Chapter 7 advocates a new approach that combines
explicit modeling of the speech signal (a technique which is well-known in
single-channel speech enhancement applications) with the spatial filtering af
forded by multi-channel array processing.
Part II is devoted to the source localization problem. The ability to locate
and track one or more speech sources is an essential requirement of micro
phone array systems. For speech enhancement applications, an accurate fix
on the primary talker, as well as knowledge of any interfering talkers or coher
ent noise sources, is necessary to effectively steer the array, enhancing a given
source while simultaneously attenuating those deemed undesirable. Location
data may be used as a guide for discriminating individual speakers in a multi
source scenario. With this information available, it would then be possible to
automatically focus upon and follow a given source on an extended basis. Of
particular interest lately, is the application of the speaker location estimates
for aiming a camera or series of cameras in a video-conferencing system. In
this regard, the automated localization information eliminates the need for a
human or number of human camera operators. Several existing commercial
products apply microphone-array technology in small-room environments to
steer a robotic camera and frame active talkers. Chapter 8 summarizes the
various approaches which have been explored to accurately locate an individ-
Preface
VII
ual in a practical acoustic environment. The emphasis is on precision in the
face of adverse conditions, with an appropriate method presented in detail.
Chapter 9 extends the problem to the case of multiple active sources. While
again considering realistic environments, the issue is complicated by the pres
ence of several talkers. Chapter 10 further generalizes the source localization
scenario to include knowledge derived from non-acoustic sensor modalities.
In this case both audio and video signals are effectively combined to track
the motion of a talker.
Part III of this text details some specific applications of microphone array
technology available today. Microphone arrays have been deployed for a vari
ety of practical applications thus far and their utility and presence in our daily
lives is increasing rapidly. At one extreme are large aperture arrays with tens
to hundreds of elements designed for large rooms, distant talkers, and adverse
acoustic conditions. Examples include the two-dimensional, harmonic array
installed in the main auditorium of Bell Laboratories, Murray Hill and the
512-element Huge Microphone Array (HMA) developed at Brown University.
While these systems provide tremendous functionality in the environments
for which they are intended, small arrays consisting of just a handful (usu
ally 2 to 8) of microphones and encompassing only a few centimeters of space
have become far more common and affordable. These systems are intended
for sound capture in close-talking, low to moderate noise conditions (such
as an individual dictating at a workstation or using a hands-free telephone
in an automobile) and have exhibited a degree of effectiveness, especially
when compared to their single microphone counterparts. The technology has
developed to the point that microphone arrays are now available in off-the
shelf consumer electronic devices available for under $150. Because of their
growing popularity and feasibility we have chosen to focus primarily on the
issues associated with small-aperture devices. Chapter 11 addresses the in
corporation of multiple microphones into hearing aid devices. The ability of
beamforming methods to reduce background noise and interference has been
shown to dramatically improve the speech understanding of the hearing im
paired and to increase their overall satisfaction with the device. Chapter 12
focuses on the case of a simple two-element array combined with postfiltering
to achieve noise and echo reduction. The performance of this configuration
is analyzed under realistic acoustic conditions and its utility is demonstrated
for desktop conferencing and intercom applications. Chapter 13 is concerned
with the problem of acoustic feedback inherent in full-duplex communica
tions involving loudspeakers and microphones. Existing single-channel echo
cancellation methods are integrated within a beamforming context to achieve
enhanced echo suppression. These results are applied to single- and multi
channel conferencing scenarios. Chapter 14 explores the use of microphone
arrays for sound capture in automobiles. The issues of noise, interference, and
echo cancellation specifically within the car environment are addressed and a
particularly effective approach is detailed. Chapter 15 discusses the applica-
VIII
Preface
tion of microphone arrays to improve the performance of speech recognition
systems in adverse conditions. Strategies for effectively coupling the acous
tic signal enhancements afforded through beamforming with existing speech
recognition techniques are presented. A specific adaptation of a recognizer to
function with an array is presented. Finally, Chapter 16 presents an overview
of the problem of separating blind mixtures of acoustic signals recorded at a
microphone array. This represents a very new application for microphone ar
rays, and is a technique that is fundamentally different to the spatial filtering
approaches detailed in earlier chapters.
In the final section of the book, Part IV presents expert summaries of
current open problems in the field, as well as personal views of what the future
of microphone array processing might hold. These summaries, presented in
Chapters 17 and 18, describe both academically-oriented research problems,
as well as industry-focused areas where microphone array research may be
headed.
The individual chapters that we selected for .the book were designed to
be tutorial in nature with a specific emphasis on recent important results.
We hope the result is a text that will be of utility to a large audience, from
the student Or practicing engineer just approaching the field to the advanced
researcher with multi-channel signal processing experience.
Cambridge MA, USA
London, UK
January 2001
Michael Brandstein
Darren Ward
Contents
Part I. Speech Enhancement
1 Constant Directivity Beamforming
Darren B. Ward, Rodney A. Kennedy, Robert C. Williamson ........ 3
1.1 Introduction................................................ 3
1.2 Problem Formulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6
7
1.3 Theoretical Solution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3.1 Continuous sensor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7
1.3.2 Beam-shaping function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
1.4 Practical Implementation .................................... 9
1.4.1 Dimension-reducing parameterization. . . . . . . . . . . . . . . .. . . .
9
1.4.2 Reference beam-shaping filter. . . . . . . . . . . . . . . . . . . . . . . . . .. 11
1.4.3 Sensor placement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 12
1.4.4 Summary of implementation . . . . . . . . . . . . . . . . . . . . . . . . . . .. 12
1.5 Examples;................................................. 13
1.6 Conclusions .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 16
References ..................................................... 16
2 Superdirective Microphone Arrays
Joerg Bitzer, K. Uwe Simmer .................................... 19
2.1 Introduction................................................ 19
2.2 Evaluation of Beamformers... .. . . . . .. .. . . . . . . . . . . . .. . . . . .. ... 20
2.2.1 Array-Gain........................................... 21
2.2.2 Beampattern.......................................... 22
2.2.3 Directivity............................................ 23
2.2.4 Front-to-Back Ratio ................................... 24
2.2.5 White Noise Gain ..................................... 24
2.3 Design of Superdirective Beamformers . . . . . . . . . . . . . . . . . . . . . . . .. 24
2.3.1 Delay-and-Sum Beamformer ............................ 26
2.3.2 Design for spherical isotropic noise. . . . . . . . . . . . . . . . . . . . . .. 26
2.3.3 Design for Cylindrical Isotropic Noise . . . . . . . . . . . . . . . . . . .. 30
2.3.4 Design for an Optimal Front-to-Back Ratio.. .. . . . . . . . . ... 30
2.3.5 Design for Measured Noise Fields. . .. . . . . . .. . . . . .. . . . . ... 32
2.4 Extensions and Details ...................................... 33
2.4.1 Alternative Form. . .. . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. 33
X
Contents
2.4.2 Comparison with Gradient Microphones. . . . . . . . . . . . . . . . .. 35
2.5 Conclusion................................................. 36
References ..................................................... 37
3 Post-Filtering Techniques
K. Uwe Simmer, Joerg Bitzer, Claude Marro. .. . . . . . . . .. . . . . . . . . . .. 39
3.1 Introduction................................................ 39
3.2 Multi-channel Wiener Filtering in Subbands . . . . . . . . . . . . . . . . . . .. 41
3.2.1 Derivation of the Optimum Solution. . . . . . .. . . . . .. . . . . . .. 41
3.2.2 Factorization of the Wiener Solution . . . . . . . . . . . . . . . . . . . .. 42
3.2.3 Interpretation......................................... 45
3.3 Algorithms for Post-Filter Estimation ......................... 46
3.3.1 Analysis of Post-Filter Algorithms. . . . . . . . . . . . . . . . . . . . . .. 47
3.3.2 Properties of Post-Filter Algorithms ..................... 49
3.3.3 A New Post-Filter Algorithm ........................... 50
3.4 Performance Evaluation ..................................... 51
3.4.1 Simulation System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 52
3.4.2 Objective Measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 52
3.4.3 Simulation Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 54
3.5 Conclusion................................................. 57
4 Spatial Coherence Functions for Differential Microphones
in Isotropic Noise Fields
Gary W. Elko .... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 61
4.1 Introduction................................................ 61
4.2 Adaptive Noise Cancellation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 61
4.3 Spherically Isotropic Coherence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 65
4.4 Cylindrically Isotropic Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 73
4.5 Conclusions................................................ 77
References ..................................................... 84
5 Robust Adaptive Beamforming
Osamu Hoshuyama, Akihiko Sugiyama. . . . . . . . . . . . . . . . . . . . . . . . . . . .. 87
5.1 Introduction................................................ 87
5.2 Adaptive Beamformers . .... . . . . . . . . . . .. . . . . . . . . . .. . . .. . . . . . .. 88
5.3 Robustness Problem in the GJBF . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 90
5.4 Robust Adaptive Microphone Arrays -
Solutions to Steering-
Vector Errors .............................................. 92
5.4.1 LAF-LAF Structure ................................... 92
5.4.2 CCAF-LAF Structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 94
5.4.3 CCAF-NCAF Structure.......... ... ...... ............. 95
5.4.4 CCAF-NCAF Structure with an AMC ................... 97
5.5 Software Evaluation of a Robust Adap~ive Microphone Array. . . .. 99
5.5.1 Simulated Anechoic Environment.. .. . . . . . .. . . . . .. . . . . . .. 99
5.5.2 Reverberant Environment .............................. 101
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