Abstract
A novelmethod for blind estimation of the reverberation time (RT60) is proposed based on applying spectro-temporal modulation filters to time-frequency representations. 2D-Gabor filters arranged in a filterbank enable an analysis of the properties of temporal, spectral, and spectro-temporal filtering for this task. Features are used as input to a multi-layer perceptron (MLP) classifier combined with a simple decision rule that attributes a specific RT60 to a given utterance and allows to assess the reliability of the approach for different resolutions of RT60 classification. While the filter set including temporal, spectral, and spectro-temporal filters already outperforms an MFCC baseline, the error rates are further reduced when relying on diagonal spectro-temporal filters alone. The average error rate is 1.9% for the best feature set, which corresponds to a relative reduction of 58.3% compared to the MFCC baseline for RT60s in 0.1 s resolution.