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Speech dereverberation performance of a polynomial-EVD subspace approach

Speech dereverberation performance of a polynomial-EVD subspace approach
Speech dereverberation performance of a polynomial-EVD subspace approach
The degradation of speech arising from additive background noise and reverberation affects the performance of important speech applications such as telecommunications, hearing aids, voice-controlled systems and robot audition. In this work, we focus on dereverberation. It is shown that the parameterized polynomial matrix eigenvalue decomposition (PEVD)-based speech enhancement algorithm exploits the lack of correlation between speech and the late reflections to enhance the speech component associated with the direct path and early reflections. The algorithm’s performance is evaluated using simulations involving measured acoustic impulse responses and noise from the ACE corpus. The simulations and informal listening examples have indicated that the PEVD-based algorithm performs dereverberation over a range of SNRs without introducing any noticeable processing artefacts.
Neo, Vincent W.
7ec5cc5f-8248-40ec-8864-b31335d4ddf2
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Naylor, Patrick A.
13079486-664a-414c-a1a2-01a30bf0997b
Neo, Vincent W.
7ec5cc5f-8248-40ec-8864-b31335d4ddf2
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Naylor, Patrick A.
13079486-664a-414c-a1a2-01a30bf0997b

Neo, Vincent W., Evers, Christine and Naylor, Patrick A. (2020) Speech dereverberation performance of a polynomial-EVD subspace approach. European Signal Processing Conference, Netherlands. 18 - 22 Jan 2021. 5 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

The degradation of speech arising from additive background noise and reverberation affects the performance of important speech applications such as telecommunications, hearing aids, voice-controlled systems and robot audition. In this work, we focus on dereverberation. It is shown that the parameterized polynomial matrix eigenvalue decomposition (PEVD)-based speech enhancement algorithm exploits the lack of correlation between speech and the late reflections to enhance the speech component associated with the direct path and early reflections. The algorithm’s performance is evaluated using simulations involving measured acoustic impulse responses and noise from the ACE corpus. The simulations and informal listening examples have indicated that the PEVD-based algorithm performs dereverberation over a range of SNRs without introducing any noticeable processing artefacts.

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neo2020 - Accepted Manuscript
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More information

Accepted/In Press date: 29 May 2020
Venue - Dates: European Signal Processing Conference, Netherlands, 2021-01-18 - 2021-01-22

Identifiers

Local EPrints ID: 441500
URI: http://eprints.soton.ac.uk/id/eprint/441500
PURE UUID: eea60f79-480f-4050-aedd-1a64a3fa1d00
ORCID for Christine Evers: ORCID iD orcid.org/0000-0003-0757-5504

Catalogue record

Date deposited: 16 Jun 2020 16:31
Last modified: 26 Jun 2020 00:46

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Contributors

Author: Vincent W. Neo
Author: Christine Evers ORCID iD
Author: Patrick A. Naylor

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