| 期刊全称 | A Perspective on Single-Channel Frequency-Domain Speech Enhancement | | 影响因子2023 | Jacob Benesty,Yiteng Huang | | 视频video | | | 学科分类 | Synthesis Lectures on Speech and Audio Processing | | 图书封面 |  | | 影响因子 | This book focuses on a class of single-channel noise reduction methods that are performed in the frequency domain via the short-time Fourier transform (STFT). The simplicity and relative effectiveness of this class of approaches make them the dominant choice in practical systems. Even though many popular algorithms have been proposed through more than four decades of continuous research, there are a number of critical areas where our understanding and capabilities still remain quite rudimentary, especially with respect to the relationship between noise reduction and speech distortion. All existing frequency-domain algorithms, no matter how they are developed, have one feature in common: the solution is eventually expressed as a gain function applied to the STFT of the noisy signal only in the current frame. As a result, the narrowband signal-to-noise ratio (SNR) cannot be improved, and any gains achieved in noise reduction on the fullband basis come with a price to pay, which is speechdistortion. In this book, we present a new perspective on the problem by exploiting the difference between speech and typical noise in circularity and interframe self-correlation, which were ignored i | | Pindex | Book 2011 |
The information of publication is updating
|
|
发表于 2025-3-21 19:36:37
