INTERSPEECH 2013
14thAnnual Conference of the International Speech Communication Association

Lyon, France
August 25-29, 2013

Text-Dependent Speaker Recognition Using PLDA with Uncertainty Propagation

T. Stafylakis (1), Patrick Kenny (1), P. Ouellet (1), J. Perez (2), M. Kockmann (2), Pierre Dumouchel (1)

(1) CRIM, Canada
(2) VoiceTrust, Germany

In this paper, we apply and enhance the i-vector-PLDA paradigm to text-dependent speaker recognition. Due to its origin in textindependent speaker recognition, this paradigm does not make use of the phonetic content of each utterance. Moreover, the uncertainty in the i-vector estimates should be taken into account in the PLDA model, due to the short duration of the utterances. To bridge this gap, a phrase-dependent PLDA model with uncertainty propagation is introduced. We examined it on the RSR-2015 dataset and we show that despite its low channel variability, improved results over the GMM-UBM model are attained.

Full Paper

Bibliographic reference.  Stafylakis, T. / Kenny, Patrick / Ouellet, P. / Perez, J. / Kockmann, M. / Dumouchel, Pierre (2013): "Text-dependent speaker recognition using PLDA with uncertainty propagation", In INTERSPEECH-2013, 3684-3688.