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Polynomial matrix eigenvalue decomposition of spherical harmonics for speech enhancement

Polynomial matrix eigenvalue decomposition of spherical harmonics for speech enhancement
Polynomial matrix eigenvalue decomposition of spherical harmonics for speech enhancement
Speech enhancement algorithms using polynomialmatrixeigenvalue decomposition (PEVD) have been shown to be effective for noisy and reverberant speech. However, these algorithms do not scale well in complexity with the number of channels used in the processing. For a spherical microphone array sampling an order-limited sound field, the spherical harmonics provide a compact representation of the microphone signals in the form of eigenbeams. We propose a PEVD algorithm that uses only the lower dimension eigenbeams for speech enhancement at a significantly lower computation cost. The proposed algorithm is shown to significantly reduce complexity while maintaining full performance. Informal listening examples have also indicated that the processing does not introduce any noticeable artefacts.
IEEE
Neo, Vincent W.
7ec5cc5f-8248-40ec-8864-b31335d4ddf2
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Naylor, Patrick
8c20a1a0-4507-4a0f-8324-f3075354dc52
Neo, Vincent W.
7ec5cc5f-8248-40ec-8864-b31335d4ddf2
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Naylor, Patrick
8c20a1a0-4507-4a0f-8324-f3075354dc52

Neo, Vincent W., Evers, Christine and Naylor, Patrick (2021) Polynomial matrix eigenvalue decomposition of spherical harmonics for speech enhancement. In IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP). IEEE. 5 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Speech enhancement algorithms using polynomialmatrixeigenvalue decomposition (PEVD) have been shown to be effective for noisy and reverberant speech. However, these algorithms do not scale well in complexity with the number of channels used in the processing. For a spherical microphone array sampling an order-limited sound field, the spherical harmonics provide a compact representation of the microphone signals in the form of eigenbeams. We propose a PEVD algorithm that uses only the lower dimension eigenbeams for speech enhancement at a significantly lower computation cost. The proposed algorithm is shown to significantly reduce complexity while maintaining full performance. Informal listening examples have also indicated that the processing does not introduce any noticeable artefacts.

Text
[ICASSP2021]_PEVD_of_Spherical_Harmonics_for_Speech_Enhancement_final - Accepted Manuscript
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Accepted/In Press date: 30 January 2021

Identifiers

Local EPrints ID: 447988
URI: http://eprints.soton.ac.uk/id/eprint/447988
PURE UUID: 4cee3906-1cf3-4c92-8e97-0128a13a7b17
ORCID for Christine Evers: ORCID iD orcid.org/0000-0003-0757-5504

Catalogue record

Date deposited: 29 Mar 2021 16:38
Last modified: 30 Mar 2021 02:04

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Contributors

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

University divisions

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