  We propose a novel approach to translating from a morphologically complex
language. Unlike previous research, which has targeted word inflections and
concatenations, we focus on the pairwise relationship between morphologically
related words, which we treat as potential paraphrases and handle using
paraphrasing techniques at the word, phrase, and sentence level. An important
advantage of this framework is that it can cope with derivational morphology,
which has so far remained largely beyond the capabilities of statistical
machine translation systems. Our experiments translating from Malay, whose
morphology is mostly derivational, into English show significant improvements
over rivaling approaches based on five automatic evaluation measures (for
320,000 sentence pairs; 9.5 million English word tokens).
