Benesty, Jacob

Chen, Jingdong

Christensen, Mads Græsbøll

Jensen, Jesper Rindom

EURASIP Journal on Advances in Signal Processing

Jacob Benesty

Mads Græsbøll Christensen

Jesper Rindom Jensen

Jingdong Chen

Springer - Publisher Connector

A brief overview of speech enhancement with linear filtering

In this paper, we provide an overview of some recently introduced principles and ideas for speech enhancement with linear filtering and explore how these are related, and how they can be used in various applications. This is done in a general framework where the speech enhancement problem is stated as a signal vector estimation problem, i.e., with a filter matrix, where the estimate is obtained by means of a matrix-vector product of the filter matrix and the noisy signal vector. In this framework minimum distortion, MVDR, tradeoff, maximum SNR, and Wiener filters are derived from the conventional speech enhancement approach and the recently introduced orthogonal decomposition approach. For each of the filters, we derive their properties in terms of output SNR and speech distortion. We then demonstrate how the ideas can be applied to single- and multichannel noise reduction in both the time and frequency domains as well as binaural noise reduction.In this paper, we provide an overview of some recently introduced principles and ideas for speech enhancement with linear filtering and explore how these are related and how they can be used in various applications. This is done in a general framework where the speech enhancement problem is stated as a signal vector estimation problem, i.e., with a filter matrix, where the estimate is obtained by means of a matrix-vector product of the filter matrix and the noisy signal vector. In this framework, minimum distortion, minimum variance distortionless response (MVDR), tradeoff, maximum signal-to-noise ratio (SNR), and Wiener filters are derived from the conventional speech enhancement approach and the recently introduced orthogonal decomposition approach. For each of the filters, we derive their properties in terms of output SNR and speech distortion. We then demonstrate how the ideas can be applied to single- and multichannel noise reduction in both the time and frequency domains as well as binaural noise reduction

file:///data/remote/core/dit/data/Springer-OA/pdf/dc3/aHR0cDovL2xpbmsuc3ByaW5nZXIuY29tLzEwLjExODYvMTY4Ny02MTgwLTIwMTQtMTYyLnBkZg==.pdf

A brief overview of speech enhancement with linear filtering

Abstract

Similar works

Full text

Available Versions

Springer - Publisher Connector

Springer - Publisher Connector

VBN