MT for Minority Languages Using Elicitation-Based Learning of Syntactic Transfer Rules

The AVENUE project contains a run-time machine translation program that is surrounded by pre- and post-run-time modules. The post-run-time module selects among translation alternatives. The pre-run-time modules are concerned with elicitation of data and automatic learning of transfer rules in order to facilitate the development of machine translation between a language with extensive resources for natural language processing and a language with few resources for natural language processing. This paper describes the run-time transfer-based machine translation system as well as two of the pre-run-time modules: elicitation of data from the minority language and automated learning of transfer rules from the elicited data. Key words: elicitation, rule learning, syntactic transfer rules, minority languages

• Type: Journal
• Year: 2002
• Where: MT
• Authors: Katharina Probst, Lori S. Levin, Erik Peterson, Alon Lavie, Jaime G. Carbonell
• Keywords: Machine Translation, MT 2002, Natural Language Processing, Transfer Rules