DISCRIMINATIVE ADAPTIVE TRAINING USING THE MPE CRITERION
L. Wang and P.C. Woodland
December 2003
This paper addresses the use of discriminative training criteria for Speaker Adaptive Training (SAT), where both the transform generation and model parameter estimation are estimated using the Minimum Phone Error (MPE) criterion. In a similar fashion to the use of I-smoothing for standard MPE training, a smoothing technique is introduced to avoid over-training when optimizing MPE-based feature-space transforms. Experiments on a Conversational Telephone Speech (CTS) transcription task demonstrate that MPE-based SAT models can reduce the word error rate over non-SAT MPE models by 1.0\% absolute, after lattice-based MLLR adaptation. Moreover, a simplified implementation of MPE-SAT with the use of constrained MLLR, in place of MPE-estimated transforms, is also discussed.
If you have difficulty viewing files that end '.gz',
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
web site.
If you have difficulty viewing files that are in PostScript, (ending
'.ps' or '.ps.gz'), then you may be able to
find tools to view them at
the gsview
web site.
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.