Analysis and Prediction of Unalignable Words in Parallel Text

Professional human translators usually do not employ the concept of word alignments, producing translations ‘sense-forsense’ instead of ‘word-for-word’. This suggests that unalignable words may be prevalent in the parallel text used for machine translation (MT). We analyze this phenomenon in-depth for Chinese-English translation. We further propose a simple and effective method to improve automatic word alignment by pre-removing unalignable words, and show improvements on hierarchical MT systems in both translation directions.