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首页> 外文会议>Workshop on natural language processing techiques for educational applications >Condition Random Fields-based Grammatical Error Detection for Chinese as Second Language
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Condition Random Fields-based Grammatical Error Detection for Chinese as Second Language

机译：条件随机字段的语法错误检测中文作为第二语言

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摘要

The foreign learners are not easy to learn Chinese as a second language. Because there are many special rules different from other languages in Chinese. When the people learn Chinese as a foreign language usually make some grammatical errors, such as missing, redundant, selection and disorder. In this paper, we proposed the conditional random fields (CRFs) to detect the grammatical errors. The features based on statistical word and part-of-speech (POS) pattern were adopted here. The relationships between words by part-of-speech are helpful for Chinese grammatical error detection. Finally, we according to CRF determined which error types in sentences. According to the observation of experimental results, the performance of the proposed model is acceptable in precision and recall rates.
机译：外国学习者并不容易学习中文作为第二语言。因为有许多不同的规则与中文中的其他语言不同。当人们学习中文作为外语通常会产生一些语法错误，例如缺失，冗余，选择和紊乱。在本文中，我们提出了条件随机字段（CRF）来检测语法错误。这里采用了基于统计词和词语（POS）模式的特征。通过演讲的单词之间的关系有助于中国语法错误检测。最后，我们根据CRF确定句子中的错误类型。根据实验结果的观察，拟议模型的性能在精度和召回速率下是可接受的。

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