Blind Speech Separation von Shoji (Hrsg.) Makino

CHF 216.00 inkl. MwSt.
ISBN: 978-1-4020-6478-4
Einband: Fester Einband
Verfügbarkeit: Lieferbar in ca. 20-45 Arbeitstagen
+ -

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.


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.


AutorMakino, Shoji (Hrsg.) / Lee, Te-Won (Hrsg.) / Sawada, Hiroshi (Hrsg.)
EinbandFester Einband
Erscheinungsjahr2007
Seitenangabe432 S.
LieferstatusLieferbar in ca. 20-45 Arbeitstagen
AusgabekennzeichenEnglisch
MasseH23.5 cm x B15.5 cm 1'780 g
CoverlagSpringer (Imprint/Brand)
ReiheSignals and Communication Technology
VerlagSpringer Nature EN

Alle Bände der Reihe "Signals and Communication Technology"

Über den Autor Shoji (Hrsg.) Makino

SHOJI MAKINO (F) received the B. E., M. E., and Ph.D. degrees from Tohoku University, Japan, in 1979, 1981, and 1993, respectively. He joined NTT in 1981. He is now a Professor at University of Tsukuba. His research interests include adaptive filtering technologies, realization of acoustic echo cancellation, blind source separation of convolutive mixtures of speech, and acoustic signal processing for speech and audio applications. Dr. Makino received the IEEE SPS Best Paper Award in 2014, the IEEE MLSP Competition Award in 2007, the ICA Unsupervised Learning Pioneer Award in 2006, the Commendation for Science and Technology of Japanese Government in 2015, the TELECOM System Technology Award in 2015 and 2004, the Achievement Award of the Institute of Electronics, Information, and Communication Engineers (IEICE) in 1997, and the Outstanding Technological Development Award of the Acoustical Society of Japan (ASJ) in 1995, the Paper Award of the IEICE in 2005 and 2002, the Paper Award of the ASJ in 2005 and 2002. He is the author or co-author of more than 200 articles in journals and conference proceedings and is responsible for more than 150 patents. He was a Keynote Speaker at ICA2007 and a Tutorial speaker at EMBC 2013, Interspeech 2011 and ICASSP 2007. Dr. Makino IEEE activities include: Member, SPS Technical Directions Board (2013-14), SPS Awards Board (2006-08), SPS Conference Board (2002-04), IEEE Jack S. Kilby Signal Processing Medal Committee (2015-), IEEE James L. Flanagan Speech & Audio Processing Award Committee (2008-11) and Member and Chair, SPS Audio and Electroacoustics Technical Committee (1993-09 and 2013-14, respectively); SPS Distinguished Lecturer (2009-10); Chair, Circuits and Systems Society Blind Signal Processing Technical Committee (2009-2010); Associate Editor, IEEE Transactions on Speech and Audio Processing (2002-05) and EURASIP Journal on Advances in Signal Processing (2005-2012). He was the Vice President, Engineering Sciences Society of the IEICE (2007-08) and Chair, Engineering Acoustics Technical Committee of the IEICE (2006-08). He is a Member, International IWAENC Standing committee and International ICA Steering Committee; General Chair, WASPAA2007 and IWAENC2003; Organizing Chair, ICA2003; and Plenary Chair, ICASSP2012. Dr. Makino is an IEEE Fellow, an IEICE Fellow, a Board member of the ASJ, and a member of EURASIP and ISCA.

Weitere Titel von Shoji (Hrsg.) Makino