An Example-based Decoder for Spoken Language Machine Translation.

In this paper, we propose an example-based decoder for a statistical machine translation (SMT) system, which is used for spoken language machine translation. In this way, it will help to solve the re-ordering problem and other problems for spoken language MT, such as lots of omissions, idioms etc. Through experiments, we show that this approach obtains improvements over the baseline on a Chinese-English spoken language translation task.