ISCA Archive Interspeech 2013
ISCA Archive Interspeech 2013

ALIZE 3.0 — open source toolkit for state-of-the-art speaker recognition

Anthony Larcher, Jean-Francois Bonastre, Benoit Fauve, Kong Aik Lee, Christophe Lévy, Haizhou Li, John S. D. Mason, Jean-Yves Parfait

ALIZE is an open-source platform for speaker recognition. The ALIZE library implements a low-level statistical engine based on the well-known Gaussian mixture modelling. The toolkit includes a set of high level tools dedicated to speaker recognition based on the latest developments in speaker recognition such as Joint Factor Analysis, Support Vector Machine, i-vector modelling and Probabilistic Linear Discriminant Analysis. Since 2005, the performance of ALIZE has been demonstrated in series of Speaker Recognition Evaluations (SREs) conducted by NIST and has been used by many participants in the last NIST-SRE 2012. This paper presents the latest version of the corpus and performance on the NIST-SRE 2010 extended task.

doi: 10.21437/Interspeech.2013-634

Cite as: Larcher, A., Bonastre, J.-F., Fauve, B., Lee, K.A., Lévy, C., Li, H., Mason, J.S.D., Parfait, J.-Y. (2013) ALIZE 3.0 — open source toolkit for state-of-the-art speaker recognition. Proc. Interspeech 2013, 2768-2772, doi: 10.21437/Interspeech.2013-634

  author={Anthony Larcher and Jean-Francois Bonastre and Benoit Fauve and Kong Aik Lee and Christophe Lévy and Haizhou Li and John S. D. Mason and Jean-Yves Parfait},
  title={{ALIZE 3.0 — open source toolkit for state-of-the-art speaker recognition}},
  booktitle={Proc. Interspeech 2013},