We use directed graphical models (DGMs) to automatically detect decision discussions in multi-party dialogue. Our approach distinguishes between different dialogue act (DA) types based on their role in the formulation of a decision. DGMs enable us to model dependencies, including sequential ones. We summarize decisions by extracting suitable phrases from DAs that concern the issue under discussion and its resolution. Here we use a semantic-similarity metric to improve results on both manual and ASR transcripts.
In Proceedings of the 10th Annual SIGDIAL Meeting on Discourse and Dialogue (SIGdial 09), London, UK.
Extracting Decisions from multi-party Dialog using Directed Graphical Models and Semantic Similarity
Trung Bui, M. Frampton, J. Dowding, S. Peters
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