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MT for Minority Languages Using Elicitation-Based Learning of Syntactic Transfer Rules
Authors:Katharina Probst  Lori Levin  Erik Peterson  Alon Lavie  Jaime Carbonell
Affiliation:(1) Language Technologies Institute, Carnegie Mellon University, Pittsburgh, PA, USA
Abstract:The AVENUE project contains a run-time machine translationprogram that is surrounded by pre- and post-run-time modules. Thepost-run-time module selects among translation alternatives. Thepre-run-time modules are concerned with elicitation of data andautomatic learning of transfer rules in order to facilitate thedevelopment of machine translation between a language with extensiveresources for natural language processing and a language with fewresources for natural language processing. This paper describes therun-time transfer-based machine translation system as well as two ofthe pre-run-time modules: elicitation of data from the minoritylanguage and automated learning of transfer rules from theelicited data.
Keywords:elicitation  rule learning  syntactic transfer rules  minority languages
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