Contribution au Niveau de l'Approche Indirecte à Base de Transfert dans la Traduction Automatique
This work addresses morphosyntactic problems in machine translation for Arabic language processing, but it appears incremental as it builds on existing indirect transfer approaches.
The thesis tackled morphological analysis of Arabic for machine translation by developing a morphological analyzer for Arabic used in bilingual information retrieval, showing statistically significant performance, and proposing morphosyntactic transfer rules from English to Arabic for translation without semantic distortion.
In this thesis, we address several important issues concerning the morphological analysis of Arabic language applied to textual data and machine translation. First, we provided an overview on machine translation, its history and its development, then we exposed human translation techniques for eventual inspiration in machine translation, and we exposed linguistic approaches and particularly indirect transfer approaches. Finally, we presented our contributions to the resolution of morphosyntactic problems in computer linguistics as multilingual information retrieval and machine translation. As a first contribution, we developed a morphological analyzer for Arabic, and we have exploited it in the bilingual information retrieval such as a computer application of multilingual documentary. Results validation showed a statistically significant performance. In a second contribution, we proposed a list of morphosyntactic transfer rules from English to Arabic for translation in three phases: analysis, transfer, generation. We focused on the transfer phase without semantic distortion for an abstraction of English in a sufficient subset of Arabic.