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

fYear

2011

fDate

15-17 Nov. 2011

Firstpage

11

Lastpage

14

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Asian Language Processing (IALP), 2011 International Conference on

Conference_Location

Penang

Print_ISBN

978-1-4577-1733-8

Type

conf

DOI

10.1109/IALP.2011.24

Filename

6121458