Non-intrusive estimation of the level of reverberation in speech

We show corroborating evidence that, among a set of common acoustic parameters, the clarity index C₅₀ provides a measure of reverberation that is well correlated with speech recognition accuracy. We also present a data driven method for non-intrusive C₅₀ parameter estimation from a single channel speech signal. The method extracts a number of features from the speech signal and uses a binary regression tree, trained on appropriate training data, to estimate the C₅₀. Evaluation is carried out using speech utterances convolved with real and simulated room impulse responses, and additive babble noise. The new method outperforms a baseline approach in our evaluation.