Our experimental results on this open-domain spoken language translation task show that the proposed method leads to significant translation performance improvement over a state-of-the-art baseline, and the system using the proposed method achieved the best single system translation result in the Chinese-to-English MT track.

In the Chinese-to-English translation task , we are provided with human translated Chinese text with punctuations inserted.

This is an open-domain spoken language translation task .

The two models are integrated into a state-of-the-art phrase-based machine translation system and evaluated on Chinese-to-English translation tasks with large-scale training data.

The two models have been integrated into a phrase-based SMT system and evaluated on Chinese-to-English translation tasks using large-scale training data.

In this section, we present our eXperiments on Chinese-to-English translation tasks , which are trained with large-scale data.

We evaluated our approach on large-scale J apanese-English and English-Japanese machine translation tasks , and show that it can significantly outperform the baseline phrase-based SMT system.

To test our ranking reorder model, we carry out eXperiments on large scale English-To-Japanese, and J apanese-To-English translation tasks .

We evaluated our approach on large-scale J apanese-English and English-Japanese machine translation tasks , and experimental results show that our approach can bring significant improvements to the baseline phrase-based SMT system in both pre-ordering and integrated decoding settings.