This paper describes a framework for multilingual translation using existing translation engines. Our method allows translation between non-English languages through English as a “hub language”. This hub language method has two major problems: “information loss” and “error accumulation”. In order to address these problems, we represent the hub language using the Linguistic Annotation Language (LAL), which contains English syntactic information and source language information. We show the effectiveness of the annotation approach with a series of experiments.

This paper describes a system for finding phrasal translation correspondences from parallel parsed corpus that are collections paired English and Japanese sentences. First, the system finds phrasal correspondences by Japanese-English translation dictionary consultation. Then, the system finds correspondences in remaining phrases by using sentences dependency structures and the balance of all correspondences. The method is based on an assumption that in parallel corpus most fragments in a source sentence have corresponding fragments in a target sentence.