In this section
@article{Parada:2015:10.1186/s13634-015-0237-7,
author = {Parada, PP and Sharma, D and Naylor, PA and van, Waterschoot T},
doi = {10.1186/s13634-015-0237-7},
journal = {Eurasip Journal on Advances in Signal Processing},
pages = {1--12},
title = {Reverberant speech recognition exploiting clarity index estimation},
url = {http://dx.doi.org/10.1186/s13634-015-0237-7},
volume = {2016},
year = {2015}
}
TY - JOUR
AB - We present single-channel approaches to robust automatic speech recognition (ASR) in reverberant environments based on non-intrusive estimation of the clarity index (C 50). Our best performing method includes the estimated value of C 50 in the ASR feature vector and also uses C 50 to select the most suitable ASR acoustic model according to the reverberation level. We evaluate our method on the REVERB Challenge database employing two different C 50 estimators and show that our method outperforms the best baseline of the challenge achieved without unsupervised acoustic model adaptation, i.e. using multi-condition hidden Markov models (HMMs). Our approach achieves a 22.4 % relative word error rate reduction in comparison to the best baseline of the challenge.
AU - Parada,PP
AU - Sharma,D
AU - Naylor,PA
AU - van,Waterschoot T
DO - 10.1186/s13634-015-0237-7
EP - 12
PY - 2015///
SN - 1687-6180
SP - 1
TI - Reverberant speech recognition exploiting clarity index estimation
T2 - Eurasip Journal on Advances in Signal Processing
UR - http://dx.doi.org/10.1186/s13634-015-0237-7
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000358321400001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/32163
VL - 2016
ER -
Speech and Audio Processing Lab
CSP Group, EEE Department
Imperial College London
Exhibition Road, London, SW7 2AZ, United Kingdom