Information-Based Machine Translation

This paper describes an approach to Machine Translation that places linguistic information at its foundation. The difficulty of translation from English to Japanese is illustrated with data that shows the influence of various linguistic contextual factors. Next, a method for natural language transfer is presented that integrates translation examples (represented as typed feature structures with source-target indices) with linguistic rules and constraints. The method has been implemented, and the results of an evaluation are presented.

• Type: Conference
• Year: 2001
• Where: NAACL
• Authors: Keiko Horiguchi
• Keywords: Linguistic Contextual Factors, Linguistic Information, NAACL 2001, NAACL 2007, Typed Feature Structures