Uncertainty Corpus: Resource to Study User Affect in Complex Spoken Dialogue Systems

We present a corpus of spoken dialogues between students and an adaptive Wizard-of-Oz tutoring system, in which student uncertainty was manually annotated in real-time. We detail the corpus contents, including speech files, transcripts, annotations, and log files, and we discuss possible future uses by the computational linguistics community as a novel resource for studying naturally occurring user affect and adaptation in complex spoken dialogue systems.