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Sensitivity of Room Impulse Responses in Changing Acoustic Environment

Karolina Prawda

TL;DR

This work addresses the variability of room impulse responses (RIRs) in time-varying environments and its impact on systems like echo cancellation and active acoustics. It introduces a coherence-based framework that combines short-time coherence with a single-parameter sensitivity descriptor $\\Gamma$ to quantify and distinguish changes in absorption distribution, atmospheric conditions, and human presence, explicitly modeling measurements as $x(t,f)=h(t,f)+u(t,f)$. The study demonstrates that absorption distribution changes cause rapid coherence loss and sizable $\\Gamma$, while atmospheric variations have much smaller effects, and human presence induces frequency-dependent coherence changes with elevated $\\Gamma$, especially when occlusion occurs. The methodology provides a robust, frequency-aware tool for monitoring acoustic environment changes, with practical implications for calibration, navigation, and tracking in robotics and audio sensing contexts.

Abstract

Changes in room acoustics, such as modifications to surface absorption or the insertion of a scattering object, significantly impact measured room impulse responses (RIRs). These changes can affect the performance of systems used in echo cancellation and active acoustics and support tasks such as navigation and object tracking. Recognizing and quantifying such changes is, therefore, critical for advancing technologies based on room acoustics. This study introduces a method for analyzing acoustic environment changes by evaluating the similarity of consecutively recorded RIRs. Short-time coherence is employed to characterize modifications, including changes in wall absorption or the presence of a moving person in the room. A sensitivity rating is further used to quantify the magnitude of these changes. The results clearly differentiate between types of modifications -- atmospheric variation, changes in absorption, and human presence. The methods described provide a novel approach to analyzing and interpreting room acoustics, emphasizing RIR similarity and extracting information from temporal and spectral signal properties.

Sensitivity of Room Impulse Responses in Changing Acoustic Environment

TL;DR

This work addresses the variability of room impulse responses (RIRs) in time-varying environments and its impact on systems like echo cancellation and active acoustics. It introduces a coherence-based framework that combines short-time coherence with a single-parameter sensitivity descriptor to quantify and distinguish changes in absorption distribution, atmospheric conditions, and human presence, explicitly modeling measurements as . The study demonstrates that absorption distribution changes cause rapid coherence loss and sizable , while atmospheric variations have much smaller effects, and human presence induces frequency-dependent coherence changes with elevated , especially when occlusion occurs. The methodology provides a robust, frequency-aware tool for monitoring acoustic environment changes, with practical implications for calibration, navigation, and tracking in robotics and audio sensing contexts.

Abstract

Changes in room acoustics, such as modifications to surface absorption or the insertion of a scattering object, significantly impact measured room impulse responses (RIRs). These changes can affect the performance of systems used in echo cancellation and active acoustics and support tasks such as navigation and object tracking. Recognizing and quantifying such changes is, therefore, critical for advancing technologies based on room acoustics. This study introduces a method for analyzing acoustic environment changes by evaluating the similarity of consecutively recorded RIRs. Short-time coherence is employed to characterize modifications, including changes in wall absorption or the presence of a moving person in the room. A sensitivity rating is further used to quantify the magnitude of these changes. The results clearly differentiate between types of modifications -- atmospheric variation, changes in absorption, and human presence. The methods described provide a novel approach to analyzing and interpreting room acoustics, emphasizing RIR similarity and extracting information from temporal and spectral signal properties.
Paper Structure (7 sections, 6 equations, 5 figures)

This paper contains 7 sections, 6 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Methodology
  3. Short-time coherence
  4. Sensitivity rating
  5. Change in surface absorption
  6. Human presence in the room
  7. Conclusion

Figures (5)

  • Figure 1: Short-time coherence between repeated RIRs from Arni database. The coherence loss resulting from time-variant measurement environment is more similar to the expected coherence curve obtained through \ref{['eq:snr']} than when the absorption distribution in the room has changed.
  • Figure 2: Sensitivity of RIRs from Arni database. Grey dots show single values of $\Gamma$ for each RIR pair, whilst black dots represent median values for each analyzed condition of $A$. The red dots are the sensitivity values for when the change in RIRs are caused only by atmospheric variation. Note that the top half of the Y-axis is linear, while the bottom half is logarithmic for enhanced readability of the results.
  • Figure 3: (Top) Layout of the analyzed room from the SoundCam database. The circled microphone position is occluded in one of the considered configurations, when the human is in the circled position. (Bottom) A close-up of first 10 ms of two RIRs measured with the circled microphone: (black) direct path nonoccluded, (red) direct path occluded.
  • Figure 4: (Top) Short-time coherence curves for occluded (blue) and nonoccluded (red) microphones compared to the median of all receivers for the 19-kHz band. (Bottom) Corresponding $\Gamma$ for frequency bands between 1--19 kHz.
  • Figure 5: (Top) Time-frequency short-time coherence for two RIRs from SoundCam dataset wang2023soundcam. (Bottom) Corresponding frequency-dependent sensitivity $\Gamma$.