Abstract
Dialogue act taxonomies, such as those of DAMSL, DiAML or the HCRC dialogue structure, can be incorporated into a larger meta-model by breaking down their labels into primitive functional features. Doing so enables the re-exploitation of annotated data for automatic dialogue act recognition tasks across taxonomies, i.e. it gives us the means to make a classifier learn from data annotated according to taxonomies different from the target taxonomy. We propose a meta-model covering several well-known taxonomies of dialogue acts, and we demonstrate its usefulness for the task of cross-taxonomy dialogue act recognition.
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Notes
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i.e. It can’t discuss the planning of an action, such as the utterance “ok I’ll reboot my computer then”.
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If the taxonomy is “flat”, i.e. not hierarchical, all labels are treated as siblings.
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While not specified in the guidelines, Inform and in some cases Answer could arguably be considered a parent of all feedback labels.
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Salim, S., Hernandez, N., Morin, E. (2018). Dialogue Act Taxonomy Interoperability Using a Meta-model. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2017. Lecture Notes in Computer Science(), vol 10761. Springer, Cham. https://doi.org/10.1007/978-3-319-77113-7_24
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