The MATCH corpus: a corpus of older and younger users’ interactions with spoken dialogue systems

Abstract

We present the MATCH corpus, a unique data set of 447 dialogues in which 26 older and 24 younger adults interact with nine different spoken dialogue systems. The systems varied in the number of options presented and the confirmation strategy used. The corpus also contains information about the users' cognitive abilities and detailed usability assessments of each dialogue system. The corpus, which was collected using a Wizard-of-Oz methodology, has been fully transcribed and annotated with dialogue acts and ''Information State Update'' (ISU) representations of dialogue context. Dialogue act and ISU annotations were This research was supported by the MATCH project (SHEFC-HR04016, performed semi-automatically. In addition to describing the corpus collection and annotation, we present a quantitative analysis of the interaction behaviour of older and younger users and discuss further applications of the corpus. We expect that the corpus will provide a key resource for modelling older people's interaction with spoken dialogue systems.

A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version

“…The latter was transcribed and annotated with simple speech acts such as "signaling emotions" or "self-addressing". The MATCH corpus (Georgila et al, 2010) is a small corpus of 447 dialogues based on a Wizard-of-Oz experiment, which contains conversations from 50 young and old adults interacting with spoken dialogue systems. These conversations were annotated semi-automatically with dialogue acts and "Information State Update" (ISU) representations of dialogue context.…”

Designing a spoken dialogue interface to an intelligent cognitive assistant for people with dementia

“…It is difficult to extrapolate from knowledge of cognitive ageing to the usability problems that older users will encounter [14,15], not least because the trajectory of cognitive ageing is incredibly diverse. Existing work includes design patterns [16], databases of interactions between older people and interactive voice response systems [17] and voice interfaces for specific applications (e.g., [10,18,19]). …”

Making Emergency Calls More Accessible to Older Adults Through a Hands-free Speech Interface in the House

“…Some authors (Baba et al, 2004) have reported that classical ASR systems exhibit poor performances for older adults' voice. The MATCH corpus is a collection of dialogues in which older and younger users interacted with a spoken dialogue system in English (Georgila et al, 2010). Analysis made thanks to the MATCH corpus confirmed that representative corpora of human-machine interactions need to contain a substantial sample of older adults.…”