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Early reflections pose a major challenge for parametric virtual acoustics systems. Reflections within a spatial impulse response (IR) must be compactly encoded to allow interactive rendering within limited resources. Encoding individual echoes is far too expensive, while the exponentially-decaying-noise model only befits late reverberation. We propose a novel statistical formulation for compactly encoding salient early reflection properties with six interpretable, orthogonal parameters capturing the loudness, echo density, temporal mean & spread, and directional mean & spread of energy arrival within the IR. Further, we propose a robust approach for additive separation of the impulse response into a coherent (specular) and incoherent (diffuse) component, rather than partitioning at a mixing time. We discuss initial results on a variety of measured IRs in indoor and outdoor spaces suggesting that salient acoustical variations across scenes are captured by the proposed parameters.
Author (s): Raghuvanshi, Nikunj;
Allen, Andrew;
Snyder, John;
Chemistruck, Michael;
Cross, Noel;
Walker, Christopher;
Willette, Aaron;
McWilliams, Nathan;
Myrbeck, Shane;
Affiliation:
Microsoft, Redmond, WA, USA; Arup, Los Angeles, CA, USA
(See document for exact affiliation information.)
Publication Date:
2022-08-06
Session subject:
Paper
DOI:
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Raghuvanshi, Nikunj; Allen, Andrew; Snyder, John; Chemistruck, Michael; Cross, Noel; Walker, Christopher; Willette, Aaron; McWilliams, Nathan; Myrbeck, Shane; 2022; Compact statistical encoding of early reflections for auditory virtual reality [PDF]; Microsoft, Redmond, WA, USA; Arup, Los Angeles, CA, USA; Paper 36; Available from: https://aes.org/publications/elibrary-page/?id=21866
Raghuvanshi, Nikunj; Allen, Andrew; Snyder, John; Chemistruck, Michael; Cross, Noel; Walker, Christopher; Willette, Aaron; McWilliams, Nathan; Myrbeck, Shane; Compact statistical encoding of early reflections for auditory virtual reality [PDF]; Microsoft, Redmond, WA, USA; Arup, Los Angeles, CA, USA; Paper 36; 2022 Available: https://aes.org/publications/elibrary-page/?id=21866
@inproceedings{Raghuvanshi2022compact,
title={{Compact statistical encoding of early reflections for auditory virtual reality}},
author={Raghuvanshi, Nikunj and Allen, Andrew and Snyder, John and Chemistruck, Michael and Cross, Noel and Walker, Christopher and Willette, Aaron and McWilliams, Nathan and Myrbeck, Shane},
year={2022},
month={aug},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 36; AES Conference: AES 2022 International Audio for Virtual and Augmented Reality Conference; August 2022},
number={36},
organization={AES},
}
TY – paper
TI – Compact statistical encoding of early reflections for auditory virtual reality
AU – Raghuvanshi, Nikunj
AU – Allen, Andrew
AU – Snyder, John
AU – Chemistruck, Michael
AU – Cross, Noel
AU – Walker, Christopher
AU – Willette, Aaron
AU – McWilliams, Nathan
AU – Myrbeck, Shane
PY – 2022
JO – Journal of the Audio Engineering Society
VL – 36
Y1 – August 2022
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