On the use of TDNN-extracted features information in talker identification
Younès Bennani, Patrick Gallinari · 1991
The authors propose a novel model for text-independent talker identification which uses TDNN (time-delay neural network) extracted feature information. This model has been tested on 20 speakers (10 male and 10 female) from the TIMIT database using an LPC (linear predictive coding) parameterization. An average identification of 98% was observed.>