Data generation approaches for topic classification in multilingual spoken dialog systems

Abstract

The conception of spoken-dialog systems (SDS) usually faces the problem of extending or adapting the system to multiple languages. This implies the creation of modules specifically for the new languages, which is a time consuming process. In this paper, we propose two methods to reduce the time needed to extend the SDS to other languages. Our methods are particularly oriented to the topic classification and semantic tagging tasks and we evaluate their effectiveness on topic classification for three languages: English, Spanish, French.