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Dimensionality of dialogue act tagsets

An empirical analysis of large corpora

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Abstract

This article compares one-dimensional and multi-dimensional dialogue act tagsets used for automatic labeling of utterances. The influence of tagset dimensionality on tagging accuracy is first discussed theoretically, then based on empirical data from human and automatic annotations of large scale resources, using four existing tagsets: damsl, swbd-damsl, icsi-mrda and maltus. The Dominant Function Approximation proposes that automatic dialogue act taggers could focus initially on finding the main dialogue function of each utterance, which is empirically acceptable and has significant practical relevance.

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Acknowledgements

This work has been supported by the Swiss National Science Foundation within the IM2 NCCR on Interactive Multimodal Information Management \(({\tt www.im2.ch}).\) The author would like to thank Jean Carletta, Hannah Carvey, Alex Clark, Liz Shriberg, Sandrine Zufferey, and the anonymous reviewers for their helpful comments on this paper.

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  1. IDIAP Research Institute, Centre du Parc, Av. des Prés-Beudin 20, P.O. Box 592, 1920, Martigny, Switzerland

    Andrei Popescu-Belis

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  1. Andrei Popescu-Belis
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Correspondence to Andrei Popescu-Belis.

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Popescu-Belis, A. Dimensionality of dialogue act tagsets. Lang Resources & Evaluation 42, 99–107 (2008). https://doi.org/10.1007/s10579-008-9063-y

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  • DOI: https://doi.org/10.1007/s10579-008-9063-y

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