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COLING
2010

An Efficient Shift-Reduce Decoding Algorithm for Phrased-Based Machine Translation

10 years 1 months ago
An Efficient Shift-Reduce Decoding Algorithm for Phrased-Based Machine Translation
In statistical machine translation, decoding without any reordering constraint is an NP-hard problem. Inversion Transduction Grammars (ITGs) exploit linguistic structure and can well balance the needed flexibility against complexity constraints. Currently, translation models with ITG constraints usually employs the cube-time CYK algorithm. In this paper, we present a shift-reduce decoding algorithm that can generate ITG-legal translation from left to right in linear time. This algorithm runs in a reduce-eager style and is suited to phrase-based models. Using the state-ofthe-art decoder Moses as the baseline, experiment results show that the shift-reduce algorithm can significantly improve both the accuracy and the speed on different test sets.
Yang Feng, Haitao Mi, Yang Liu, Qun Liu
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2010
Where COLING
Authors Yang Feng, Haitao Mi, Yang Liu, Qun Liu
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