Options
Frame pruning for automatic speaker identification
Auteur(s)
Besacier, Laurent
Bonastre, J. F.
Date de parution
1998-09-08
In
IEEE European Signal Processing Conference EUSIPCO, Institute of Electrical and Electronics Engineers (IEEE), 1998///367-370
Résumé
In this paper, we propose a frame selection procedure for text-independent speaker identification. Instead of averaging the frame likelihoods along the whole test utterance, some of these are rejected (pruning) and the final score is computed with a limited number of frames. This pruning stage requires a prior frame level likelihood normalization in order to make comparison between frames meaningful. This normalization procedure alone leads to a significative performance enhancement. As far as pruning is concerned, the optimal number of frames pruned is learned on a tuning data set for normal and telephone speech. Validation of the pruning procedure on 567 speakers leads to a significative improvement on TIMIT and NTIMIT (up to 30% error rate reduction on TIMIT).
Identifiants
Type de publication
journal article
Dossier(s) à télécharger
