ISCA Archive Interspeech 2005
ISCA Archive Interspeech 2005

Fast unsupervised speaker adaptation through a discriminative eigen-MLLR algorithm

Bart Bakker, Carsten Meyer, Xavier Aubert

We present a new method for unsupervised, fast speaker adaptation that combines the Eigen-MLLR transform approach with discriminative MLLR. We thereby aim to profit both from the performance improvements that are generally provided by a discriminative approach, and from the reliability that Eigen-MLLR has demonstrated in fast adaptation scenarios. We present first evaluation results on the Spoke 4 subset of the 1994 Wall Street Journal (WSJ) database. Our results show that, in fast enrollment scenarios, discriminative Eigen-MLLR allows for clear improvements both over non-discriminative Eigen-MLLR and over discriminative MLLR. We further introduce a method to estimate the weight parameters of Eigen-MLLR discriminatively, and show that this allows for further improvements on the considered data sets.


doi: 10.21437/Interspeech.2005-152

Cite as: Bakker, B., Meyer, C., Aubert, X. (2005) Fast unsupervised speaker adaptation through a discriminative eigen-MLLR algorithm. Proc. Interspeech 2005, 257-260, doi: 10.21437/Interspeech.2005-152

@inproceedings{bakker05_interspeech,
  author={Bart Bakker and Carsten Meyer and Xavier Aubert},
  title={{Fast unsupervised speaker adaptation through a discriminative eigen-MLLR algorithm}},
  year=2005,
  booktitle={Proc. Interspeech 2005},
  pages={257--260},
  doi={10.21437/Interspeech.2005-152}
}