Abstract
This work aims at characterising verbal alignment processes for improving virtual agent communicative capabilities. We propose computationally inexpensive measures of verbal alignment based on expression repetition in dyadic textual dialogues. Using these measures, we present a contrastive study between Human-Human and Human-Agent dialogues on a negotiation task. We exhibit quantitative differences in the strength and orientation of verbal alignment showing the ability of our approach to characterise important aspects of verbal alignment.
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CITATION STYLE
Duplessis, G. D., Clavel, C., & Landragin, F. (2017). Automatic measures to characterise verbal alignment in human-agent interaction. In SIGDIAL 2017 - 18th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Proceedings of the Conference (pp. 71–81). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-5510
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