In this paper, we investigate two facets of speaker recognition : cross-language speaker identification and same-language non-native text-independent speaker identification. In this context, experiments have been conducted, using standard multi-Gaussian modeling, on the brand new multi-language TNO corpus. Our results indicate how speaker identification performance might be affected when speakers do not use the same language during the training and testing, or when the population is composed of non-native speakers.
Cite as: Durou, G. (1999) Multilingual text-independent speaker identification. Proc. Multi-Lingual Interoperability in Speech Technology, 68-72
@inproceedings{durou99_mist,
author={Geoffrey Durou},
title={{Multilingual text-independent speaker identification}},
year=1999,
booktitle={Proc. Multi-Lingual Interoperability in Speech Technology},
pages={68--72}
}