Improving Response Diversity through Commonsense-Aware Empathetic Response Generation

Tzu-Hsien Huang, Chia-Hui Chang

Abstract
Due to the lack of conversation practice, the main challenge for the second-language learners is speaking. Our goal is to develop a chatbot to encourage individuals to reflect, describe, analyse and communicate what they read as well as improve students’ English expression skills. In this paper, we exploit COMMET, an inferential commonsense knowledge generator, as the background knowledge to improve the generation diversity. We consider two approaches to increase the diversity of empathetic response generation. For nonpretrained models, We apply AdaLabel (Wang et al., 2021) to Commonsense-aware Empathetic model (Sabour et al., 2022) and improve Distinct-2 score from 2.99 to 4.08 on EMPATHETIC DIALOGUES (ED). Furthermore, we augment the pretrained BART model with various commonsense knowledge to generate more informative empathetic responses. Not only has the automatic evaluation of distinct-2 scores improved from 9.11 to 11.21, but the manual case study also shows that CE-BART significantly outperform CEM-AdaLabel.
Anthology ID:
2022.rocling-1.37
Volume:
Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)
Month:
November
Year:
2022
Address:
Taipei, Taiwan
Venue:
ROCLING
SIG:
Publisher:
The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
Note:
Pages:
299–306
Language:
Chinese
URL:
https://aclanthology.org/2022.rocling-1.37
DOI:
Bibkey:
Cite (ACL):
Tzu-Hsien Huang and Chia-Hui Chang. 2022. Improving Response Diversity through Commonsense-Aware Empathetic Response Generation. In Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022), pages 299–306, Taipei, Taiwan. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).
Cite (Informal):
Improving Response Diversity through Commonsense-Aware Empathetic Response Generation (Huang & Chang, ROCLING 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/starsem-semeval-split/2022.rocling-1.37.pdf
Data
ATOMIC, ConceptNet, EmpatheticDialogues
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