Event Details

Lunch seminar with Dr Vittorio Tantucci

Abstract: Resonance occurs dynamically when interlocutors creatively coconstruct utterances that are formally and phonetically similar to the utterance of a prior speaker. In this study, we argue that such similarity can inform the machine learning prediction of linguistic and cross-cultural diversity. We compared two sets of 1,000 exchanges involving (dis)-agreement from the two balanced Callhome corpora of naturalistic interaction in Mandarin Chinese and American English. We found a correlation of overt use of pragmatic markers with resonance, indicating that priming does not occur as an exclusively implicit mechanism (as it is commonly held in the experimental literature e.g. Bock 1986; Bock et al. 2007), but naturalistically underpins dialogic engagement and cooperation among interactants. The applied results of this study can lead to a novel turn in AI research of conversational interfaces (McTear et al. 2016; Klopfenstein et al. 2017), as they reveal the fundamental role played cross-linguistically by resonance as a form of engagement of human-to-human interaction and the importance to address this mechanism in machine-to-human communication.