Author ORCID Identifier

https://orcid.org/0000-0002-3912-1470

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Electrical and electronic engineering

Publication Details

@article{deFrein22Soft, author={Bagchi, Swarnadeep and de Fr\'{e}in, Ruair\'{i}}, journal={2022 33rd Irish Signals and Systems Conference (ISSC)}, title={Soft-Mask De-Mixing for Anechoic Mixtures}, year={2022}, volume={}, number={}, pages={1-6}, doi={10.1109/ISSC55427.2022.9826179}, url = {https://ieeexplore.ieee.org/abstract/document/9826179} }

Published version

https://ieeexplore.ieee.org/document/9826179

Abstract

This paper extends a computationally efficient, soft-mask based source separation (SS) technique called Redress, to anechoic mixing scenarios. SS methods are an integral part of hearing aid research. We call the resulting method D-Redress. In its original form, Redress was intended for instantaneous mixing scenarios. Numerical evaluations demonstrate that soft-mask based techniques reduce the level of artifacts in the separated speech. Monte Carlo trials on 1000 real speech mixtures demonstrate that the D-Redress successfully extends Redress in terms of Overall-Perceptual (OPS), Target-Perceptual (TPS) scores and Human-Ear Intelligibility (HEI).

DOI

https://doi.org/10.1109/ISSC55427.2022.9826179

Funder

SFI

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