计算机科学 ›› 2025, Vol. 52 ›› Issue (5): 227-234.doi: 10.11896/jsjkx.240400035
何春辉, 葛斌, 张翀, 徐浩
HE Chunhui, GE Bin, ZHANG Chong, XU Hao
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%。
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