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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
This article is part of the Research Topic Audio and Acoustics of Movement View all 5 articles

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 final, formatted version of the article will be published soon.

    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

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.