A Study of Discriminative Training for HMM-Based Online Handwritten Chinese/Japanese Character Recognition

@article{Wang2010ASO,
  title={A Study of Discriminative Training for HMM-Based Online Handwritten Chinese/Japanese Character Recognition},
  author={Yongqiang Wang and Qiang Huo and Yu Shi},
  journal={2010 12th International Conference on Frontiers in Handwriting Recognition},
  year={2010},
  pages={518-523}
}
We present a study of discriminative training of classifiers using both maximum mutual information (MMI) and minimum classification error (MCE) criteria for online handwritten Chinese/Japanese character recognition based on continuous-density hidden Markov models. It is observed that MCE-trained classifiers can achieve a much higher recognition accuracy than that of MMI-trained ones. Benchmark results of MCE-trained classifiers for simplified Chinese, traditional Chinese and Japanese characters… CONTINUE READING