Syntax-Based Grammaticality Improvement using CCG and Guided Search

Machine-produced text often lacks grammaticality and fluency. This paper studies grammaticality improvement using a syntax-based algorithm based on CCG. The goal of the search problem is to find an optimal parse tree among all that can be constructed through selection and ordering of the input words. The search problem, which is significantly harder than parsing, is solved by guided learning for best-first search. In a standard word ordering task, our system gives a BLEU score of 40.1, higher than the previous result of 33.7 achieved by a dependency-based system.

• Type: Journal
• Year: 2011
• Where: EMNLP
• Authors: Yue Zhang 0004, Stephen Clark
• Keywords: EMNLP 2011, Input Words, Natural Language Processing, Parse Tree, Search Problem