Canonical correlation analysis in speech enhancement
72,56 $

Canonical correlation analysis in speech enhancement

JACOB BENESTY, ISRAEL COHEN


Canonical correlation analysis in speech enhancement

JACOB BENESTY, ISRAEL COHEN

72,56 $ 72,56 $
Régulier: 72,56 $
Rabais: 0,00 $ (0%)
Livre numérique non disponible
Résumé

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.


Détails
Titre
Canonical correlation analysis in speech enhancement
Prix
72,56 $
Sujet
Format Poche
Non
Langue
Français/French
Date de publication
2017-08-31
ISBN
9783319670201
Code Interne
2323032
Numéro de produit
2323032
Format numérique
pdf
Disponibilité
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Protection
Adobe DRM
Entrepôt Numérique
NUMILOG

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