融合定长Seq2Seq网络的中文成语智能纠错模型  

Intelligent Error Correction Model for Chinese Idioms Fused with Fixed-length Seq2Seq Network

作　　者：何春辉 葛斌[1] 张翀[1] 徐浩[1] HE Chunhui;GE Bin;ZHANG Chong;XU Hao(Laboratory for Big Data and Decision,National University of Defense Technology,Changsha 410073,China)

机构地区：[1]国防科技大学大数据与决策实验室,长沙410073

出　　处：《计算机科学》2025年第5期227-234,共8页Computer Science

基　　金：国家重点研发计划(2022YFB3103600)。

摘　　要：四字成语作为一类特殊词语,在中文使用中非常流行。随着中文纠错任务的发展,中文成语的智能纠错已经成为自然语言处理领域的一个研究热点。针对现有方法在中文成语智能纠错任务上准确率偏低的问题,提出了一种融合定长Seq2Seq网络的中文成语智能纠错模型。它在底层通过融合Seq2Seq网络架构和注意力机制,并结合混合数据集构造方法,共同训练得到输入和输出端序列长度固定的Seq2Seq模型,用来完成中文四字成语智能纠错任务。在大型公开中文成语纠错数据集上的实验结果表明,定长Seq2Seq模型优于现有方法,能够实现同一个模型同时兼容乱序、缺字和错字3种不同的中文成语智能纠错目标。它的综合纠错准确率可以达到91.3%,比最优基线模型高出11.73%。As a special kind of words,four-character idioms are very popular in Chinese.With the development of Chinese error correction task,intelligent error correction for Chinese idioms has become a research hotspot in natural language processing(NLP)domain.For the low accuracy of the existing methods in intelligent error correction task for Chinese idioms,this paper proposes an intelligent error correction model for Chinese idioms fused with fixed-length Seq2Seq network.In the bottom layer,Seq2Seq network architecture and attention mechanism are combined with hybrid dataset construction method to train Seq2Seq model with fixed input and output sequence length,which is used to solve intelligent error correction task for Chinese four-character idioms.Experimental results on a large public Chinese idiom error correction dataset show that the performance of fixed-length Seq2Seq model is better than the existing methods,and it can achieve the goal of intelligent error correction of three diffe-rent Chinese idioms:out-of-order,missing character and wrong character.Its comprehensive error correction accuracy can reach 91.3%,which is 11.73%higher than the optimal baseline model.

关 键 词：成语纠错 定长Seq2Seq 双向GRU 注意力机制 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]