ISCA Archive Odyssey 2004
ISCA Archive Odyssey 2004

Variational Bayesian speaker clustering

Fabio Valente, Christian Wellekens

In this paper we explore the use of Variational Bayesian (VB) learning in unsupervised speaker clustering. VB learning is a relatively new learning technique that has the capacity of doing at the same time parameter learning and model selection. We tested this approach on the NIST 1996 HUB-4 evaluation test for speaker clustering when the speaker number is a priori known and when it has to be estimated. VB shows a higher accuracy in terms of average cluster purity and average speaker purity compared to the Maximum Likelihood solution.

Cite as: Valente, F., Wellekens, C. (2004) Variational Bayesian speaker clustering. Proc. The Speaker and Language Recognition Workshop (Odyssey 2004), 207-214

  author={Fabio Valente and Christian Wellekens},
  title={{Variational Bayesian speaker clustering}},
  booktitle={Proc. The Speaker and Language Recognition Workshop (Odyssey 2004)},