DIALOGUE-ACT TAGGING USING SMART FEATURE SELECTION; RESULTS ON MULTIPLE CORPORA

Abstract
This paper presents an overview of our on-going work on dialogue-act classification. Results are presented on the ICSI, switchboard, and on a selection of the AMI corpus, setting a baseline for forthcoming research. For these corpora the best accuracy scores obtained are 89.27%, 65.68% and 59.76%, respectively. We introduce a smart compression technique for feature selection and compare the performance from a subset of the AMI transcriptions with AMI-ASR output for the same subset.

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