An Improved Patent Machine Translation System Using Adaptive Enhancement for NTCIR-10 PatentMT Task
Hai Zhao, Jingyi Zhang, Masao Utiyama, Eiichiro Sumita · NTCIR · 2013
This paper describes the work that we conducted for the Chinese-English (CE) task of the NTCIR-10 patent machine translation evaluation. We built standard phrase-based and hierarchical phrase-based statistical machine translation (SMT) systems with optimized word segmentation, adaptive language model and improved parameter tuning strategy. Our systems outperform ocial baselines by approximate 2 BLEU points.