Robust automatic speaker verification has become
increasingly desirable in recent years with the growing
trend toward remote security verification procedures
for telephone banking, bio-metric security measures and
similar applications. While many approaches have been
applied to this problem, genetic programming offers
inherent feature selection and solutions that can be
meaningfully analysed, making it well suited to this
task. This paper introduces a genetic programming
system to evolve programs capable of speaker
verification and evaluates its performance with the
publicly available TIMIT corpora. We also show the
effect of a simulated telephone network on
classification results which highlights the principal
advantage, namely robustness to both additive and
convolutive noise
%0 Journal Article
%1 Day:2007:ASLP
%A Day, Peter
%A Nandi, Asoke K.
%D 2007
%J IEEE Transactions on Audio, Speech and Language
Processing
%K additive algorithms, convolutive extraction, feature genetic network networks noise, programming, recognition, remote robust security selection, speaker telephone text-independent verification,
%N 1
%P 285--295
%R 10.1109/TASL.2006.876765
%T Robust Text-Independent Speaker Verification Using
Genetic Programming
%V 15
%X Robust automatic speaker verification has become
increasingly desirable in recent years with the growing
trend toward remote security verification procedures
for telephone banking, bio-metric security measures and
similar applications. While many approaches have been
applied to this problem, genetic programming offers
inherent feature selection and solutions that can be
meaningfully analysed, making it well suited to this
task. This paper introduces a genetic programming
system to evolve programs capable of speaker
verification and evaluates its performance with the
publicly available TIMIT corpora. We also show the
effect of a simulated telephone network on
classification results which highlights the principal
advantage, namely robustness to both additive and
convolutive noise
@article{Day:2007:ASLP,
abstract = {Robust automatic speaker verification has become
increasingly desirable in recent years with the growing
trend toward remote security verification procedures
for telephone banking, bio-metric security measures and
similar applications. While many approaches have been
applied to this problem, genetic programming offers
inherent feature selection and solutions that can be
meaningfully analysed, making it well suited to this
task. This paper introduces a genetic programming
system to evolve programs capable of speaker
verification and evaluates its performance with the
publicly available TIMIT corpora. We also show the
effect of a simulated telephone network on
classification results which highlights the principal
advantage, namely robustness to both additive and
convolutive noise},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Day, Peter and Nandi, Asoke K.},
biburl = {https://www.bibsonomy.org/bibtex/2e7b78aa449c0c68ce3ac3b0e0c3fa0e5/brazovayeye},
doi = {10.1109/TASL.2006.876765},
interhash = {d155a554e712672d193e2c7211592889},
intrahash = {e7b78aa449c0c68ce3ac3b0e0c3fa0e5},
issn = {1558-7916},
journal = {IEEE Transactions on Audio, Speech and Language
Processing},
keywords = {additive algorithms, convolutive extraction, feature genetic network networks noise, programming, recognition, remote robust security selection, speaker telephone text-independent verification,},
month = {January},
notes = {see also IEEE Transactions on Speech and Audio
Processing},
number = 1,
pages = {285--295},
timestamp = {2008-06-19T17:38:27.000+0200},
title = {Robust Text-Independent Speaker Verification Using
Genetic Programming},
volume = 15,
year = 2007
}