  While there has been significant progress towards modelling coherence in
written discourse, the work in modelling spoken discourse coherence has been
quite limited. Unlike the coherence in text, coherence in spoken discourse is
also dependent on the prosodic and acoustic patterns in speech. In this paper,
we model coherence in spoken discourse with audio-based coherence models. We
perform experiments with four coherence-related tasks with spoken discourses.
In our experiments, we evaluate machine-generated speech against the speech
delivered by expert human speakers. We also compare the spoken discourses
generated by human language learners of varying language proficiency levels.
Our results show that incorporating the audio modality along with the text
benefits the coherence models in performing downstream coherence related tasks
with spoken discourses.
