Paper: A Generative Joint, Additive, Sequential Model of Topics and Speech Acts in Patient-Doctor Communication

ACL ID D13-1182
Title A Generative Joint, Additive, Sequential Model of Topics and Speech Acts in Patient-Doctor Communication
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

We develop a novel generative model of con- versation that jointly captures both the top- ical content and the speech act type asso- ciated with each utterance. Our model ex- presses both token emission and state tran- sition probabilities as log-linear functions of separate components corresponding to topics and speech acts (and their interactions). We apply this model to a dataset comprising anno- tated patient-physician visits and show that the proposed joint approach outperforms a base- line univariate model.