Using prosodic annotations to improve coreference resolution of spoken text

This paper is the first to examine the effect of prosodic features on coreference resolution in spoken discourse. We test features from different prosodic levels and investigate which strategies can be applied. Our results on the basis of manual prosodic labelling show that the presence of an accent is a helpful feature in a machine-learning setting. Including prosodic boundaries and determining whether the accent is the nuclear accent further increases results.