Due to the differences in education background, accents, etc., different individuals have their unique way of pronunciation. This paper exploits the pronunciation characteristics of speakers and proposes a new conditional pronunciation modeling (CPM) technique for speaker verification. The proposed technique aims to establish a link between articulatory properties (such as manners and places of articulation) and phoneme sequences produced by a speaker. This is achieved by aligning two articulatory feature (AF) streams with a phoneme sequence determined by a phoneme recognizer, and formulating the probabilities of articulatory classes conditioned on the phonemes as speaker-dependent probabilistic models. The scores obtained from the AF-based pronunciation models are then fused with those obtained from a spectral-based speaker verification system, with the frame-by-frame fused scores weighted by the confidence of the pronunciation models. Evaluations based on the SPIDRE corpus demonstrate that AF-based CPM systems can recognize speakers even with short utterances and are readily combined with spectral-based systems to further enhance the reliability of speaker verification.
Cite as: Leung, K.-Y., Mak, M.-W., Kung, S.-Y. (2004) Articulatory feature-based conditional pronunciation modeling for speaker verification. Proc. Interspeech 2004, 2597-2600, doi: 10.21437/Interspeech.2004-545
@inproceedings{leung04_interspeech,
author={Ka-Yee Leung and Man-Wai Mak and Sun-Yuan Kung},
title={{Articulatory feature-based conditional pronunciation modeling for speaker verification}},
year=2004,
booktitle={Proc. Interspeech 2004},
pages={2597--2600},
doi={10.21437/Interspeech.2004-545}
}