DocumentCode
319592
Title
Automatic gender identification optimised for language independence
Author
Slomka, Stefan ; Sridharan, Sridha
Author_Institution
Queensland Univ. of Technol., Brisbane, Qld., Australia
Volume
1
fYear
1997
fDate
4-4 Dec. 1997
Firstpage
145
Abstract
In this paper 63 automatic gender identification (AGI) systems based on the fusion of multiple knowledge sources using a linear classifier (LC) are tested on speakers of 11 languages present in the OGI speech corpus. It is found that training the LC with multiple languages can improve the accuracy of the AGI system.
Keywords
identification; natural languages; optimisation; pattern classification; speech recognition; AGI systems; OGI speech corpus; Oregon Graduate Institute; accuracy; automatic gender identification; language independence; linear classifier; multiple knowledge sources fusion; optimisation; Automatic speech recognition; Cepstrum; Fuses; Natural languages; Signal processing; Speech analysis; Speech processing; System testing; Tail; Telephony;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE
Conference_Location
Brisbane, Qld., Australia
Print_ISBN
0-7803-4365-4
Type
conf
DOI
10.1109/TENCON.1997.647278
Filename
647278
Link To Document