Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (5): 227-234.doi: 10.11896/jsjkx.240400035

• Artificial Intelligence • Previous Articles     Next Articles

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

HE Chunhui, GE Bin, ZHANG Chong, XU Hao   

  1. Laboratory for Big Data and Decision,National University of Defense Technology,Changsha 410073,China
  • Received:2024-04-04 Revised:2024-08-20 Online:2025-05-15 Published:2025-05-12
  • About author:HE Chunhui,born in 1991,master.His main research interests include information processing and artificial intelligence.
    GE Bin,born in 1979,Ph.D,researcher.His main research interests include big data analysis and information extraction.
  • Supported by:
    National Key Research and Development Program of China(2022YFB3103600).

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Abstract: 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.

Key words: Idioms error correction, Fixed length Seq2Seq, BiGRU, Attention mechanism

CLC Number: 

  • TP391
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