Room adaptive conditioning method for sound event classification in reverberant environments

TL;DR

This paper introduces a room adaptive conditioning method for sound event classification that leverages room impulse response information to improve robustness against reverberation in indoor environments.

Contribution

The proposed method effectively reduces reverberation-induced performance degradation by incorporating room impulse response data, even when only approximate room type information is available.

Findings

Significantly improved classification robustness in reverberant environments.

Effective even with inferred room type rather than exact room impulse response.

Potential for real-world application due to robustness with approximate room data.

Abstract

Ensuring performance robustness for a variety of situations that can occur in real-world environments is one of the challenging tasks in sound event classification. One of the unpredictable and detrimental factors in performance, especially in indoor environments, is reverberation. To alleviate this problem, we propose a conditioning method that provides room impulse response (RIR) information to help the network become less sensitive to environmental information and focus on classifying the desired sound. Experimental results show that the proposed method successfully reduced performance degradation caused by the reverberation of the room. In particular, our proposed method works even with similar RIR that can be inferred from the room type rather than the exact one, which has the advantage of potentially being used in real-world applications.