首页|New Findings from Zhejiang University of Water Resources and Electric Power in M achine Translation Provides New Insights (Sense-aware Decoder for Character Base d Japanese-chinese Nmt)
New Findings from Zhejiang University of Water Resources and Electric Power in M achine Translation Provides New Insights (Sense-aware Decoder for Character Base d Japanese-chinese Nmt)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Translation h ave been presented. According to news reporting from Hangzhou, People’s Republic of China, by NewsRx journalists, research stated, “Compared to subword based Ne ural Machine Translation (NMT), character based NMT eschews linguistic -motivate d segmentation which performs directly on the raw character sequence, following a more absolute end -to -end manner. This property is more fascinating for machi ne translation (MT) between Japanese and Chinese, both of which use consecutive logographic characters without explicit word boundaries.”
HangzhouPeople’s Republic of ChinaAs iaEmerging TechnologiesMachine LearningMachine TranslationZhejiang Unive rsity of Water Resources and Electric Power
NETL
NSTL
