Year: 2024
Type: article
Abstract: Room impulse responses (RIRs) are used in several applications, such as augmented reality and virtual reality. These applications require a large number of RIRs to be convolved with audio, under strict latency constraints. In this paper, we consider the compression of RIRs, in conjunction with fast time-domain convolution. We consider three different methods of RIR approximation for the purpose of RIR compression and compare them to state-of-the-art compression. The methods are evaluated using several standard objective quality measures, both channel-based and signal-based. We also propose a novel low-rank-based algorithm for fast time-domain convolution and show how the convolution can be carried out without the need to decompress the RIR. Numerical simulations are performed using RIRs of different lengths, recorded in three different rooms. It is shown that compression using low-rank approximation is a very compelling option to the state-of-the-art Opus compression, as it performs as well or better than on all but one considered measure, with the added benefit of being amenable to fast time-domain convolution. Supplementary information: The online version contains supplementary material available at 10.1186/s13636-024-00363-5.
Institutions: KU Leuven, Aalto University
Language: English
Topic: Speech and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,890
Awards: G1359211980, G434337789, Innovative research and valorization of plainchant through digital technology (THE SOUND OF MUSIC)., G6398803747, Understanding Musical Co-Creation for Social-Emotional Development in Adults with Autism Spectrum Disorder (UNMUTED), The Spatial Dynamics of Room Acoustics
OpenAlex ID: W4402513016