《语音信号处理：理论与实践》第二版

语音信号处理

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"语音信号处理——理论与实践(第二版)"，作者Philipos C. Loizou，本书深入探讨了语音增强的理论与实践方法，是该领域的权威读物。语音信号处理是通信、音频工程、人工智能和人机交互等多个领域中的关键技术。这本书详细介绍了语音处理的基础知识和最新发展，主要涵盖了以下几个核心知识点： 1. **语音信号的基本概念**：书中首先会讲解语音信号的生成机制，包括声学模型和生理模型，以及声音的物理特性如频率、幅度和时间结构。 2. **数字信号处理基础**：对于语音信号处理，数字信号处理是必不可少的工具。这包括采样理论、傅里叶变换、滤波器设计、快速傅里叶变换(FFT)等基本概念和方法。 3. **语音增强技术**：这是本书的重点，涉及噪声抑制、回声消除、混响减少、多说话人分离等实际问题的解决方案。这些技术有助于提高语音的清晰度和可理解性，尤其在嘈杂环境中。 4. **统计建模与自适应处理**：书中可能涵盖高斯混合模型(GMM)、隐马尔科夫模型(HMM)在语音识别和增强中的应用，以及自适应滤波算法，如LMS(最小均方误差)和RLS(递归最小二乘)算法。 5. **现代语音处理技术**：可能包括深度学习在语音识别、情感分析和语音增强中的应用，如卷积神经网络(CNN)、循环神经网络(RNN)和长短时记忆网络(LSTM)。 6. **MATLAB实现**：作者可能会提供MATLAB代码示例，帮助读者理解和实现书中介绍的算法，以便进行实验和进一步研究。 7. **评估方法**：书中会讨论评估语音处理效果的方法，如客观质量度量（如PESQ，PER）和主观评价标准（如MOS，MUSHRA）。 8. **实践应用**：除了理论部分，书中的例子和练习将连接理论与实际应用，涵盖如语音通信、语音识别、语音合成、助听设备等领域。通过阅读这本书，读者可以系统地掌握语音信号处理的理论知识，并具备解决实际问题的能力。对于研究生、研究人员以及相关行业的工程师来说，是一本不可多得的参考书。

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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

这一节展望挺好

混响

干扰

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

可能的创新点

我们队均方误差的痴

迷，迟滞了噪声消除

的发展

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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