Room Identification Using Frequency Dependence of Spectral Decay Statistics
Alastair H. Moore, Patrick A. Naylor, Mike Brookes
Abstract
A method for room identification is proposed based on the reverberation properties of multichannel speech recordings. The approach exploits the dependence of spectral decay statistics on the reverberation time of a room. The average negative-side variance within 1/3-octave bands is proposed as the identifying feature and shown to be effective in a classification experiment. However, negative-side variance is also dependent on the direct-to-reverberant energy ratio. The resulting sensitivity to different spatial configurations of source and microphones within a room are mitigated using a novel reverberation enhancement algorithm. A classification experiment using speech convolved with measured impulse responses and contaminated with environmental noise demonstrates the effectiveness of the proposed method, achieving 79% correct identification in the most demanding condition compared to 40% using unenhanced signals.
BibTeX
@inproceedings{icassp2018_roomidentificati,
title = {Room Identification Using Frequency Dependence of Spectral Decay Statistics},
author = {Alastair H. Moore and Patrick A. Naylor and Mike Brookes},
booktitle = {ICASSP 2018},
year = {2018}
}