Robotics & Machine Learning Daily News2024,Issue(MAY.7) :76-77.

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)

Robotics & Machine Learning Daily News2024,Issue(MAY.7) :76-77.

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)

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Abstract

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.”

Key words

Hangzhou/People’s Republic of China/As ia/Emerging Technologies/Machine Learning/Machine Translation/Zhejiang Unive rsity of Water Resources and Electric Power

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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