Speech Dereverberation

1. Front Matter

   Pages i-xviii

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2. Introduction

   • Patrick A. Naylor, Nikolay D. Gaubitch

   Pages 1-19

3. Models, Measurement and Evaluation

   • Patrick A. Naylor, Emanuël A. P. Habets, Jimi Y.-C. Wen, Nikolay D. Gaubitch

   Pages 21-56

4. Speech Dereverberation Using Statistical Reverberation Models

   • Emanuël A. P. Habets

   Pages 57-93

5. Dereverberation Using LPC-based Approaches

   • Nikolay D. Gaubitch, Mark R. P. Thomas, Patrick A. Naylor

   Pages 95-128

6. Multi-microphone Speech Dereverberation Using Eigen-decomposition

   • Sharon Gannot

   Pages 129-156

7. Adaptive Blind Multichannel System Identification

   • Andy Khong, Patrick A. Naylor

   Pages 157-187

8. Subband Inversion of Multichannel Acoustic Systems

   • Nikolay D. Gaubitch, Patrick A. Naylor

   Pages 189-217

9. Bayesian Single Channel Blind Dereverberation of Speech from a Moving Talker

   • James R. Hopgood, Christine Evers, Steven Fortune

   Pages 219-270

10. Inverse Filtering for Speech Dereverberation Without the Use of Room Acoustics Information

    • Masato Miyoshi, Marc Delcroix, Keisuke Kinoshita, Takuya Yoshioka, Tomohiro Nakatani, Takafumi Hikichi

    Pages 271-310

11. TRINICON for Dereverberation of Speech and Audio Signals

    • Herbert Buchner, Walter Kellermann

    Pages 311-385

12. Back Matter

    Pages 387-388

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Speech Dereverberation gathers together an overview, a mathematical formulation of the problem and the state-of-the-art solutions for dereverberation.

Speech Dereverberation presents current approaches to the problem of reverberation. It provides a review of topics in room acoustics and also describes performance measures for dereverberation. The algorithms are then explained with mathematical analysis and examples that enable the reader to see the strengths and weaknesses of the various techniques, as well as giving an understanding of the questions still to be addressed. Techniques rooted in speech enhancement are included, in addition to a treatment of multichannel blind acoustic system identification and inversion. The TRINICON framework is shown in the context of dereverberation to be a generalization of the signal processing for a range of analysis and enhancement techniques.

Speech Dereverberation is suitable for students at masters and doctoral level, as well as established researchers.

• Acoustics
• CP4748
• Dereverberation
• Speech Enhancement
• Speech Processing
• Speech Recognition
• algorithms
• room acoustics

From the reviews:

“A comprehensive overview of the current state of the art in advanced signal processing techniques for improving speech enhancement through speech dereverberation … . targeted to established researchers and students at the masters and doctoral level and will be particularly attractive to those interested in detailed mathematical and statistical presentations of signal processing techniques. …  highly recommended for anyone interested in learning about the latest state of the art solutions and future areas of research in this exciting and important field.” (Emily Cross, Noise Control Engineering Journal, Vol. 59 (2), March-April, 2011)

• Department of Electrical and Electronic Engineering, Imperial College London, London, UK

  Patrick A. Naylor, Nikolay D. Gaubitch

Patrick A. Naylor has a PhD in Speech Signal Processing from Imperial College London, where he is currently Reader and Director of Postgraduate Studies for the Department of Electrical and Electronic Engineering. His research interests include speech and audio signal processing; adaptive signal processing; speech enhancement in telecommunications; hands-free functionality; blind SIMO/MIMO channel estimation and dereverberation; speaker identification and verification; and speech production modelling. He is on the IEEE Technical Committee on Audio and Electroacoustics and is Associate Editor of the IEEE Transactions on Audio Speech and Language Processing.

Nikolay D. Gaubitch has a PhD in Acoustic Signal Processing from Imperial College London, where he is now Research Associate. In 2001 and 2002 he was awarded the Drapers' Company Undergraduate Prize for outstanding academic achievement. His research interests span various topics in single and multichannel speech and audio processing including dereverberation, blind system identification, acoustic system equalization and speech enhancement. He is a member of the IEEE.

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