Text-independent speaker identification

Author

Birnbaum, M. ; Brown, Kathy L. ; Bardenhagen, Steven

Author_Institution

Lockheed Martin Co., Nashua, NH, USA

Volume

2

fYear

1996

fDate

7-10 May 1996

Firstpage

677

Abstract

We have developed a new approach for speaker identification (SID) that employs fenonic speaker Markov modeling (FSMM). The FSMM is a hidden Markov model whose parameters capture and describe intra-speaker spectral dynamics. FSMM technology has been successfully applied in isolated word recognition and speaker adaptation applications. In this new application of FSMM technology to speaker identification, we have obtained an identification accuracy of 96.9% on the King database using 16 talkers. The results suggest that the FSMM provides a promising model for capturing and identifying speaker-specific characteristics

Keywords

hidden Markov models; parameter estimation; speaker recognition; spectral analysis; speech processing; King database; fenonic speaker Markov modeling; hidden Markov model; identification accuracy; intraspeaker spectral dynamics; isolated word recognition; speaker adaptation; speaker identification; speaker specific characteristics; text-independent speaker identification; Cepstral analysis; Character recognition; Databases; Hidden Markov models; Humans; Isolation technology; Loudspeakers; Speech; Statistics; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1520-6149

Print_ISBN

0-7803-3192-3

Type

conf

DOI

10.1109/ICASSP.1996.543211

Filename

543211