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手写汉语拼音的融合识别系统
引用本文: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.
作者姓名:朱萌  刘长松  陈御天  邹燕明
作者单位:1. 清华大学智能技术与系统国家重点实验室,北京,100084;清华大学电子工程系清华信息科学与技术国家实验室,北京,100084
2. 诺基亚北京研究院,北京,100176
基金项目:国家“973”计划基金资助项目(2007CB311004);;国家自然科学基金资助项目(60772049)
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
修稿时间: 

Combined Recognition System for Handwritten Pinyin
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.
Authors:ZHU Meng  LIU Chang-song  CHEN Yu-tian  ZOU Yan-ming
Affiliation:(1. State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084; 2. Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing 100084; 3. Nokia Research Center, Beijing 100176)
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.
Keywords:Chinese information processing  character recognition  base line
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