logo Idiap Research Institute        
 [BibTeX] [Marc21]
Infinite Models for Speaker Clustering
Type of publication: Idiap-RR
Citation: valente:rr06-19
Number: Idiap-RR-19-2006
Year: 2006
Institution: IDIAP
Note: Published in ICLSP 2006
Abstract: In this paper we propose the use of infinite models for the clustering of speakers. Speaker segmentation is obtained trough a Dirichlet Process Mixture (DPM) model which can be interpreted as a flexible model with an infinite a priori number of components. Learning is based on a Variational Bayesian approximation of the infinite sequence. DPM model is compared with fixed prior systems learned by ML/BIC, MAP/BIC and a Variational Bayesian method. Experiments are run on a speaker clustering task on the NIST-96 Broadcast News database.
Userfields: ipdmembership={speech},
Keywords:
Projects Idiap
Authors Valente, Fabio
Crossref by valente:Icslp:2006
Added by: [UNK]
Total mark: 0
Attachments
  • valente-idiap-rr-06-19.pdf
  • valente-idiap-rr-06-19.ps.gz
Notes