Abstract

This paper investigates proactivity, a characteristic phenomenon of collaborative human-human interaction, where a participant in the dialogue offers the addressee some useful and not explicitly requested information. More precisely, a proactive behaviour is: (i) self-prompted and not simply reactive, that is, the speaker does not act merely in response to the requests the other participant has made; (ii) somehow effective for the achievement of the dialogue goal, since the speaker has a long-term, goal-directed behaviour that predicts future states and needs. Proactivity has been poorly investigated from a theoretical point of view, and there is a general need of empirical data for both quantitative and qualitative research. The paper provides an extensive analysis of proactivity in several human-human task-oriented dialogic corpora, selected with different characteristics, including chat exchanges and telephone calls, collection modalities such as natural setting and Wizard of Oz, and two languages, Italian and English. The main result is the D-Pro Corpus, a new resource manually annotated at the utterance level with proactivity and dialogue acts, which allows to investigate proactivity in the context of task-oriented dialogues. There are several findings from our empirical investigation of proactivity: (i) we find that about 20% of turns in our corpus are proactive turns, showing that this is a very diffused and relevant phenomenon; (ii) we confirm the non-reactive nature of proactivity, highlighting the presence of a pattern where a turn in the dialogue triggers a reaction in a following turn and a proactive utterance is then added to the turn; (iii) we show that only a limited number of dialogue acts are actually involved in expressing proactivity, and we discuss the theoretical implications of this finding; (iv) we empirically confirm that proactivity has a crucial role in recovering from goal-failure situations, contributing to the effectiveness of the whole dialogue; (v) we support the intuition of a non-uniform distribution of proactive utterances throughout the dialogue. Our empirical findings and the D-Pro Corpus provide relevant insights for deeper theoretical investigations, as well as crucial resources for improving proactivity in current task-oriented dialogue systems.