ICASSP 2018accepted0 citations
A Study of Noise PSD Estimators for Single Channel Speech Enhancement
Mathew Shaji Kavalekalam, Jesper Kjær Nielsen, Mads Græsbøll Christensen, Jesper Bünsow Boldt
Abstract
The estimation of the noise power spectral density (PSD) forms a critical component of several existing single channel speech enhancement systems. In this paper, we evaluate one new and some of the existing and commonly used noise PSD estimation algorithms in terms of the spectral estimation accuracy and the enhancement performance for different commonly encountered background noises, which are stationary and non-stationary in nature. The evaluated algorithms include the Minimum Statistics, MMSE, IMCRA methods and a new model-based method.
BibTeX
@inproceedings{icassp2018_astudyofnoisepsd,
title = {A Study of Noise PSD Estimators for Single Channel Speech Enhancement},
author = {Mathew Shaji Kavalekalam and Jesper Kjær Nielsen and Mads Græsbøll Christensen and Jesper Bünsow Boldt},
booktitle = {ICASSP 2018},
year = {2018}
}