Natural Language Processing Advancements By Deep Learning: A Survey
TABLE VII: The machine translation state-of-the-art models evaluated on the English-German dataset of ACL 2014 Ninth Workshop on Statistical Machine TRranslation. The evaluation metric is BLEU score.
['Model', 'Accuracy']
Improved machine translation models continue to emerge, driven in part by the growth in people’s interest and need to understand other languages Most of them are variants of the end-to-end decoder-encoder approach. For example, [wu2016google] tries to deal with the problem of rare words. Their LSTM network consists of encoder and decoder layers using residual layers along with the attention mechanism. Their system was able to decrease training time, speed up inference, and handle translation of rare words.