Title
Analysis and Comparison of Multichannel Noise Reduction Methods in a Common Framework
Abstract
Noise reduction for speech enhancement is a useful technique, but in general it is a challenging problem. While a single-channel algorithm is easy to use in practice, it inevitably introduces speech distortion to the desired speech signal while reducing noise. Today, the explosive growth in computational power and the continuous drop in the cost and size of acoustic electric transducers are driving the interest of employing multiple microphones in speech processing systems. This opens new opportunities for noise reduction. In this paper, we present an analysis of three multichannel noise reduction algorithms, namely Wiener filter, subspace, and spatial-temporal prediction, in a common framework. We intend to investigate whether it is possible for the multichannel noise reduction algorithms to reduce noise without speech distortion. Finally, we justify what we learn via theoretical analyses by simulations using real impulse responses measured in the varechoic chamber at Bell Labs.
Year
DOI
Venue
2008
10.1109/TASL.2008.921754
IEEE Transactions on Audio, Speech & Language Processing
Keywords
Field
DocType
explosives,impulse response,wiener filter,acoustic noise,noise reduction,algorithm design and analysis,signal processing,speech processing
Wiener filter,Speech enhancement,Noise reduction,Noise,Speech processing,Median filter,Noise measurement,Noise (signal processing),Computer science,Speech recognition
Journal
Volume
Issue
ISSN
16
5
1558-7916
Citations 
PageRank 
References 
32
1.38
20
Authors
3
Name
Order
Citations
PageRank
Yiteng Huang1123998.26
Jacob Benesty21941146.01
Jingdong Chen31460128.79