Multiple-cluster adaptive training schemes
Mark Gales · 2002
This paper examines the training of multiple-cluster systems using adaptive training schemes. Various forms of transformation and canonical model are described in a consistent framework allowing re-estimation formulae for all cases to be simply derived. Initial experiments using these various schemes on a large vocabulary speech recognition task are presented. The initial experiments indicate that to achieve best performance when adapting these multiple-cluster systems requires the use of adaptive training schemes rather than using simpler cluster initialisation schemes.