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Harmonic minimum mean squared error filters for multichannel speech enhancement

Jensen, Jesper Rindom; Christensen, Mads Groesboll and Jakobsson, Andreas LU (2017) 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings p.501-505
Abstract

Many state-of-the-art multichannel speech enhancement methods rely on second-order statistics of the desired speech signal, the noise signal, or both. Estimation of those are difficult in practice, resulting in a practical performance that is typically much lower than their potential theoretical performance. We propose two multichannel enhancement techniques that instead rely on a model for voiced speech. That is, the proposed methods are driven by the signals' fundamental frequencies, which may be accurately estimated even in noisy scenarios. The first method is designed independently of the microphone array geometry and source position, whereas these are utilized in the second approach. Thereby, we can investigate when to exploit such... (More)

Many state-of-the-art multichannel speech enhancement methods rely on second-order statistics of the desired speech signal, the noise signal, or both. Estimation of those are difficult in practice, resulting in a practical performance that is typically much lower than their potential theoretical performance. We propose two multichannel enhancement techniques that instead rely on a model for voiced speech. That is, the proposed methods are driven by the signals' fundamental frequencies, which may be accurately estimated even in noisy scenarios. The first method is designed independently of the microphone array geometry and source position, whereas these are utilized in the second approach. Thereby, we can investigate when to exploit such information in the case of localization errors and violations of the spatial assumptions. Numerical results show that the proposed method is able to outperform competing methods in terms of both output SNRs and PESQ scores.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
DOA mismatch, harmonic filters, MMSE filtering, multichannel speech enhancement, voiced speech
in
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
pages
5 pages
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
external identifiers
  • scopus:85023776452
DOI
10.1109/ICASSP.2017.7952206
language
English
LU publication?
yes
id
e030642d-a2e2-4cfe-a5a0-cd7b090200b3
date added to LUP
2017-07-27 13:59:07
date last changed
2017-08-07 10:20:21
@inproceedings{e030642d-a2e2-4cfe-a5a0-cd7b090200b3,
  abstract     = {<p>Many state-of-the-art multichannel speech enhancement methods rely on second-order statistics of the desired speech signal, the noise signal, or both. Estimation of those are difficult in practice, resulting in a practical performance that is typically much lower than their potential theoretical performance. We propose two multichannel enhancement techniques that instead rely on a model for voiced speech. That is, the proposed methods are driven by the signals' fundamental frequencies, which may be accurately estimated even in noisy scenarios. The first method is designed independently of the microphone array geometry and source position, whereas these are utilized in the second approach. Thereby, we can investigate when to exploit such information in the case of localization errors and violations of the spatial assumptions. Numerical results show that the proposed method is able to outperform competing methods in terms of both output SNRs and PESQ scores.</p>},
  author       = {Jensen, Jesper Rindom and Christensen, Mads Groesboll and Jakobsson, Andreas},
  booktitle    = {2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings},
  keyword      = {DOA mismatch,harmonic filters,MMSE filtering,multichannel speech enhancement,voiced speech},
  language     = {eng},
  month        = {06},
  pages        = {501--505},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Harmonic minimum mean squared error filters for multichannel speech enhancement},
  url          = {http://dx.doi.org/10.1109/ICASSP.2017.7952206},
  year         = {2017},
}