语音增强与降噪技术实践第二版

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"语音增强，降噪pdf - Speech.Enhancement.Theory.and.Practice.2nd.Edition" 《语音增强：理论与实践》第二版是由Philipos C. Loizou编著的专业书籍，主要关注的是语音处理领域中的一个重要课题——语音增强与降噪。这本书深入探讨了如何在实际应用中改善语音质量，提升语音信号的可理解性和听觉体验。语音增强是语音通信、语音识别、听力辅助设备以及许多其他音频处理系统的关键技术。这一领域涉及广泛的理论和实践知识，包括信号处理、统计建模、机器学习以及噪声抑制算法等。书中的内容可能涵盖以下几个方面： 1. **语音信号的基础理论**：介绍语音产生的生理过程、声学特性以及数字信号表示，这是理解和处理语音的基础。 2. **噪声模型**：分析各种环境噪声，如白噪声、粉红噪声、交通噪声等，了解它们对语音的影响和建模方法。 3. **信号增强算法**：讲解如Wiener滤波器、谱减法、自适应滤波、非负矩阵分解（NMF）等用于噪声抑制和语音增强的技术。 4. **统计建模**：讨论统计建模在语音增强中的应用，如高斯混合模型（GMM）、隐马尔科夫模型（HMM）等，这些模型可以帮助识别和分离语音和噪声。 5. **实时系统实现**：介绍如何将理论算法应用于实际的硬件或软件系统，包括处理速度、计算复杂度和实时性方面的考虑。 6. **评估方法**：探讨客观和主观评估标准，如珀塞尔等级、信噪比（SNR）提升、语音可懂度指数（STOI）等，用于衡量增强效果。 7. **MATLAB实现**：虽然书中可能不保证MATLAB代码的准确性，但作者可能提供了一些示例代码或练习，帮助读者理解和应用所学概念。 8. **应用案例**：可能包含实际应用场景，如语音识别系统的预处理、无线通信中的语音传输优化、听力障碍者的助听设备等。 9. **最新研究进展**：第二版可能涵盖了自第一版以来的最新研究成果和技术进步。此书对于电子工程师、计算机科学家、音频工程师以及在语音处理相关领域工作的专业人士来说是一份宝贵的参考资料，它不仅提供了深入的理论背景，还强调了实践应用和问题解决。通过阅读和实践，读者能够掌握提高语音质量和清晰度的技巧，从而在各自的领域中实现更好的性能。

xvContents

12.2.5 Comparisons in Reference to Noisy Speech ............593

12.2.6 Contribution of Speech and Noise Distortion

toJudgment of Overall Quality ................................ 597

12.2.7 Summary of Findings ...............................................598

12.3 Comparison of Enhancement Algorithms:

SpeechIntelligibility ............................................................. 598

12.3.1 Listening Tests: Procedure ....................................... 599

12.3.2 Intelligibility Evaluation: Results ............................. 600

12.3.3 Intelligibility Comparison among Algorithms .........602

12.3.4 Intelligibility Comparison against Noisy

Speech .............................................................. 603

12.3.5 Summary of Findings ............................................... 604

12.5 Summary ...............................................................................605

References ........................................................................................605

PART IV Future Steps

Chapter 13 Algorithms That CanImprove Speech Intelligibility ......................609

13.1 Reasons for the Absence of Intelligibility Improvement

with ExistingNoise-Reduction Algorithms ..........................609

13.1.1 Inuence of Speech Distortions ............................... 610

13.1.2 Lack of Effective SNR Increase ............................... 612

13.2 Algorithms Based on Channel Selection: ADifferent

Paradigm for Noise Reduction .............................................. 613

13.3 Channel-Selection Criteria .................................................... 619

13.3.1 SNR Criterion ...........................................................620

13.3.2 SNR

ESI

Selection Criterion ....................................... 623

13.3.3 Other Selection Criteria ............................................628

13.3.4 Channel-Selection Criteria for Reverberation .......... 629

13.3.5 Universal Selection Criterion for All Types

ofBackground Interferers ........................................ 631

13.4 Intelligibility Evaluation of Channel- Selection-Based

Algorithms: Ideal Conditions ................................................ 632

13.4.1 Broadband Noise Conditions .................................... 633

13.4.2 Competing-Talker Conditions ..................................634

13.4.3 Reverberant Conditions ............................................ 639

13.5 Implementation of Channel-Selection-Based Algorithms

in Realistic Conditions .......................................................... 639

13.5.1 Simple, But Ineffective, Algorithms for Binary

Mask Estimation .......................................................640

13.5.2 Effective Channel-Selection Algorithms Based

on Binary Classiers ................................................ 641

13.5.3 Adapting to New Noise Environments ..................... 645

xvii

Preface to the Second Edition

The second edition of this text not only revises the rst edition but also expands it.

In particular, it includes two new chapters. Chapter 11 provides a thorough cover-

age of objective intelligibility measures and Chapter 13 covers algorithms that can

improve speech intelligibility. The feedback I received from most readers about the

rst edition is that much of the focus of the text has been placed on algorithms that

can improve speech quality rather than speech intelligibility. The second edition

comes in response to those readers. With the proliferation of mobile devices and hear-

ing devices (hearing aids and cochlear implants), there is a growing and pressing need

to design algorithms that can improve speech intelligibility without sacricing qual-

ity. The inclusion of a chapter on intelligibility measures, which can predict reliably

speech intelligibility, is absolutely necessary in order to understand why the algo-

rithms described in Chapter 13 do improve speech intelligibility. Secondly, having a

good understanding of some of the commonly used intelligibility metrics can assist us

in the design of novel noise reduction algorithms that derive statistical estimators that

maximize/minimize such metrics. This stands in contrast with the conventional esti-

mators that aim to minimize the mean-square error (MSE), a metric that is “speech

ignorant” and not motivated by any known facts about how human listeners are able

to perceive speech in complex listening situations. It is the opinion of this author that

our obsession with the MSE metric delayed progress in the eld of noise reduction.

The contents of the DVD-ROM have also been updated to include (1)MATLAB

code with the implementation of some of the intelligibility measures described in

Chapter 11, (2) MATLAB code and C/C++ code with the implementation of the

algorithms described in Chapter 13, and (3) real-world noise recordings. In addition,

it includes the implementation of the wideband-version of the PESQ measure for

assessing the quality of speech sampled at rates higher than 8 kHz.

I wish to express my sincere thanks to all my graduate students who contributed

in some way to the writing of the second edition. In particular, I would like to

thank my postdoctorate students, Drs. Kamil Wójcicki, Jianfen Ma, and Fei Chen,

who wrote many of the MATLAB algorithms included in the updated DVD-ROM.

Many thanks also go to Oldooz Hazrati and Dr. Kostas Kokkinakis. Thanks also

go to Jacky Gao, Yi Gao, Li Xiao, and Fang Deng who, in the course of translat-

ing the rst edition to Chinese, found many errors and typos. I am also thankful

to Nora Konopka, editor at Taylor & Francis Group, for providing the support and

encouragement for this book.

Finally, I would like to express my deepest gratitude to my wife Demetria for her

understanding and undying support throughout this project.

Philipos C. Loizou

University of Texas at Dallas

Dallas, Texas

xix

Preface to the First Edition

This text is, in part, an outgrowth of my graduate course on speech signal processing,

which I have been teaching at the University of Texas at Dallas since the fall of 1999.

It is also, in part, a product of my own research in the area. The fact that no textbook

existed at the time on speech enhancement, other than a few edited books suitable for

the experts, made it difcult to teach the fundamental principles of speech enhance-

ment in a graduate-level course. It must be equally frustrating for new students or

speech scientists interested in getting into the eld of speech enhancement without

having access to a tutorial review or introductory paper (the last review paper was

published in the Proceedings of IEEE in 1979 by Lim and Oppenheim). That work

provided the initial motivation to write this book. My interest in this area stems from

my research to develop noise reduction algorithms that can be used to help hearing-

impaired listeners (cochlear implant listeners) better communicate in noisy environ-

ments.* Crucial to the development of such noise reduction algorithms is the basic

understanding of the limitations and potential of existing enhancement algorithms,

which I believe this book provides.

The textbook consists of 11 chapters, which are outlined in detail in Chapter 1

(Introduction). It is divided into three main parts. Part I presents the digital-signal

processing and speech-signal fundamentals needed to understand speech enhance-

ment algorithms. Part II presents the various classes of speech enhancement algo-

rithms proposed over the past two decades, and Part III presents the methods and

measures used to evaluate the performance of speech enhancement algorithms.

The text body is supplemented with examples and gures designed to help the

reader understand the theory. The book is accompanied by a DVD-ROM, which

contains a speech corpus appropriate for quality and intelligibility evaluation of

processed speech, and MATLAB

code with the implementation of major speech

enhancement algorithms. It is my strong belief that having access to MATLAB code

and a common speech database against which to evaluate new speech enhancement

algorithms is crucial and necessary in order to move the eld forward. Appendix C

provides a detailed description of the contents of the DVD-ROM.

The book can be used as a textbook for a one-semester graduate-level course on

speech enhancement. Necessary prerequisites for such a course would be a course

on digital signal processing and fundamental knowledge of probability theory, ran-

dom variables, and linear algebra. This book can also be used as a supplement to an

introductory course on speech processing. In this case, Chapters 4 through 8 could

be covered along with a select set of sections from Chapters 9 and 10.

I wish to express my sincere thanks to the many colleagues and graduate stu-

dents who contributed in some way to the writing of this book. I would like to

thank Professors Patrick Wolfe, Kuldip Paliwal, Peter Assmann, John Hansen, and

This work is supported by the National Institutes on Deafness and Other Communication Disorders,

NIH.

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