In this section
@inproceedings{Parada:2014:10.1109/ICASSP.2014.6854497,
author = {Parada, PP and Sharma, D and Naylor, PA},
doi = {10.1109/ICASSP.2014.6854497},
pages = {4718--4722},
title = {Non-intrusive estimation of the level of reverberation in speech},
url = {http://dx.doi.org/10.1109/ICASSP.2014.6854497},
year = {2014}
}
TY - CPAPER
AB - We show corroborating evidence that, among a set of common acoustic parameters, the clarity index C<inf>50</inf> provides a measure of reverberation that is well correlated with speech recognition accuracy. We also present a data driven method for non-intrusive C<inf>50</inf> 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 C<inf>50</inf>. 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. © 2014 IEEE.
AU - Parada,PP
AU - Sharma,D
AU - Naylor,PA
DO - 10.1109/ICASSP.2014.6854497
EP - 4722
PY - 2014///
SN - 1520-6149
SP - 4718
TI - Non-intrusive estimation of the level of reverberation in speech
UR - http://dx.doi.org/10.1109/ICASSP.2014.6854497
ER -
Speech and Audio Processing Lab
CSP Group, EEE Department
Imperial College London
Exhibition Road, London, SW7 2AZ, United Kingdom