Abstract:
Handwritten device users are easy to forget how to write a certain Chinese character. It is necessary to provide Pinyin input method for them. This paper constructs a Pinyin word recognition system through classifier fusion style. It obtains the cutting point of Pinyin word by Hidden Markov Model(HMM) classifier, accomplishes after-recognition fusion by using recognition module for statistic characteristic, studies and improves the base line extraction method for Pinyin word. Experimental results show that this method can recognize 91.37% test samples from 17 745 ones.
Key words:
Chinese information processing,
character recognition,
base line
摘要: 手写设备用户容易忘记特定中文单字写法,需要为其提供拼音输入法。采用分类器融合方式构筑拼音单词识别系统,通过隐马尔可夫模型分类器获得拼音单词的切分点,利用统计特征识别模块进行识别后融合,研究并改进拼音单词基线提取方法。实验结果表明,该方法对17 745个测试样本的识别率达91.37%。
关键词:
中文信息处理,
字符识别,
基线
CLC Number:
ZHU Meng; LIU Chang-song; CHEN Yu-tian; ZOU Yan-ming. Combined Recognition System for Handwritten Pinyin[J]. Computer Engineering, 2010, 36(7): 170-172.
朱 萌;刘长松;陈御天;邹燕明. 手写汉语拼音的融合识别系统[J]. 计算机工程, 2010, 36(7): 170-172.