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Machine Translation
Machine translation is the task of translating a sentence in a source language to a different target language.
Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.
One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.
<span style="color:grey; opacity: 0.6">( Image credit: Google seq2seq )</span>
하위 태스크
UM
Unsupervised Machine Translation
MM
Multimodal Machine Translation
LN
Low-Resource Neural Machine Translation
AP
Automatic Post-Editing
BL
Bilingual Lexicon Induction
CL
Clinical Language Translation
LD
Legal Document Translation
LR
Low Resource NMT
LR
Low Resource Neural Machine Translation
T
Transliteration