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.
Cite as: Stafylakis, T., Kenny, P., Ouellet, P., Perez, J., Kockmann, M., Dumouchel, P. (2013) Text-dependent speaker recognition using PLDA with uncertainty propagation. Proc. Interspeech 2013, 3684-3688, doi: 10.21437/Interspeech.2013-691
@inproceedings{stafylakis13_interspeech,
author={T. Stafylakis and Patrick Kenny and P. Ouellet and J. Perez and M. Kockmann and Pierre Dumouchel},
title={{Text-dependent speaker recognition using PLDA with uncertainty propagation}},
year=2013,
booktitle={Proc. Interspeech 2013},
pages={3684--3688},
doi={10.21437/Interspeech.2013-691}
}