CONF
bengio:2001:icassp/IDIAP
Learning the Decision Function for Speaker Verification
Bengio, Samy
MariĆ©thoz, Johnny
EXTERNAL
http://publications.idiap.ch/attachments/reports/2000/rr00-40.pdf
PUBLIC
http://publications.idiap.ch/index.php/publications/showcite/bengio:2000:rr00-40
Related documents
IEEE International Conference on Acoustic, Speech, and Signal Processing, ICASSP
2001
Salt Lake, City, USA
IDIAP-RR 00-40
This paper explores the possibility to replace the usual thresholding decision rule of log likelihood ratios used in speaker verification systems by more complex and discriminant decision functions based for instance on Linear Regression models or Support Vector Machines. Current speaker verification systems, based on generative models such as HMMs or GMMs, can indeed easily be adapted to use such decision functions. Experiments on both text dependent and text independent tasks always yielded performance improvements and sometimes significantly.
REPORT
bengio:2000:rr00-40/IDIAP
Learning the Decision Function for Speaker Verification
Bengio, Samy
MariĆ©thoz, Johnny
EXTERNAL
http://publications.idiap.ch/attachments/reports/2000/rr00-40.pdf
PUBLIC
Idiap-RR-40-2000
2000
IDIAP
published in IEEE International Conference on Acoustic, Speech, and Signal Processing
This paper explores the possibility to replace the usual thresholding decision rule of log likelihood ratios used in speaker verification systems by more complex and discriminant decision functions based for instance on Linear Regression models or Support Vector Machines. Current speaker verification systems, based on generative models such as HMMs or GMMs, can indeed easily be adapted to use such decision functions. Experiments on both text dependent and text independent tasks always yielded performance improvements and sometimes significantly.