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.
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.