Developing Non-European Translation Pairs in a Medium-Vocabulary Medical Speech Translation System

We describe recent work on MedSLT, a medium-vocabulary interlingua-based medical speech translation system, focussing on issues that arise when handling languages of which the grammar engineer has little or no knowledge. We describe how we can systematically create and maintain multiple forms of grammars, lexica and interlingual representations, with some versions being used by language informants, and some by grammar engineers. In particular, we describe the advantages of structuring the interlingua definition as a simple semantic grammar, which includes a human-readable surface form. We show how this allows us to rationalise the process of evaluating translations between languages lacking common speakers. The grammar-based interlingua definition can also be used in other ways. We describe two applications: a simple generic tool for debugging to-interlingua translation rules, and a method for improving speech understanding performance by rescoring N-best speech hypothesis lists. Examples presented focus on the concrete case of translation between Japanese and Arabic in both directions. 1