Annotations for Dynamic Diagnosis of the Dialog State
Laurence Y. Devillers, Sophie Rosset, Hélène Bonneau-Maynard, Lori F Lamel · 2002
This paper describes recent work aimed at relating multi-level dialog annotations with meta-data annotations for a corpus of real humanhuman dialogs.This work is carried out in the context of the AMITIES project in which spoken dialog systems for call center services are being developed.A corpus of 100 agent-client dialogs have been annotated with three types of annotations.The first are utterance-level DAMSL-style dialogic labels.The second set of annotations applies to exchanges and takes into account of the dynamic aspect of dialog progress.Finally, 5 emotions types are annotated at the utterance level.Some of these multi-style annotations were used in a multiple linear regression analysis to predict dialog quality.The predictive factors are able to explain about 80% of the dialog accidents.