Blur kernel estimation approach to blind reverberation time estimation

Abstract

Reverberation time is an important parameter for characterizing acoustic environments. It is useful in many applications including acoustic scene analysis, robust automatic speech recognition and dereverberation. Given knowledge of the acoustic impulse response, reverberation time can be measured using Schroeder's backward integration method. Since it is not always practical to obtain impulse responses, blind estimation algorithms are sometimes desirable. In this work, the reverberation problem is viewed as an image blurring problem. The blur kernel is estimated through spectral analysis in the modulation domain and the T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sub> is subsequently estimated from the blur kernel's parameters. It is shown through experimental results that the proposed approach is able to improve robustness to higher T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sub> s especially with increasing levels of additive noise up to an signal-to-noise ratio (SNR) of 10 dB.