Time domain reconstruction of spatial sound fields using compressed sensing

Andrew Wabnitz; Nicolas Epain; André Van Schaik; Craig Jin

doi:10.1109/ICASSP.2011.5946441

Time domain reconstruction of spatial sound fields using compressed sensing

Andrew Wabnitz
, Nicolas Epain
, André Van Schaik
, Craig Jin

MARCS Institute for Brain, Behaviour & Development

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

25 Citations (Scopus)

Abstract

A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.

Original language	English
Title of host publication	Proceedings of the 36th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 22-27 May 2011, Prague, Czech Republic
Publisher	IEEE
Pages	465-468
Number of pages	4
ISBN (Print)	9781457705397
DOIs	https://doi.org/10.1109/ICASSP.2011.5946441
Publication status	Published - 2011
Event	ICASSP (Conference) - Duration: 22 May 2011 → …

Conference

Conference	ICASSP (Conference)
Period	22/05/11 → …

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10.1109/ICASSP.2011.5946441

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@inproceedings{52c3bba60d8548d09fbd6f3227e93bea,

title = "Time domain reconstruction of spatial sound fields using compressed sensing",

abstract = "A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.",

author = "Andrew Wabnitz and Nicolas Epain and \{Van Schaik\}, Andr{\'e} and Craig Jin",

year = "2011",

doi = "10.1109/ICASSP.2011.5946441",

language = "English",

isbn = "9781457705397",

pages = "465--468",

booktitle = "Proceedings of the 36th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 22-27 May 2011, Prague, Czech Republic",

publisher = "IEEE",

note = "ICASSP (Conference) ; Conference date: 22-05-2011",

}

Wabnitz, A, Epain, N, Van Schaik, A & Jin, C 2011, Time domain reconstruction of spatial sound fields using compressed sensing. in Proceedings of the 36th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 22-27 May 2011, Prague, Czech Republic. IEEE, pp. 465-468, ICASSP (Conference), 22/05/11. https://doi.org/10.1109/ICASSP.2011.5946441

Time domain reconstruction of spatial sound fields using compressed sensing. / Wabnitz, Andrew; Epain, Nicolas; Van Schaik, André et al.
Proceedings of the 36th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 22-27 May 2011, Prague, Czech Republic. IEEE, 2011. p. 465-468.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - Time domain reconstruction of spatial sound fields using compressed sensing

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AU - Epain, Nicolas

AU - Van Schaik, André

AU - Jin, Craig

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N2 - A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.

AB - A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.

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DO - 10.1109/ICASSP.2011.5946441

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SN - 9781457705397

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BT - Proceedings of the 36th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 22-27 May 2011, Prague, Czech Republic

PB - IEEE

T2 - ICASSP (Conference)

Y2 - 22 May 2011

ER -

Time domain reconstruction of spatial sound fields using compressed sensing

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