We participated in the IWSLT 2013 Evaluation Campaign for the MT track for two official directions: German↔English. Our system consisted of a reordering module and a statistical machine translation (SMT) module under a pre-ordering SMT framework. We trained the reordering module using three scalable methods in order to utilize training instances as many as possible. The translation quality of our primary submissions were comparable to that of a hierarchical phrasebased SMT, which usually requires a longer time to decode.

We participated in the OLYMPICS task in IWSLT 2012 and submitted two formal runs using a forest-to-string translation system. Our primary run achieved better translation quality than our contrastive run, but worse than a phrase-based and a hierarchical system using Moses.

We introduce a novel translation rule that captures discontinuous, partial constituent, and non-projective phrases from source language. Using the traversal order sequences of the dependency tree, our proposed method 1) extracts the synchronous rules in linear time and 2) combines them efficiently using the CYK chart parsing algorithm. We analytically show the effectiveness of this translation rule in translating relatively free order sentences, and empirically investigate the coverage of our proposed method.