Paris NLP Season 3 Meetup #2 at Méritis

Thanks to our host Meritis

• François Yvon, LIMSI/CNRS

Using monolingual data in Neural Machine Translation

Modern machine translation rests on the availability of appropriate parallel corpora, which are scarce and costly to accumulate. Monolingual corpora are much easier to get, and can be easily integrated into Statistical Machine Translation systems, where they have shown to be of great help. The issue is slightly different in Neural Machine Translation (NMT) , and how to take advantage of these resources is still the subject to discussions. In this talk, I will try to summarize a series of recent papers on this topic and comment on the current state of the debate. This will also give me the opportunity to discuss research in NMT in more general terms. This has been conducted jointly with Franck Burlot.


• Kezhan SHI, Data Science manager at Allianz France,

will show you interesting results with NLP techniques in an Insurance project through an in-depth case study involving :

– string distance or phonetic distance (used in geocoding for string fuzzy matching)
– documents classification (for construction firm’s activity recognition)
– word2vec (understanding construction firm’s activities)

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