Reverberation time estimation on the ACE corpus using the SDD method

TL;DR

This paper evaluates a reverberation time estimation algorithm on real recorded room impulse responses from the ACE corpus, demonstrating its effectiveness beyond simulated environments.

Contribution

It extends previous work by testing the T60 estimation algorithm on real room data, showing comparable performance to simulated data results.

Findings

Achieved similar T60 estimation accuracy on real and simulated data.

Validated the algorithm's applicability to real-world acoustic environments.

Demonstrated robustness of the SDD method in practical scenarios.

Abstract

Reverberation Time (T60) is an important measure for characterizing the properties of a room. The author's T60 estimation algorithm was previously tested on simulated data where the noise is artificially added to the speech after convolution with a impulse responses simulated using the image method. We test the algorithm on speech convolved with real recorded impulse responses and noise from the same rooms from the Acoustic Characterization of Environments (ACE) corpus and achieve results comparable results to those using simulated data.