SPEAKER ADAPTATION OF CONTINUOUS DENSITY HMMS USING MULTIVARIATE LINEAR REGRESSION
C.J. Leggetter and P.C. Woodland
A method of speaker adaptation for continuous density mixture Gaussian HMMs is presented. A transformation for the component mixture means is derived by linear regression using a maximum likelihood optimisation criteria. The best use is made of the available adaptation data by defining equivalence classes of regression transforms and tying one regression matrix to a number of component mixtures. This allows successful adaptation on any amount of adaptation data. Tests on the RM1 database show that successful adaptation can be achieved with only 11 seconds of speech, and performance converges towards that of speaker dependent training as more adaptation data is used.
If you have difficulty viewing files that end
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
If you have difficulty viewing files that are in PostScript, (ending
'.ps.gz'), then you may be able to
find tools to view them at
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.