In this paper, we present a novel global reordering model that can be incorporated into standard phrase-based statistical machine translation. Unlike previous local reordering mod...
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to capture phrase reorderings using a structure learning framework....
We present a constituent parsing-based reordering technique that improves the performance of the state-of-the-art English-to-Japanese phrase translation system that includes disto...
Syntactic reordering approaches are an effective method for handling word-order differences between source and target languages in statistical machine translation (SMT) systems. T...
This paper presents a direct word reordering model with novel syntax-based features for statistical machine translation. Reordering models address the problem of reordering source...