Title :
Joint Decoding for Chinese Word Segmentation and POS Tagging Using Character-Based and Word-Based Discriminative Models
Author :
Li, Xinxin ; Wang, Xuan ; Yao, Lin
Author_Institution :
Shenzhen Grad. Sch., Comput. Applic. Res. Center, Harbin Inst. of Technol., Shenzhen, China
Abstract :
For Chinese word segmentation and POS tagging problem, both character-based and word-based discriminative approaches can be used. Experiments show that these two approaches bring different errors and can complement each other. In this paper, we propose a joint decoding model based on both character-based and word-based models using multi-beam search algorithm. Experimental results show that the joint decoding model outperforms character-based and word-based baseline models.
Keywords :
character recognition; decoding; natural language processing; search problems; speech processing; word processing; Chinese word segmentation; POS tagging; character-based discriminative models; joint decoding model; multibeam search algorithm; part-of-speech tagging; word-based discriminative models; Computational linguistics; Computational modeling; Decoding; Hidden Markov models; Joints; Tagging; Training; Chinese word segmentation; joint decoding model; part-of-speech tagging;
Conference_Titel :
Asian Language Processing (IALP), 2011 International Conference on
Conference_Location :
Penang
Print_ISBN :
978-1-4577-1733-8
DOI :
10.1109/IALP.2011.24