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New neural machine translation architectures are experimenting with pairs of neural encoders / decoders, one pair for each language and a shared language indepe
by ogrisel 12y ago
New neural machine translation architectures are experimenting with pairs of neural encoders / decoders, one pair for each language and a shared language independent vector space for the meaning of all words:
http://arxiv.org/abs/1406.1078 http://arxiv.org/abs/1406.1078
http://arxiv.org/abs/1409.3215 http://arxiv.org/abs/1409.3215
http://arxiv.org/abs/1410.8206 http://arxiv.org/abs/1410.8206
So the total number of models is still linear with the number of languages.
I do not know whether this new generation of translation models is leveraged by the google translation app though.
Also pairs of languages for which their are big amount of parallel training data will still be favored.
- rancur 12y ago> Also pairs of languages for which their are big amount of parallel training data will still be favored. wouldn't bible translations help?
- ogrisel 12y agoIt might but: - the vocabulary and topics covered in the bible is quite different from today's written and spoken text, especially phone discussions or social network messages. - other aligned corpora such as http://www.statmt.org/europarl/ http://www.statmt.org/europarl/ are much larger than the bible (several millions of tokens for most pairs vs less than 1 million for the Bible) Agreed that http://www.statmt.org/europarl/ http://www.statmt.org/europarl/ does not cover non-European languages.