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Direction of arrival estimation in the spherical harmonic domain using subspace pseudointensity vectors

Direction of arrival estimation in the spherical harmonic domain using subspace pseudointensity vectors
Direction of arrival estimation in the spherical harmonic domain using subspace pseudointensity vectors
Direction of arrival (DOA) estimation is a fundamental problem in acoustic signal processing. It is used in a diverse range of applications, including spatial filtering, speech dereverberation, source separation and diarization. Intensity vector-based DOA estimation is attractive, especially for spherical sensor arrays, because it is computationally efficient. Two such methods are presented that operate on a spherical harmonic decomposition of a sound field observed using a spherical microphone array. The first uses pseudointensity vectors (PIVs) and works well in acoustic environments where only one sound source is active at any time. The second uses subspace pseudointensity vectors (SSPIVs) and is targeted at environments where multiple simultaneous soures and significant levels of reverberation make the problem more challenging. Analytical models are used to quantify the effects of an interfering source, diffuse noise, and sensor noise on PIVs and SSPIVs. The accuracy of DOA estimation using PIVs and SSPIVs is compared against the state of the art in simulations including realistic reverberation and noise for single and multiple, stationary and moving sources. Finally, robust performance of the proposed methods is demonstrated by using speech recordings in a real acoustic environment.
2329-9304
178-192
Moore, Alastair
285f4de7-30ca-470a-9e65-72ab7298dfdf
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Naylor, Patrick
8c20a1a0-4507-4a0f-8324-f3075354dc52
Moore, Alastair
285f4de7-30ca-470a-9e65-72ab7298dfdf
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Naylor, Patrick
8c20a1a0-4507-4a0f-8324-f3075354dc52

Moore, Alastair, Evers, Christine and Naylor, Patrick (2017) Direction of arrival estimation in the spherical harmonic domain using subspace pseudointensity vectors. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 25 (1), 178-192. (doi:10.1109/TASLP.2016.2613280).

Record type: Article

Abstract

Direction of arrival (DOA) estimation is a fundamental problem in acoustic signal processing. It is used in a diverse range of applications, including spatial filtering, speech dereverberation, source separation and diarization. Intensity vector-based DOA estimation is attractive, especially for spherical sensor arrays, because it is computationally efficient. Two such methods are presented that operate on a spherical harmonic decomposition of a sound field observed using a spherical microphone array. The first uses pseudointensity vectors (PIVs) and works well in acoustic environments where only one sound source is active at any time. The second uses subspace pseudointensity vectors (SSPIVs) and is targeted at environments where multiple simultaneous soures and significant levels of reverberation make the problem more challenging. Analytical models are used to quantify the effects of an interfering source, diffuse noise, and sensor noise on PIVs and SSPIVs. The accuracy of DOA estimation using PIVs and SSPIVs is compared against the state of the art in simulations including realistic reverberation and noise for single and multiple, stationary and moving sources. Finally, robust performance of the proposed methods is demonstrated by using speech recordings in a real acoustic environment.

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More information

Accepted/In Press date: 31 August 2016
e-pub ahead of print date: 26 September 2016
Published date: January 2017

Identifiers

Local EPrints ID: 437939
URI: http://eprints.soton.ac.uk/id/eprint/437939
ISSN: 2329-9304
PURE UUID: 99de2e34-c534-42de-af3c-155cf69d95f1
ORCID for Christine Evers: ORCID iD orcid.org/0000-0003-0757-5504

Catalogue record

Date deposited: 24 Feb 2020 17:31
Last modified: 07 Oct 2020 02:27

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