Single-channel Late Reverberation Power Spectral Density Estimation Using Denoising Autoencoders

Ina Kodrasi and Hervé Bourlard

Abstract:

In order to suppress the late reverberation in the spectral domain, many single-channel dereverberation techniques rely on an estimate of the late reverberation power spectral density (PSD). In this paper, we propose a novel approach to late reverberation PSD estimation using a denoising autoencoder (DA), which is trained to learn a mapping from the microphone signal PSD to the late reverberation PSD. Simulation results show that the proposed approach yields a high PSD estimation accuracy and generalizes well to unseen data. Furthermore, simulation results show that the proposed DA-based PSD estimate yields a higher PSD estimation accuracy and a similar dereverberation performance than a state-of-the-art statistical PSD estimate, which additionally also requires knowledge of the reverberation time.

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Cite as: Kodrasi, I., Bourlard, H. (2018) Single-channel Late Reverberation Power Spectral Density Estimation Using Denoising Autoencoders. Proc. Interspeech 2018, 1319-1323, DOI: 10.21437/Interspeech.2018-1660.

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BiBTeX Entry:

@inproceedings{Kodrasi2018,
author={Ina Kodrasi and Hervé Bourlard},
title={Single-channel Late Reverberation Power Spectral Density Estimation Using Denoising Autoencoders},
year=2018,
booktitle={Proc. Interspeech 2018},
pages={1319--1323},
doi={10.21437/Interspeech.2018-1660},
url={http://dx.doi.org/10.21437/Interspeech.2018-1660} }