Room identification using frequency dependence of spectral decay statistics. Moore, A. H., Naylor, P. A., & Brookes, M. In ICASSP, Calgery, Canada, April, 2018.
abstract   bibtex   
A method for room identification is proposed based on the reverber- ation properties of multichannel speech recordings. The approach exploits the dependence of spectral decay statistics on the reverber- ation 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 vari- ance 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.
@inproceedings{Moore2018,
	address = {Calgery, Canada},
	title = {Room identification using frequency dependence of spectral decay statistics},
	abstract = {A method for room identification is proposed based on the reverber- ation properties of multichannel speech recordings. The approach exploits the dependence of spectral decay statistics on the reverber- ation 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 vari- ance 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.},
	booktitle = {{ICASSP}},
	author = {Moore, Alastair H. and Naylor, Patrick A. and Brookes, Mike},
	month = apr,
	year = {2018},
}

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