Title
On the Importance of the Pearson Correlation Coefficient in Noise Reduction
Abstract
Noise reduction, which aims at estimating a clean speech from noisy observations, has attracted a considerable amount of research and engineering attention over the past few decades. In the single-channel scenario, an estimate of the clean speech can be obtained by passing the noisy signal picked up by the microphone through a linear filter/transformation. The core issue, then, is how to find an optimal filter/transformation such that, after the filtering process, the signal-to-noise ratio (SNR) is improved but the desired speech signal is not noticeably distorted. Most of the existing optimal filters (such as the Wiener filter and subspace transformation) are formulated from the mean-square error (MSE) criterion. However, with the MSE formulation, many desired properties of the optimal noise-reduction filters such as the SNR behavior cannot be seen. In this paper, we present a new criterion based on the Pearson correlation coefficient (PCC). We show that in the context of noise reduction the squared PCC (SPCC) has many appealing properties and can be used as an optimization cost function to derive many optimal and suboptimal noise-reduction filters. The clear advantage of using the SPCC over the MSE is that the noise-reduction performance (in terms of the SNR improvement and speech distortion) of the resulting optimal filters can be easily analyzed. This shows that, as far as noise reduction is concerned, the SPCC-based cost function serves as a more natural criterion to optimize as compared to the MSE.
Year
DOI
Venue
2008
10.1109/TASL.2008.919072
IEEE Transactions on Audio, Speech & Language Processing
Keywords
Field
DocType
correlation methods,distortion,filtering theory,speech enhancement,Pearson correlation coefficient,clean speech estimation,noise-reduction filter,optimal filter,speech distortion,speech enhancement,squared PCC,Mean-square error (MSE),Pearson correlation coefficient,Wiener filter,noise reduction,speech distortion,speech enhancement
Speech enhancement,Noise reduction,Wiener filter,Speech processing,Signal processing,Linear filter,Computer science,Signal-to-noise ratio,Filter (signal processing),Speech recognition
Journal
Volume
Issue
ISSN
16
4
1558-7916
Citations 
PageRank 
References 
16
1.17
13
Authors
3
Name
Order
Citations
PageRank
Jacob Benesty11941146.01
Jingdong Chen21460128.79
Yiteng Huang3123998.26