GMM and kernel-based speaker recognition with the ISIP toolkit

This paper describes an open source framework for developing speaker recognition systems. Among other features, it supports kernel classifiers, such as the support and relevance vector machines. The paper also presents results for the IME corpus using Gaussian mixture models, which outperforms previously published ones, and discusses strategies for applying discriminative classifiers to speaker recognition