Character-based PSMT for Closely Related Languages

Translating unknown words between related languages using a character-based statistical machine translation model can be beneficial. In this paper, we describe a simple method to combine character-based models with standard word-based models to increase the coverage of a phrase-based SMT system. Using this approach, we can show a modest improvement when translating between Norwegian and Swedish. The potentials of applying character-based models to closely related languages is also illustrated by applying the character model on its own. The performance of such an approach is similar to the word-level baseline and closer to the reference in terms of string similarity.