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In current statistical machine translation, IBM model based word alignment is widely used as a starting point to build phrase-based machine translation systems. However, such alignment model is separated from the rest of machine translation pipeline and optimized independently. Furthermore, structural information is not taken into account in the alignment model, which sometimes leads to incorrect...
In this paper, we present advanced techniques that improved the performance of IBM Malay-English speech translation system significantly. During this work, we generated linguistics-driven hierarchical rules to enhance the formal syntax-based translation model; designed an active learning approach with bi-directional translations that outperformed unsupervised training; utilized translation direction...
Named entity (NE) translation is a challenging problem in machine translation (MT). Most of the training bi-text corpora for MT lack enough samples of NEs to cover the wide variety of contexts NEs can appear in. In this paper, we present a technique to translate NEs based on their NE types in addition to a phrase-based translation model. Our NE translation model is based on a syntax-based system similar...
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