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Ramón Granell, Stephen Pulman, Carlos D. Martínez-Hinarejos, José-Miguel Benedí. Dialogue Act Tagging and Segmentation with a Single Perceptron. Interspeech: 11th Annual Conference of the International Speech Communication Association, 2010. pp. 3074-3077.

In this paper we present a simultaneous automatic Dialogue Act (DA) tagger and segmenter. The model employed is based on the well-known single layer perceptron algorithm used success- fully in other Computational Linguistic tasks. A decoding pro- cess was developed for searching the sequence of segments and DA tags from all the possible exponential possibilities. A set of features based on combination of words and DA tags were empirically selected. Models were tested over transcriptions of two corpora of dialogues (Switchboard and Dihana) and tran- scriptions and ASR output of a third corpus composed by meet- ings (AMI corpus). The results obtained for such a simple but powerful model are for some of the evaluation metrics equal or better than much more complex models presented in recent studies for the same experiments.