| 书目名称 | Canonical Correlation Analysis in Speech Enhancement |
| 编辑 | Jacob Benesty,Israel Cohen |
| 视频video | |
| 概述 | Focusses on the challenging problem enhancing of noisy speech.Shows how to apply filtering approach and the CCA to the speech enhancement problem.Address also the problem of adaptive beamforming from |
| 丛书名称 | SpringerBriefs in Electrical and Computer Engineering |
| 图书封面 |  |
| 描述 | .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 enhan |
| 出版日期 | Book 2018 |
| 关键词 | CCA Canonical Correlation Analysis; Time-frequency-domain Noise Reduction; Single-channel speech enhan |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-67020-1 |
| isbn_softcover | 978-3-319-67019-5 |
| isbn_ebook | 978-3-319-67020-1Series ISSN 2191-8112 Series E-ISSN 2191-8120 |
| issn_series | 2191-8112 |
| copyright | The Author(s) 2018 |
发表于 2025-3-21 18:01:53
