A Hybrid Approach For Spoken Language Machine Translation

Wenhan Chao, Zhoujun Li, Yuexin Chen · 2007

In this paper, we propose a hybrid approach, which is a statistical machine translation (SMT), while using an example-based decoder.In this way, it will solve efficiently the re-ordering problem in SMT and the problems for spoken language MT, such as lots of omissions, idioms etc.We present a novel re-ordering model for SMT firstly and then an example-based decoder.Through experiments, we show that this approach obtains significant improvements over the baseline on a Chinese-English spoken language translation task.

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