LIMSI@WMT'17
Résumé
This paper describes LIMSI's submissions to the news shared task
at WMT'17 for English into Czech and Latvian, as well as related experiments. This year's novelties
consist in the use of a neural machine translation system with a factored
output predicting simultaneously a lemma decorated with morphological
information and a fine-grained part-of-speech. Such a type of system
drew our attention to the specific step of reinflection, where
lemmas and parts-of-speech are transformed into fully inflected words.
Finally, we ran experiments showing an efficient strategy for parameter initialization,
as well as data filtering procedures.
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