Machine translation with grammar association: some improvements and the Loco_C Model

Authors:
Federico Prat
Affiliations:
Universitat Jaume I de Castelló, Castellón de la Plana, Spain
Venue:
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Year:
2001

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Abstract

Grammar Association is a technique for Machine Translation and Language Understanding introduced in 1993 by Vidal, Pieraccini and Levin. All the statistical and structural models involved in the translation process are automatically built from bilingual examples, and the optimal translation of new sentences can be efficiently found by Dynamic Programming algorithms. This paper presents and discusses Grammar Association state of the art, including a new statistical model: Loco_C.