Graph Propagation for Paraphrasing Out-of-Vocabulary Words in Statistical Machine Translation
Majid Razmara, Maryam Siahbani, Reza Haffari, Anoop Sarkar · 2013
Out-of-vocabulary (oov) words or phrases still remain a challenge in statistical machine translation especially when a limited amount of parallel text is available for training or when there is a domain shift from training data to test data. In this paper, we propose a novel approach to finding translations for oov words. We induce a lexicon by constructing a graph on source language monolingual text and employ a graph propagation technique in order to find translations for all the source language phrases. Our method differs from previous approaches by adopting a graph propagation approach that takes into account not only one-step (from oov directly to a source language phrase that has a translation) but multi-step paraphrases from oov source language words to other source language phrases and eventually to target language transla-tions. Experimental results show that our graph propagation method significantly improves per-formance over two strong baselines under intrin-sic and extrinsic evaluation metrics. 1