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Can I use Bert for machine translation?
BERT is not a machine translation model, BERT is designed to provide a contextual sentence representation that should be useful for various NLP tasks.
Does Google Translate use Bert?
Does Google Translate use Bert? BERT was created by Google to help their search engine in understanding the content on various web pages. BERT can be helpful to the search engine because it is a natural language processing technique. Currently, BERT is also being used by Google Translate.
Is machine translation supervised or unsupervised?
The machine translation system could be built as a fully supervised one, though the parallel corpus is small (50K); as an unsupervised one, using the two monolingual corpora; and as a semi-supervised one.
What factors of machine translation can involve?
These factors include the intended use of the translation, the nature of the machine translation software, and the nature of the translation process. Different programs may work well for different purposes.
How to effectively apply Bert to neural machine translation?
However, how to effectively apply BERT to neural machine translation (NMT) lacks enough exploration. While BERT is more commonly used as fine-tuning instead of contextual embedding for downstream language understanding tasks, in NMT, our preliminary exploration of using BERT as contextual embedding is better than using for fine-tuning.
Which is the most powerful neural machine translation technique?
Among them, BERT is one of the most powerful techniques that inspires lots of variants like XLNet, XLM, RoBERTa and achieves state-of-the-art results for many language understanding tasks including reading comprehension, text classification, etc (Devlin et al., 2019).
What are the extra modules in Bert NMT?
Compared to standard NMT, in addition to BERT, there are two extra attention modules, the BERT-encoder attention and BERT-decoder attention. An input sequence is first transformed into representations processed by BERT.