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1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings
Most adaptation methods for speech recognition using hidden Markov models fall into two categories; one is the Bayesian approach, where prior distributions for the model parameters are assumed, and the other is the transformation based approach, where a predetermined simple transformation form is employed to modify the model parameters. It is known that the former is better when the amount of data for a d a p tation is large, while the latter is better when the amount of data is small. In thisdoi:10.1109/asru.1997.659114 fatcat:pfpbmj7wv5ed3pheivgmd7bqda