Topic-relevant Response Generation using Optimal Transport for an Open-domain Dialog System

Shuying Zhang, Tianyu Zhao, Tatsuya Kawahara

Abstract
Conventional neural generative models tend to generate safe and generic responses which have little connection with previous utterances semantically and would disengage users in a dialog system. To generate relevant responses, we propose a method that employs two types of constraints - topical constraint and semantic constraint. Under the hypothesis that a response and its context have higher relevance when they share the same topics, the topical constraint encourages the topics of a response to match its context by conditioning response decoding on topic words’ embeddings. The semantic constraint, which encourages a response to be semantically related to its context by regularizing the decoding objective function with semantic distance, is proposed. Optimal transport is applied to compute a weighted semantic distance between the representation of a response and the context. Generated responses are evaluated by automatic metrics, as well as human judgment, showing that the proposed method can generate more topic-relevant and content-rich responses than conventional models.
Anthology ID:
2020.coling-main.359
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Editors:
Donia Scott, Nuria Bel, Chengqing Zong
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
4067–4077
Language:
URL:
https://preview.aclanthology.org/icon-24-ingestion/2020.coling-main.359/
DOI:
10.18653/v1/2020.coling-main.359
Bibkey:
Cite (ACL):
Shuying Zhang, Tianyu Zhao, and Tatsuya Kawahara. 2020. Topic-relevant Response Generation using Optimal Transport for an Open-domain Dialog System. In Proceedings of the 28th International Conference on Computational Linguistics, pages 4067–4077, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Topic-relevant Response Generation using Optimal Transport for an Open-domain Dialog System (Zhang et al., COLING 2020)
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PDF:
https://preview.aclanthology.org/icon-24-ingestion/2020.coling-main.359.pdf
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