语境化汉字表征在汉语语法错误诊断中的应用

NLP-TEA@ACL Pub Date : 2018-07-01 DOI:10.18653/v1/W18-3725

Jianbo Zhao, Si Li, Zhiqing Lin

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引用次数: 0

摘要

如今，越来越多的人学习汉语作为他们的第二语言。建立汉语语法错误自动诊断系统已成为一个重要的挑战。本文提出了一种基于语境化字符表征的汉语语法错误诊断模型。与使用LSTM (Long-Short Term Memory)的传统模型相比，我们的模型具有更好的性能，并且不需要添加太多的人工特征。

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Contextualized Character Representation for Chinese Grammatical Error Diagnosis

Nowadays, more and more people are learning Chinese as their second language. Establishing an automatic diagnosis system for Chinese grammatical error has become an important challenge. In this paper, we propose a Chinese grammatical error diagnosis (CGED) model with contextualized character representation. Compared to the traditional model using LSTM (Long-Short Term Memory), our model have better performance and there is no need to add too many artificial features.

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NLP-TEA@ACL

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