@inproceedings{shum-etal-2020-sketch,
title = "Sketch-Fill-A-{R}: A Persona-Grounded Chit-Chat Generation Framework",
author = "Shum, Michael and
Zheng, Stephan and
Kryscinski, Wojciech and
Xiong, Caiming and
Socher, Richard",
editor = "Wen, Tsung-Hsien and
Celikyilmaz, Asli and
Yu, Zhou and
Papangelis, Alexandros and
Eric, Mihail and
Kumar, Anuj and
Casanueva, I{\~n}igo and
Shah, Rushin",
booktitle = "Proceedings of the 2nd Workshop on Natural Language Processing for Conversational AI",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.nlp4convai-1.14/",
doi = "10.18653/v1/2020.nlp4convai-1.14",
pages = "118--131",
abstract = "Human-like chit-chat conversation requires agents to generate responses that are fluent, engaging and consistent. We propose Sketch- Fill-A-R, a framework that uses a persona-memory to generate chit-chat responses in three phases. First, it generates dynamic sketch responses with open slots. Second, it generates candidate responses by filling slots with parts of its stored persona traits. Lastly, it ranks and selects the final response via a language model score. Sketch-Fill-A-R outperforms a state-of-the-art baseline both quantitatively (10-point lower perplexity) and qualitatively (preferred by 55{\%} in head-to-head single-turn studies and 20{\%} higher in consistency in multi-turn user studies) on the Persona-Chat dataset. Finally, we extensively analyze Sketch-Fill-A-R`s responses and human feedback, and show it is more consistent and engaging by using more relevant responses and questions."
}
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<abstract>Human-like chit-chat conversation requires agents to generate responses that are fluent, engaging and consistent. We propose Sketch- Fill-A-R, a framework that uses a persona-memory to generate chit-chat responses in three phases. First, it generates dynamic sketch responses with open slots. Second, it generates candidate responses by filling slots with parts of its stored persona traits. Lastly, it ranks and selects the final response via a language model score. Sketch-Fill-A-R outperforms a state-of-the-art baseline both quantitatively (10-point lower perplexity) and qualitatively (preferred by 55% in head-to-head single-turn studies and 20% higher in consistency in multi-turn user studies) on the Persona-Chat dataset. Finally, we extensively analyze Sketch-Fill-A-R‘s responses and human feedback, and show it is more consistent and engaging by using more relevant responses and questions.</abstract>
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%0 Conference Proceedings
%T Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework
%A Shum, Michael
%A Zheng, Stephan
%A Kryscinski, Wojciech
%A Xiong, Caiming
%A Socher, Richard
%Y Wen, Tsung-Hsien
%Y Celikyilmaz, Asli
%Y Yu, Zhou
%Y Papangelis, Alexandros
%Y Eric, Mihail
%Y Kumar, Anuj
%Y Casanueva, Iñigo
%Y Shah, Rushin
%S Proceedings of the 2nd Workshop on Natural Language Processing for Conversational AI
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F shum-etal-2020-sketch
%X Human-like chit-chat conversation requires agents to generate responses that are fluent, engaging and consistent. We propose Sketch- Fill-A-R, a framework that uses a persona-memory to generate chit-chat responses in three phases. First, it generates dynamic sketch responses with open slots. Second, it generates candidate responses by filling slots with parts of its stored persona traits. Lastly, it ranks and selects the final response via a language model score. Sketch-Fill-A-R outperforms a state-of-the-art baseline both quantitatively (10-point lower perplexity) and qualitatively (preferred by 55% in head-to-head single-turn studies and 20% higher in consistency in multi-turn user studies) on the Persona-Chat dataset. Finally, we extensively analyze Sketch-Fill-A-R‘s responses and human feedback, and show it is more consistent and engaging by using more relevant responses and questions.
%R 10.18653/v1/2020.nlp4convai-1.14
%U https://aclanthology.org/2020.nlp4convai-1.14/
%U https://doi.org/10.18653/v1/2020.nlp4convai-1.14
%P 118-131
Markdown (Informal)
[Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework](https://aclanthology.org/2020.nlp4convai-1.14/) (Shum et al., NLP4ConvAI 2020)
ACL