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Automatic Detection and Correction for Chinese Misspelled Words Using Phonological and Orthographic Similarities

机译:利用语音和正字法相似度自动检测和纠正中文拼写错误的单词

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摘要

How to detect and correct misspelled words in documents is a very important issue for Mandarin and Japanese. This paper uses phonological similarity and orthographic similarity co-occurrence to train linear regression model. Using ACL-SIGHAN 2013 Bake-off Dataset, experimental results indicate that the detection F-score, error location F-score of our proposed method for Subtask 1 is 0.70 and 0.43 respectively, and the correction accuracy of the proposed method for Subtask 1 is 0.39.
机译:对于普通话和日语,如何检测和纠正文档中拼写错误的单词是一个非常重要的问题。本文利用语音相似度和正字相似度共现来训练线性回归模型。使用ACL-SIGHAN 2013烘焙数据集,实验结果表明,我们针对子任务1提出的方法的检测F分数,错误位置F分数分别为0.70和0.43,并且针对子任务1的提议方法的校正精度为0.39。

著录项

  • 来源
  • 会议地点 Nagoya(JP)
  • 作者单位

    Department of Computer Science and Information Engineering, National Kaohsiung University of Applied Sciences;

    Department of Educational Psychology and Counseling National Taiwan Normal University;

    Information Technology Center National Taiwan Normal University;

    Department of Computer Science and Information Engineering, National Kaohsiung University of Applied Sciences;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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