A Simple and Effective Neural Model for Joint Word Segmentation and POS Tagging

作者：Zhang, Meishan; Yu, Nan; Fu, Guohong^*

来源：IEEE/ACM Transactions on Audio Speech and Language Processing, 2018, 26(9): 1528-1538.

DOI：10.1109/TASLP.2018.2830117

• Chinese word segmentation
• POS tagging
• joint model
• neural networks
• transition system

Joint models have shown stronger capabilities for Chinese word segmentation and POS tagging, and have received great interests in the community of Chinese natural language processing. In this paper, we follow this line of work, presenting a simple yet effective sequence-to-sequence neural model for the joint task, based on a well-defined transition system, by using long short term memory neural network structures. We conduct experiments on five different datasets. The results demonstrate that our proposed model is highly competitive. By using well-trained character-level embeddings, the proposed neural joint model is able to obtain the best-reported performances in the literature.

• 出版日期2018-9
• 单位黑龙江大学