Joint Estimation of Reverberation Time and Direct-to-Reverberation Ratio from Speech using Auditory-Inspired Features

Blind estimation of acoustic room parameters such as the reverberation time T60 and the direct-to-reverberation ratio (DRR) is still a challenging task, especially in case of blind estimation from reverberant speech signals. In this work, a novel approach is proposed for joint estimation of T60 and DRR from wideband speech in noisy conditions. 2D Gabor filters arranged in a filterbank are exploited for extracting features, which are then used as input to a multi-layer perceptron (MLP). The MLP output neurons correspond to specific pairs of (T60,DRR) estimates; the output is integrated over time, and a simple decision rule results in our estimate. The approach is applied to single-microphone fullband speech signals provided by the Acoustic Characterization of Environments (ACE) Challenge. Our approach outperforms the baseline systems with median errors of close-to-zero and -1.5 dB for the T60 and DRR estimates, respectively, while the calculation of estimates is 5.8 times faster compared to the baseline.