Cristian Keil de Abreu,  André Gustavo Adami. 

This paper describes a toolkit for feature extraction and modeling of high-level features for speaker recognition systems. In addition, the toolkit provides tools to evaluate features and models according to the NIST evaluation paradigm (commonly used as reference for evaluating speaker recognition systems). The toolkit was implemented in Perl and C languages and uses several open-source software for process scheduling and feature extraction. Some results of the toolkit on the 2001 NIST competition are presented in this paper.

http://www.lbd.dcc.ufmg.br/colecoes/til/2007/0017.pdf

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