We present a study of discriminative training of classi\ufb01ers using both maximum mutual information (MMI) and minimum classi\ufb01cation error (MCE) criteria for online handwritten Chinese\/Japanese character recognition based on continuous-density hidden Markov models. It is observed that MCE-trained classi\ufb01ers can achieve a much higher recognition accuracy than that of MMI-trained ones. Benchmark results of MCE-trained classi\ufb01ers for simpli\ufb01ed Chinese, traditional Chinese and Japanese characters are reported on three recognition tasks with a vocabulary of 9119, 20924, and 12333 characters respectively.<\/p>\n","protected":false},"excerpt":{"rendered":"
We present a study of discriminative training of classi\ufb01ers using both maximum mutual information (MMI) and minimum classi\ufb01cation error (MCE) criteria for online handwritten Chinese\/Japanese character recognition based on continuous-density hidden Markov models. It is observed that MCE-trained classi\ufb01ers can achieve a much higher recognition accuracy than that of MMI-trained ones. Benchmark results of MCE-trained […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"ICFHR 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