ISCA Archive Interspeech 2007
ISCA Archive Interspeech 2007

Language identification using several sources of information with a multiple-Gaussian classifier

R. Cordoba, L. F. D'Haro, F. Fernandez-Martinez, J. M. Montero, R. Barra

We present several innovative techniques that can be applied in a PPRLM system for language identification (LID). To normalize the scores, eliminate the bias in the scores and improve the classifier, we compared the bias removal technique (up to 19% relative improvement (RI)) and a Gaussian classifier (up to 37% RI). Then, we include additional sources of information in different feature vectors of the Gaussian classifier: the sentence acoustic score (11% RI), the average acoustic score for each phoneme (11% RI), and the average duration for each phoneme (7.8% RI). The use of a multiple-Gaussian classifier with 4 feature vectors meant an additional 15.1% RI. Using 4 feature vectors instead of just PPRLM provides a 26.1% RI. Finally, we include additional acoustic HMMs of the same language with success (10% relative improvement). We will show how all these improvements have been mostly additive.


doi: 10.21437/Interspeech.2007-577

Cite as: Cordoba, R., D'Haro, L.F., Fernandez-Martinez, F., Montero, J.M., Barra, R. (2007) Language identification using several sources of information with a multiple-Gaussian classifier. Proc. Interspeech 2007, 2137-2140, doi: 10.21437/Interspeech.2007-577

@inproceedings{cordoba07b_interspeech,
  author={R. Cordoba and L. F. D'Haro and F. Fernandez-Martinez and J. M. Montero and R. Barra},
  title={{Language identification using several sources of information with a multiple-Gaussian classifier}},
  year=2007,
  booktitle={Proc. Interspeech 2007},
  pages={2137--2140},
  doi={10.21437/Interspeech.2007-577}
}