Sector-Based Encoding and Data Compression of Virtual Acoustic Scattering

In order to produce high fidelity representations of sound-fields in spatial audio applications, the acoustical nuances occurring within physicals spaces must be included. This includes the effects of scattering from the boundary surfaces of enclosed spaces, as well as the scattering from finite bodies within spaces. Recently, a method has been proposed to encode the properties of arbitrary scattering geometries into the spherical harmonic domain in the form of a scattering expansion matrix. The following study extends this previous method by providing a sector-based approach. This approach allows for the encoding of selective regions of the scattering geometry, such as the upper hemisphere. Furthermore, a second optimization is also proposed to compress and reduce the memory storage of the scattering expansion matrix. Two methods for compression are proposed, with one of them providing minimal loss of fidelity by means of the Singular Value Decomposition.

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Compression, Scattering, Virtual Acoustics

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10.23919/EUSIPCO55093.2022.9909728

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Gonzalez, R, Hold, C, Lokki, T & Politis, A 2022, Sector-Based Encoding and Data Compression of Virtual Acoustic Scattering. in 2022 30th European Signal Processing Conference (EUSIPCO). European Signal Processing Conference, IEEE, pp. 339-343, European Signal Processing Conference, Belgrade, Serbia, 29/08/2022. https://doi.org/10.23919/EUSIPCO55093.2022.9909728

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https://urn.fi/URN:NBN:fi:aalto-202211236550

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[article-cris] Sähkötekniikan korkeakoulu / ELEC

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Sector-Based Encoding and Data Compression of Virtual Acoustic Scattering

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