The University of Southampton
University of Southampton Institutional Repository

Sparse sound field representation using complex orthogonal matching pursuit

Sparse sound field representation using complex orthogonal matching pursuit
Sparse sound field representation using complex orthogonal matching pursuit
Spatial audio reproduction and translation for virtual, augmented, and extended reality applications require an efficient representation of the recorded sound fields. In this paper, we investigate the possible sparse representations of the sound field recorded by multiple microphones in reverberant environments. We combine the Complex Orthogonal Matching Pursuit (COMP) algorithm with the concept of distributed virtual sound sources to propose a sparse sound field representation. The technique uses recordings from a grid of microphones and transforms them into a sparse representation featuring a selected set of active virtual sources. Using simulation, we evaluate the proposed COMP approach with LASSO and IRLS methods in a reverberant room of regular size with a ceiling-mounted microphone array.
1336-1340
IEEE
Xu, Shaoheng
b4a43ded-bc50-44c8-aaef-2a28a9492465
Zhang, Jihui Aimee
6c5536d1-5066-437b-987c-c2307021709d
Abhayapala, Thushara D.
5de91ea7-d2b9-41d3-b309-e1023ab5bdeb
Bastine, Amy
c16171c0-97e7-4745-809d-3a4960a0fe72
Lai, Wei-Ting
dcfaa935-74a0-460b-8917-e8077ed5717d
Samarasinghe, Prasanga N.
a82cb814-1e2f-4499-84ca-618be978db62
Xu, Shaoheng
b4a43ded-bc50-44c8-aaef-2a28a9492465
Zhang, Jihui Aimee
6c5536d1-5066-437b-987c-c2307021709d
Abhayapala, Thushara D.
5de91ea7-d2b9-41d3-b309-e1023ab5bdeb
Bastine, Amy
c16171c0-97e7-4745-809d-3a4960a0fe72
Lai, Wei-Ting
dcfaa935-74a0-460b-8917-e8077ed5717d
Samarasinghe, Prasanga N.
a82cb814-1e2f-4499-84ca-618be978db62

Xu, Shaoheng, Zhang, Jihui Aimee, Abhayapala, Thushara D., Bastine, Amy, Lai, Wei-Ting and Samarasinghe, Prasanga N. (2024) Sparse sound field representation using complex orthogonal matching pursuit. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. pp. 1336-1340 . (doi:10.1109/icassp48485.2024.10445940).

Record type: Conference or Workshop Item (Paper)

Abstract

Spatial audio reproduction and translation for virtual, augmented, and extended reality applications require an efficient representation of the recorded sound fields. In this paper, we investigate the possible sparse representations of the sound field recorded by multiple microphones in reverberant environments. We combine the Complex Orthogonal Matching Pursuit (COMP) algorithm with the concept of distributed virtual sound sources to propose a sparse sound field representation. The technique uses recordings from a grid of microphones and transforms them into a sparse representation featuring a selected set of active virtual sources. Using simulation, we evaluate the proposed COMP approach with LASSO and IRLS methods in a reverberant room of regular size with a ceiling-mounted microphone array.

This record has no associated files available for download.

More information

Published date: 18 March 2024
Venue - Dates: 2024 IEEE International Conference on Acoustics, Speech and Signal Processing, , Seoul, Korea, Republic of, 2024-04-14 - 2024-04-19

Identifiers

Local EPrints ID: 492904
URI: http://eprints.soton.ac.uk/id/eprint/492904
PURE UUID: 55b8e405-8a6a-4931-82a0-cc7355c62ebe
ORCID for Jihui Aimee Zhang: ORCID iD orcid.org/0000-0001-6817-139X

Catalogue record

Date deposited: 20 Aug 2024 16:32
Last modified: 22 Aug 2024 02:07

Export record

Altmetrics

Contributors

Author: Shaoheng Xu
Author: Jihui Aimee Zhang ORCID iD
Author: Thushara D. Abhayapala
Author: Amy Bastine
Author: Wei-Ting Lai
Author: Prasanga N. Samarasinghe

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×