A modular connectionist architecture for text-independent talker identification

Author

Bennani, Younes ; Gallinari, Patrick

Author_Institution

Lab. de Recherche en Inf., Univ. de Paris-Sud, Orsay, France

fYear

1991

fDate

8-14 Jul 1991

Firstpage

857

Abstract

The authors propose a novel model for text-independent talker identification which uses TDNN (time-delay neural network)-extracted features information. This model has been tested on 20 speakers, ten male and ten female, from the TIMIT database using an LPC (linear prediction coding) parameterization. An average identification of 98% has been observed

Keywords

delays; encoding; neural nets; speech recognition; TIMIT database; linear prediction coding; modular connectionist architecture; parameterization; text-independent talker identification; time-delay neural network; Data mining; Decision making; Feature extraction; Linear predictive coding; Logic; Neural networks; Spatial databases; Speech recognition; TV; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on

Conference_Location

Seattle, WA

Print_ISBN

0-7803-0164-1

Type

conf

DOI

10.1109/IJCNN.1991.155446

Filename

155446

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2722311