LM Enhanced BiRNN-CRF for Joint Chinese Word Segmentation and POS Tagging

摘要：

　　Word segmentation and part-of-speech tagging are two preliminary but fundamental components of Chinese natural language processing.With the upsurge of deep learning,end-to-end models are built without handcrafted features.In this work,we model Chinese word segmentation and part-of-speech tagging jointly on the basis of state-of-theart BiRNN-CRF architecture.LSTM is adopted as the basic recurrent unit.Apart from utilizing pre-trained character embeddings and trigram features,we incorporate neural language model and conduct multi-task training.Highway layers are applied to tackle the discordance issue of the naive co-training.Experimental results on CTB5,CTB7,and PPD datasets show the effectiveness of the proposed method.

关键词： Chinese word segmentation POS tagging LSTM Language model

作者: Jianhu Zhang Gongshen Liu Jie Zhou Cheng Zhou Huanrong Sun

作者单位: School of Electric Information and Electronic Engineering,Shanghai Jiaotong University,Shanghai,Chin SJTU-Shanghai Songheng Content Analysis Joint Lab,Shanghai,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 105-116

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）