Amélioration a posteriori de la traduction automatique par métaheuristique

TitreAmélioration a posteriori de la traduction automatique par métaheuristique
Type de publicationThesis
Année de publication2016
AuteursLavoie-Courchesne, S.
Academic DepartmentDépartement d'informatique et de recherche opérationnelle
Number of Pages75
Date Published07/2016
Endroit d'éditionMontréal
Mots-clésCollocations, language model, Local search, Metaheuristic, Métaheuristique, Modèle de langue, Recherche locale, Statistical machine translation, Traduction automatique statistique
RésuméStatistical Machine Translation is a field ingreat demand and where machines are still far from producing human-level results.The main method used is a segment by segment linear translation of a sentence, which prevents modification of already translated parts of the sentence. Research for this memoir is based on an approach used by Langlais, Patry and Gotti 2007, which tries to correct a completed translation by modifying segments following a function which needs to be optimized. As a first step, exploration of new traits such as an inverted language model and a collocation model brings a new dimension to the optimization function. As a second step, use of different metaheuristics, such as the greedy and randomized greedy algorithms, allows greater depth while exploring the search space and allows a greater improvement of the objective function.