Modality-Preserving Phrase-Based Statistical Machine Translation
Masamichi Ideue, Kazuhide Yamamoto, Masao Utiyama, Eiichiro Sumita · 2012
In machine translation (MT), modality errors are often critical. We propose a phrase-based statistical MT method that preserves the modality of input sentences. The method introduces a feature function that counts the number of phrases in a sentence that are characteristic words for modalities. This simple method increases the number of translations that have the same modality as the input sentences.