Classical single-channel speech enhancement algorithms have two convenient properties: they require pre-learning the noise model but not the speech model, and they work online. How- ever, they often have difficulties in dealing with non-stationary noise sources. Source separation algorithms based on non- negative spectrogram decompositions are capable of dealing with non-stationary noise, but do not possess the aforemen- tioned properties. In this paper we present a novel algorithm that combines the advantages of both classical algorithms and nonnegative spectrogram decomposition algorithms. Experi- ments show that it significantly outperforms four categories of classical algorithms in non-stationary noise environments.
Cite as: Duan, Z., Mysore, G.J., Smaragdis, P. (2012) Speech enhancement by online non-negative spectrogram decomposition in nonstationary noise environments. Proc. Interspeech 2012, 595-598, doi: 10.21437/Interspeech.2012-181
@inproceedings{duan12_interspeech,
author={Zhiyao Duan and Gautham J. Mysore and Paris Smaragdis},
title={{Speech enhancement by online non-negative spectrogram decomposition in nonstationary noise environments}},
year=2012,
booktitle={Proc. Interspeech 2012},
pages={595--598},
doi={10.21437/Interspeech.2012-181}
}