Graph-Based Collective Lexical Selection for Statistical Machine Translation
Jinsong Su, Deyi Xiong, Shujian Huang, Xianpei Han, Junfeng Yao · 2015
Lexical selection is of great importance to statistical machine translation. In this paper, we propose a graph-based frame-work for collective lexical selection. The framework is established on a translation graph that captures not only local associ-ations between source-side content words and their target translations but also target-side global dependencies in terms of relat-edness among target items. We also in-troduce a random walk style algorithm to collectively identify translations of source-side content words that are strongly related in translation graph. We validate the ef-fectiveness of our lexical selection frame-work on Chinese-English translation. Ex-periment results with large-scale training data show that our approach significantly improves lexical selection. 1