Early work on automatic dialogue act classification modeled discourse structure with hidden Markov models, experimenting with lexical and prosodic features, and applying the dialogue act model as a constraint to aid in automatic speech recognition (Stolcke et al., 2000).
to this sequential modeling approach, which is best suited to offline processing, recent work has explored how lexical, syntactic, and prosodic features perform for online dialogue act tagging (when only partial dialogue sequences are available) within a maximum entropy framework (Sridhar, Bangalore, & Narayanan, 2009).