Leveraging Structural Mde in Language Processing

This paper looks at the interaction between structural metadata and language structure, i.e. syntax, in conversational speech. We present results in the use of automatically detected boundary events to improve parsing performance, and argue that the results suggest promise for using these events in language modeling. We describe strategies for incorporating metadata-informed language modeling and present results in weakly supervised learning of prosodic constituent structure that are key to the approach.