In this paper, a new language identification system is presented based on the total variability approach previously developed in the field of speaker identification. Various techniques are employed to extract the most salient features in the lower dimensional i-vector space and the system developed results in excellent performance on the 2009 LRE evaluation set without the need for any postprocessing or backend techniques. Additional performance gains are observed when the system is combined with other acoustic systems.
Cite as: Dehak, N., Torres-Carrasquillo, P.A., Reynolds, D., Dehak, R. (2011) Language recognition via i-vectors and dimensionality reduction. Proc. Interspeech 2011, 857-860, doi: 10.21437/Interspeech.2011-328
@inproceedings{dehak11_interspeech,
author={Najim Dehak and Pedro A. Torres-Carrasquillo and Douglas Reynolds and Reda Dehak},
title={{Language recognition via i-vectors and dimensionality reduction}},
year=2011,
booktitle={Proc. Interspeech 2011},
pages={857--860},
doi={10.21437/Interspeech.2011-328}
}