Voice identification using nearest-neighbor distance measure

Author

Higgins, A.L. ; Bahler, L.G. ; Porter, J.E.

Author_Institution

ITT Aerospace, San Diego, CA, USA

Volume

2

fYear

1993

fDate

27-30 April 1993

Firstpage

375

Abstract

An algorithm for attributing a sample of unconstrained speech to one of several known speakers is described. The algorithm is based on measurement of the similarity of distributions of features extracted from reference speech samples and from the sample to be attributed. The measure of feature distribution similarity employed is not based on any assumed form of the distributions involved. The theoretical basis of the algorithm is examined, and a plausible connection is shown to the divergence statistic of Kullback (1972). Experimental results are presented for the King telephone database and the Switchboard database. The performance of the algorithm is better than that reported for algorithms based on Gaussian modeling and robust discrimination.<>

Keywords

feature extraction; speech recognition; voice communication; King telephone database; Switchboard database; algorithm; divergence statistic; feature distribution similarity; nearest-neighbor distance measure; performance; unconstrained speech; voice identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on

Conference_Location

Minneapolis, MN, USA

ISSN

1520-6149

Print_ISBN

0-7803-7402-9

Type

conf

DOI

10.1109/ICASSP.1993.319317

Filename

319317