no code implementations • WS 2018 • Zied Elloumi, Laurent Besacier, Olivier Galibert, Benjamin Lecouteux
In a previous paper, we presented an ASR performance prediction system using CNNs that encode both text (ASR transcript) and speech, in order to predict word error rate.
no code implementations • 23 Apr 2018 • Zied Elloumi, Laurent Besacier, Olivier Galibert, Juliette Kahn, Benjamin Lecouteux
In this paper, we address a relatively new task: prediction of ASR performance on unseen broadcast programs.
no code implementations • JEPTALNRECITAL 2017 • Kamel Bouzidi, Zied Elloumi, Laurent Besacier, Benjamin Lecouteux, Mohamed-Faouzi Benzeghiba
Les exp{\'e}rimentations sont r{\'e}alis{\'e}s sur un corpus de journaux num{\'e}ris{\'e}s en arabe et permettent d{'}obtenir des am{\'e}liorations en score BLEU de 3, 73 et 5, 5 sur les corpus de d{\'e}veloppement et de test respectivement.
1 code implementation • COLING 2016 • Christophe Servan, Alexandre Berard, Zied Elloumi, Hervé Blanchon, Laurent Besacier
This paper presents an approach combining lexico-semantic resources and distributed representations of words applied to the evaluation in machine translation (MT).
no code implementations • JEPTALNRECITAL 2016 • Christophe Servan, Zied Elloumi, Herv{\'e} Blanchon, Laurent Besacier
Cet article pr{\'e}sente une approche associant r{\'e}seaux lexico-s{\'e}mantiques et repr{\'e}sentations distribu{\'e}es de mots appliqu{\'e}e {\`a} l{'}{\'e}valuation de la traduction automatique.