Predicting focus through prominence structure

TL;DR: This work claims that a focus is more likely if a word is more prominent than expected given its syntactic, semantic and discourse properties, and builds focus prediction models built using the NXT Switchboard corpus.

Abstract: Focus is central to our control of information flow in dialogue. Spoken language understanding systems therefore need to be able to detect focus automatically. It is well known that prominence is a key marker of focus in English, however, the relationship is not straight-forward. We present focus prediction models built using the NXT Switchboard corpus. We claim that a focus is more likely if a word is more prominent than expected given its syntactic, semantic and discourse properties. Crucially, the perception of prominence arises not only from acoustic cues, but also the position in prosodic structure. Our focus prediction results, along with a study showing the acoustic properties of focal accents vary by structural position, support our claims. As a largely novel task, these results are an important first step in detecting focus for spoken language applications.