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Reverberation, especially in large rooms, severely degrades speechrecognition performance and speech intelligibility. Since direct measurement ofroom characteristics is usually not possible, blind estimation ofreverberation-related metrics such as the reverberation time (RT) and thedirect-to-reverberant energy ratio (DRR) can be valuable information to speechrecognition and enhancement algorithms operating in enclosed environments. Theobjective of this work is to evaluate the performance of five variants of blindRT and DRR estimators based on a modulation spectrum representation ofreverberant speech with single- and multi-channel speech data. These models areall based on variants of the so-called Speech-to-Reverberation ModulationEnergy Ratio (SRMR). We show that these measures outperform a state-of-the-artbaseline based on maximum-likelihood estimation of sound decay rates in termsof root-mean square error (RMSE), as well as Pearson correlation. Compared tothe baseline, the best proposed measure, called NSRMR_k , achieves a 23%relative improvement in terms of RMSE and allows for relative correlationimprovements ranging from 13% to 47% for RT prediction.

SRMR variants for improved blind room acoustics characterization