@inproceedings{f65f7366b21a4940a49e347e504081db,
title = "An application of fuzzy entropy clustering in speaker identification",
abstract = "This paper proposes an application of fuzzy entropy (FE) clustering to train speaker models for speaker identification. The FE objective function is obtained by adding a FE term to the hard C-means objective function. A multiplication factor of the FE term is introduced as the degree of fuzzy entropy, since it is used to control the fuzzification of the FE term. The FE clustering is used in this paper to cluster speech data of speakers into codebooks, i.e. speaker models for vector quantisation-based text-independent speaker identification systems. Experiments on the TI46 database show that a speaker identification system using the FE algorithm achieves better results than that using the well-known K-means algorithm.",
author = "Dat Tran and Michael Wagner",
year = "2000",
language = "English",
isbn = "0964345692",
series = "Proceedings of the Joint Conference on Information Sciences",
publisher = "Association for Computing Machinery (ACM)",
number = "1",
pages = "228--231",
editor = "P.P. Wang",
booktitle = "Proceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000, Volume 1",
address = "United States",
edition = "1",
note = "Proceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000 ; Conference date: 27-02-2000 Through 03-03-2000",
}