DINASTI : Dialogues with a Negotiating Appointment Setting Interface
Abstract
This paper describes the DINASTI (DIalogues with a Negotiating Appointment SeTting Interface) corpus, which is composed of 1734
dialogues with the French spoken dialogue system NASTIA (Negotiating Appointment SeTting InterfAce). NASTIA is a reinforcement
learning-based system. The DINASTI corpus was collected while the system was following a uniform policy. Each entry of the corpus
is a system-user exchange annotated with 120 automatically computable features.The corpus contains a total of 21587 entries, with 385
testers. Each tester performed at most five scenario-based interactions with NASTIA. The dialogues last an average of 10.82 dialogue
turns, with 4.45 reinforcement learning decisions. The testers filled an evaluation questionnaire after each dialogue. The questionnaire
includes three questions to measure task completion. In addition, it comprises 7 Likert-scaled items evaluating several aspects of the
interaction, a numerical overall evaluation on a scale of 1 to 10, and a free text entry. Answers to this questionnaire are provided with
DINASTI. This corpus is meant for research on reinforcement learning modelling for dialogue management.