Automatic speaker verification using the neural network and combined LPC parameters

Author

Chen Zhongbao ; Yu Zhenli ; Zhang Lihe

Author_Institution

Dept. of Electron. Eng., Hangzhou Univ., China

Volume

3

fYear

1993

fDate

19-21 Oct. 1993

Firstpage

345

Abstract

Presents a new method of automatic speaker verification based on a neural network and using the combined LPC paramaters. In the study, a three layered feed-forward neural network is adapted and a variable step (VS) back-propagation algorithm for the automatic learning is used. Several sorts of LPC parameters and their combination are used as the input of the NN mentioned above. In the verification test of the experiment, three vowels /a/, /e/, /i/ uttered by each speaker are used as text-dependent speech, the population is 10 speakers (8 male and 2 female). The test shows the average correct rate of verification is 95 percent.<>

Keywords

backpropagation; feedforward neural nets; linear predictive coding; speech coding; speech recognition; /a/; /e/; /i/; LPC; automatic learning; automatic speaker verification; rate of verification; text-dependent speech; three layered feed-forward neural network; variable step (VS) back-propagation algorithm; Backpropagation algorithms; Cepstrum; Convergence; Feedforward neural networks; Feedforward systems; Linear predictive coding; Neural networks; Speaker recognition; Speech; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on

Conference_Location

Beijing, China

Print_ISBN

0-7803-1233-3

Type

conf

DOI

10.1109/TENCON.1993.327993

Filename

327993