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ORIGINAL RESEARCH article
Front. Signal Process.
Sec. Audio and Acoustic Signal Processing
Volume 4 - 2024 |
doi: 10.3389/frsip.2024.1426082
State-Space Estimation of Spatially Dynamic Room Impulse Responses using a Room Acoustic Model-based Prior
Provisionally accepted- 1 Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, Faculty of Engineering Sciences, KU Leuven, Leuven, Belgium
- 2 Institute of Sound Recording, University of Surrey, Guildford, Surrey, United Kingdom
The estimation of room impulse responses (RIRs) between static loudspeaker and microphone locations can be done using a number of well-established measurement and inference procedures. While these procedures assume a time-invariant acoustic system, time variations need to be considered for the case of spatially dynamic scenarios where loudspeakers and microphones are subject to movement. If the RIR is modeled using image sources, then movement implies that the distance to each image source varies over time, making the estimation of the spatially dynamic RIR particularly challenging. In this paper, we propose a procedure to estimate the early part of the spatially dynamic RIR between a stationary source and a microphone moving on a linear trajectory at constant velocity. The procedure is built upon a state-space model, where the state to be estimated represents the early RIR, the observation corresponds to a microphone recording in a spatially dynamic scenario, and time-varying distances to the image sources are incorporated into the state transition matrix obtained from static RIRs at the start and end point of the trajectory. The performance of the proposed approach is evaluated against state-of-the-art RIR interpolation and state-space estimation methods using simulations, demonstrating the potential of the proposed state-space model.
Keywords: state-space models, transition matrices, Acoustic RIR interpolation, Time-varying systems, Dynamic Time Warping
Received: 30 Apr 2024; Accepted: 01 Aug 2024.
Copyright: © 2024 MacWilliam, Dietzen, Ali and Van Waterschoot. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Kathleen MacWilliam, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, Faculty of Engineering Sciences, KU Leuven, Leuven, Belgium
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