Acoustic Blur Kernel with Sliding Window for Blind Estimation of Reverberation Time

Reverberation time, or T60, is a key parameter used for characterizing acoustic spaces. Blind T60 estimation is useful for many applications including speech intelligibility estimation, acoustic scene analysis and dereverberation. In our previous work, a single channel blind T60 estimator was proposed employing spectral analysis in the modulation frequency domain. It was shown that the estimation accuracy is crucially affected by the window lengths used for transformation to the modulation domain. In this work, we propose the use of a sliding window length that is dynamically updated depending on the length of the detected decay region. Experimental results demonstrated that in the presence of noise, estimation accuracy was improved over our previous work for T60 up to 700 ms. When compared against two alternative algorithms from the literature, the proposed approach demonstrated higher accuracy for T60 between 500 ms and 1 s. Finally, the proposed approach was shown to be more computationally efficient compared to two of the three alternative algorithms.