Minimum error rate training for PHMM-based text recognition
Chinching Yen, Shyh-shiaw Kuo, Chin‐Hui Lee · IEEE Transactions on Image Processing · 1999
In this work, discriminative training is studied to improve the performance of our pseudo two-dimensional (2-D) hidden Markov model (PHMM) based text recognition system. The aim of this discriminative training is to adjust model parameters to directly minimize the classification error rate. Experimental results have shown great reduction in recognition error rate even for PHMMs already well-trained using conventional maximum likelihood (ML) approaches.