ISCA Archive Interspeech 2005
ISCA Archive Interspeech 2005

Feature adaptation using projection of Gaussian posteriors

Karthik Visweswariah, Peder Olsen

In this paper we consider the use of non-linear methods for feature adaptation to reduce the mismatch between test and training conditions. The non-linearity is introduced by using the posteriors of a set of Gaussians to adapt the original features. Parameters are estimated to maximize the likelihood of the test data. The modeling framework used is based on the fMPE models [1]. We observe significant gains (17% relative) on a test data base recorded in a car. We also see significant gains on top of FMLLR (38% relative over the baseline and 8.5% relative over FMLLR).

doi: 10.21437/Interspeech.2005-163

Cite as: Visweswariah, K., Olsen, P. (2005) Feature adaptation using projection of Gaussian posteriors. Proc. Interspeech 2005, 1785-1788, doi: 10.21437/Interspeech.2005-163

  author={Karthik Visweswariah and Peder Olsen},
  title={{Feature adaptation using projection of Gaussian posteriors}},
  booktitle={Proc. Interspeech 2005},