Personalized Response Generation via Generative Split Memory Network

Yuwei Wu, Xuezhe Ma, Diyi Yang


Abstract
Despite the impressive successes of generation and dialogue systems, how to endow a text generation system with particular personality traits to deliver more personalized responses remains under-investigated. In this work, we look at how to generate personalized responses for questions on Reddit by utilizing personalized user profiles and posting histories. Specifically, we release an open-domain single-turn dialog dataset made up of 1.5M conversation pairs together with 300k profiles of users and related comments. We then propose a memory network to generate personalized responses in dialogue that utilizes a novel mechanism of splitting memories: one for user profile meta attributes and the other for user-generated information like comment histories. Experimental results show the quantitative and qualitative improvements of our simple split memory network model over the state-of-the-art response generation baselines.
Anthology ID:
2021.naacl-main.157
Volume:
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
June
Year:
2021
Address:
Online
Editors:
Kristina Toutanova, Anna Rumshisky, Luke Zettlemoyer, Dilek Hakkani-Tur, Iz Beltagy, Steven Bethard, Ryan Cotterell, Tanmoy Chakraborty, Yichao Zhou
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1956–1970
Language:
URL:
https://aclanthology.org/2021.naacl-main.157
DOI:
10.18653/v1/2021.naacl-main.157
Bibkey:
Cite (ACL):
Yuwei Wu, Xuezhe Ma, and Diyi Yang. 2021. Personalized Response Generation via Generative Split Memory Network. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1956–1970, Online. Association for Computational Linguistics.
Cite (Informal):
Personalized Response Generation via Generative Split Memory Network (Wu et al., NAACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.naacl-main.157.pdf
Optional supplementary data:
 2021.naacl-main.157.OptionalSupplementaryData.pdf
Video:
 https://aclanthology.org/2021.naacl-main.157.mp4
Code
 willyoung2017/per-chat
Data
PECPersonalDialog