MT for Minority Languages Using Elicitation-Based Learning of Syntactic Transfer Rules |
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Authors: | Katharina Probst Lori Levin Erik Peterson Alon Lavie Jaime Carbonell |
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Affiliation: | (1) Language Technologies Institute, Carnegie Mellon University, Pittsburgh, PA, USA |
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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. |
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Keywords: | elicitation rule learning syntactic transfer rules minority languages |
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