2005a. Application of word-level confidence measures in interactive statistical machine translation

Abstract. In this paper, we will address the question of how to efficiently integrate word confidence measures into a state-of-the-art interactive statistical machine translation system and improve prediction performance. Different methods will be presented: the selection of words according to their confidence as well as the rejection which has not been investigated so far. Experimental evaluation with respect to prediction accuracy of the system and typing effort saved by a user will show the improved prediction quality. Additionally, we will describe novel methods exploiting knowledge about a correct prefix of the target sentence for confidence estimation. These further increase the interactive system’s performance.