In this paper, we present the collection and analysis of a spoken dialogue corpus obtained from interactions of older and younger users with a smart-home system. Our aim is to identify the amount and the origin of linguistic differences in the way older and younger users address the system. In addition, we investigate changes in the users’ linguistic behaviour after exposure to the system. The results show that the two user groups differ in their speaking style as well as their vocabulary. In contrast to younger users, who adapt their speaking style to the expected limitations of the system, older users tend to use a speaking style that is closer to human-human communication in terms of sentence complexity and politeness. However, older users are far less easy to stereotype than younger users.

In this paper we present a corpus of interactions of older and younger users with nine different dialogue systems. The corpus has been fully transcribed and annotated with dialogue acts and “Information State Update” (ISU) representations of dialogue context. Users not only underwent a comprehensive battery of cognitive assessments, but they also rated the usability of each dialogue system on a standardised questionnaire. In this paper, we discuss the corpus collection and outline the semi-automatic methods we used for discourse-level annotations. We expect that the corpus will provide a key resource for modelling older people’s interaction with spoken dialogue systems.