Blind Speech Separation
Editors: Makino, Shoji, Lee, Te-Won, Sawada, Hiroshi (Eds.)
Free Preview- The world’s first edited book on independent component analysis (ICA)-based blind source separation (BSS) of convolutive mixtures of speech
- Brings together a small number of leading researchers to provide tutorial-like and in-depth treatment on major ICA-based BSS topics, with the objective of becoming the definitive source for current, comprehensive, authoritative, and yet accessible treatment
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- About this book
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This is the first book to provide a cutting edge reference to the fascinating topic of blind source separation (BSS) for convolved speech mixtures. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications. The individual chapters are designed to be tutorial in nature with specific emphasis on an in-depth treatment of state of the art techniques.
Blind Speech Separation is divided into three parts:
Part 1 presents overdetermined or critically determined BSS. Here the main technology is independent component analysis (ICA). ICA is a statistical method for extracting mutually independent sources from their mixtures. This approach utilizes spatial diversity to discriminate between desired and undesired components, i.e., it reduces the undesired components by forming a spatial null towards them. It is, in fact, a blind adaptive beamformer realized by unsupervised adaptive filtering.
Part 2 addresses underdetermined BSS, where there are fewer microphones than source signals. Here, the sparseness of speech sources is very useful; we can utilize time-frequency diversity, where sources are active in different regions of the time-frequency plane.
Part 3 presents monaural BSS where there is only one microphone. Here, we can separate a mixture by using the harmonicity and temporal structure of the sources. We can build a probabilistic framework by assuming a source model, and separate a mixture by maximizing the a posteriori probability of the sources.
- About the authors
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Dr. Shoji Makino is an IEEE Fellow, Associate Editor of the IEEE Transactions on Speech & Audio Processing, and Executive Manager NTT Communication Science Laboratories. Dr. Makino was also co-editor on the succesful 2005 Springer book: Benesty - Speech Enhancement.
- Table of contents (15 chapters)
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Convolutive Blind Source Separation for Audio Signals
Pages 3-45
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Frequency-Domain Blind Source Separation
Pages 47-78
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Blind Source Separation using Space–Time Independent Component Analysis
Pages 79-99
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TRINICON-based Blind System Identification with Application to Multiple-Source Localization and Separation
Pages 101-147
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SIMO-Model-Based Blind Source Separation – Principle and its Applications
Pages 149-168
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Table of contents (15 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Blind Speech Separation
- Editors
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- Shoji Makino
- Te-Won Lee
- Hiroshi Sawada
- Series Title
- Signals and Communication Technology
- Copyright
- 2007
- Publisher
- Springer Netherlands
- Copyright Holder
- Springer Science+Business Media B.V.
- eBook ISBN
- 978-1-4020-6479-1
- DOI
- 10.1007/978-1-4020-6479-1
- Hardcover ISBN
- 978-1-4020-6478-4
- Softcover ISBN
- 978-90-481-7651-9
- Series ISSN
- 1860-4862
- Edition Number
- 1
- Number of Pages
- XVI, 432
- Topics
