A Study of Noise PSD Estimators for Single Channel Speech Enhancement

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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.
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Details

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.
Original languageEnglish
JournalI E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN1520-6149
Publication statusPublished - 2018
Publication categoryResearch
Peer-reviewedYes

    Research areas

  • speech enhancement, noise PSD estimation, autoregressive models
ID: 281449698