Sogou Neural Machine Translation Systems for WMT17

Xiang Li

Abstract: We describe the Sogou neural machine translation systems for the WMT 2017 Chinese↔ English news translation tasks. Our systems are based on a multilayer encoder-decoder architecture with attention mechanism. The best translation is obtained with ensemble and reranking techniques. We also propose an approach to improve the named entity translation problem. Our Chinese→ English system achieved the highest cased BLEU among all 20 submitted systems, and our English→ Chinese system ranked the third out of 16 submitted systems.