Paper: Tree-To-String Alignment Template For Statistical Machine Translation

ACL ID P06-1077
Title Tree-To-String Alignment Template For Statistical Machine Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

We present a novel translation model based on tree-to-string alignment template (TAT) which describes the alignment be- tween a source parse tree and a target string. A TAT is capable of generating both terminals and non-terminals and per- forming reordering at both low and high levels. The model is linguistically syntax- based because TATs are extracted auto- matically from word-aligned, source side parsed parallel texts. To translate a source sentence, we first employ a parser to pro- duce a source parse tree and then ap- ply TATs to transform the tree into a tar- get string. Our experiments show that the TAT-based model significantly outper- forms Pharaoh, a state-of-the-art decoder for phrase-based models.