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...
Hierarchical phrase-based translation model has been proven to be a simple and powerful machine translation model. However, due to the computational complexity constraints, the ext...
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...
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....
This paper proposes a novel maximum entropy based rule selection (MERS) model for syntax-based statistical machine translation (SMT). The MERS model combines local contextual info...