Balancing Expressiveness and Simplicity in an Interlingua for Task Based Dialogue

In this paper we compare two interlingua representations for speech translation. The basis of this paper is a distributional analysis of the C-STAR II and NESPOLE databases tagged with interlingua representations. The C-STAR II database has been partially re-tagged with the NESPOLE interlingua, which enables us to make comparisons on the same data with two types of interlinguas and on two types of data (C-STAR II and NESPOLE) with the same interlingua. The distributional information presented in this paper show that the NESPOLE interlingua maintains the language-independence and simplicity of the C-STAR II speech-act-based approach, while increasing semantic expressiveness and scalability.