Asheesh Gulati


2020

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LEX : un jeu avec finalité d’acquisition de ressources lexicales (LEX : a game with the purpose of lexical resource acquisition)
Asheesh Gulati
Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 4 : Démonstrations et résumés d'articles internationaux

LEX est un jeu avec un but développé dans l’optique d’explorer plus avant les éléments et principes de la conception de jeux tels qu’ils sont pratiqués dans l’industrie vidéoludique, pour les mettre au service de la conception de jeux sérieux. Le premier prototype repose sur un mode bac à sable pour faire appel à la créativité du joueur et renforcer l’immersion ludique.

2015

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The ACCEPT Academic Portal: Bringing Together Pre-editing, MT and Post-editing into a Learning Environment
Pierrette Bouillon | Johanna Gerlach | Asheesh Gulati | Victoria Porro | Violeta Seretan
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

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The ACCEPT Academic Portal: Bringing Together Pre-editing, MT and Post-editing into a Learning Environment
Pierrette Bouillon | Johanna Gerlach | Asheesh Gulati | Victoria Porro | Violeta Seretan
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

2012

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Italian and Spanish Null Subjects. A Case Study Evaluation in an MT Perspective.
Lorenza Russo | Sharid Loáiciga | Asheesh Gulati
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

Thanks to their rich morphology, Italian and Spanish allow pro-drop pronouns, i.e., non lexically-realized subject pronouns. Here we distinguish between two different types of null subjects: personal pro-drop and impersonal pro-drop. We evaluate the translation of these two categories into French, a non pro-drop language, using Its-2, a transfer-based system developed at our laboratory; and Moses, a statistical system. Three different corpora are used: two subsets of the Europarl corpus and a third corpus built using newspaper articles. Null subjects turn out to be quantitatively important in all three corpora, but their distribution varies depending on the language and the text genre though. From a MT perspective, translation results are determined by the type of pro-drop and the pair of languages involved. Impersonal pro-drop is harder to translate than personal pro-drop, especially for the translation from Italian into French, and a significant portion of incorrect translations consists of missing pronouns.

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Improving machine translation of null subjects in Italian and Spanish
Lorenza Russo | Sharid Loáiciga | Asheesh Gulati
Proceedings of the Student Research Workshop at the 13th Conference of the European Chapter of the Association for Computational Linguistics