Canonical Correlation Analysis in Speech Enhancement / SpringerBriefs in Electrical and Computer Engineering (PDF)
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This book focuses on the application of canonical correlation analysis (CCA) to speech enhancement using the filtering approach. The authors explain how to derive different classes of time-domain and time-frequency-domain noise reduction filters, which are optimal from the CCA perspective for both single-channel and multichannel speech enhancement. Enhancement of noisy speech has been a challenging problem for many researchers over the past few decades and remains an active research area. Typically, speech enhancement algorithms operate in the short-time Fourier transform (STFT) domain, where the clean speech spectral coefficients are estimated using a multiplicative gain function. A filtering approach, which can be performed in the time domain or in the subband domain, obtains an estimate of the clean speech sample at every time instant or time-frequency bin by applying a filtering vector to the noisy speech vector.
Compared to the multiplicative gain approach, the filtering approach more naturally takes into account the correlation of the speech signal in adjacent time frames. In this study, the authors pursue the filtering approach and show how to apply CCA to the speech enhancement problem. They also address the problem of adaptive beamforming from the CCA perspective, and show that the well-known Wiener and minimum variance distortionless response (MVDR) beamformers are particular cases of a general class of CCA-based adaptive beamformers.
Israel Cohen is a Professor of Electrical Engineering at the Technion - Israel Institute of Technology, Haifa, Israel. He received his B.Sc. (Summa Cum Laude), M.Sc. and Ph.D. degrees in Electrical Engineering from the Technion in 1990, 1993 and 1998, respectively.
From 1990 to 1998, he was a Research Scientist with RAFAEL Research Laboratories, Haifa, Israel Ministry of Defense. From 1998 to 2001, he was a Postdoctoral Research Associate with the Department of Computer Science, Yale University, New Haven, Connecticut (CT), USA. In 2001, he joined the Technion's Department of Electrical Engineering.
He is a coeditor of the multichannel speech processing section of the Springer Handbook of Speech Processing (Springer, 2008), a co-author of Noise Reduction in Speech Processing (Springer, 2009), a coeditor of Speech Processing in Modern Communication: Challenges and Perspectives (Springer, 2010), and a General Cochair of the 2010 International Workshop on Acoustic Echo and Noise Control.
His research interests include statistical signal processing, analysis and modeling of acoustic signals, speech enhancement, noise estimation, microphone arrays, source localization, blind source separation, system identification, and adaptive filtering.
- Autoren: Jacob Benesty , Israel Cohen
- 2017, 1st ed. 2018, 121 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319670204
- ISBN-13: 9783319670201
- Erscheinungsdatum: 31.08.2017
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