Dialogue Act Recognition in Synchronous and Asynchronous Conversations
نویسندگان
چکیده
In this work, we study the effectiveness of state-of-the-art, sophisticated supervised learning algorithms for dialogue act modeling across a comprehensive set of different spoken and written conversations including: emails, forums, meetings, and phone conversations. To this aim, we compare the results of SVM-multiclass and two structured predictors namely SVMhmm and CRF algorithms. Extensive empirical results, across different conversational modalities, demonstrate the effectiveness of our SVM-hmm model for dialogue act recognition in conversations.
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