Paper Info
Title
Investigation of a parametric gain approach to single-channel speech enhancement
Abstract
This paper investigates a parametric gain approach to single-channel noise reduction in the frequency domain. In comparison with the traditional parametric Wiener gain, the major novelty of this presented approach is that the parametric gain is formulated to estimate the noise by using the mean-squared error (MSE) between the noise and the noise estimate. The enhanced signal is then obtained by subtracting the noise estimate from the noisy observation signal. We show that this new method is more practical to implement and can produce better noise reduction performance as compared to the traditional parametric Wiener filtering techniques if the order of the parametric gain is not equal to 1. If the order is 1, the parametric gain is similar to the traditional Wiener gain. Simulation results are presented to illustrate the properties of this new approach.
Year
DOI
Venue
2015
10.1109/ICASSP.2015.7177961
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Keywords
Field
DocType
Noise reduction,speech enhancement,single-channel,frequency domain,Wiener gain,parametric gain
Noise measurement,Computer science,Noise figure,Artificial intelligence,Process gain,Wiener filter,Pattern recognition,Wiener deconvolution,Algorithm,Speech recognition,Parametric statistics,Noise spectral density,Gradient noise
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
6
3
Name
Order
Citations
PageRank
Gongping Huang17613.39
Jingdong Chen21460128.79
Jacob Benesty31386136.42