Interspeech'2005 - Eurospeech

Lisbon, Portugal
September 4-8, 2005

Improvements to fMPE for Discriminative Training of Features

Daniel Povey

IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

fMPE is a previously introduced form of discriminative training, in which offsets to the features are obtained by training a projection from a high-dimensional feature space based on posteriors of Gaussians. This paper presents recent improvements to fMPE, including improved high-dimensional features which are easier to compute, and improvements to the training procedure. Other issues investigated include cross-testing of fMPE transforms (i.e. using acoustic models other than those with which the fMPE was trained) and the best way to train the Gaussians used to obtain the vector of posteriors.

Full Paper

Bibliographic reference.  Povey, Daniel (2005): "Improvements to fMPE for discriminative training of features", In INTERSPEECH-2005, 2977-2980.