2018/09/30 by Yujie Xing, Raquel Fernández, Xing, Yujie +1
Computer Science · Psychology · #Mental Health via Writing #Speech and dialogue systems #Topic Modeling #cs.CL
paper · pdf · doi:10.48550/arxiv.1810.00472
To appear in the Proceedings of the 11th International Conference on Natural Language Generation (INLG-2018)
arxiv created 2018/09/30 · arxiv updated 2018/10/02
Stylistic variation is critical to render the utterances generated by conversational agents natural and engaging. In this paper, we focus on sequence-to-sequence models for open-domain dialogue response generation and propose a new method to evaluate the extent to which such models are able to generate responses that reflect different personality traits.