Topic-Aware Response Generation in Task-Oriented Dialogue with Unstructured Knowledge Access

Yue Feng, Gerasimos Lampouras, Ignacio Iacobacci

Abstract
To alleviate the problem of structured databases’ limited coverage, recent task-oriented dialogue systems incorporate external unstructured knowledge to guide the generation of system responses. However, these usually use word or sentence level similarities to detect the relevant knowledge context, which only partially capture the topical level relevance. In this paper, we examine how to better integrate topical information in knowledge grounded task-oriented dialogue and propose “Topic-Aware Response Generation” (TARG), an end-to-end response generation model. TARG incorporates multiple topic-aware attention mechanisms to derive the importance weighting scheme over dialogue utterances and external knowledge sources towards a better understanding of the dialogue history. Experimental results indicate that TARG achieves state-of-the-art performance in knowledge selection and response generation, outperforming previous state-of-the-art by 3.2, 3.6, and 4.2 points in EM, F1 and BLEU-4 respectively on Doc2Dial, and performing comparably with previous work on DSTC9; both being knowledge-grounded task-oriented dialogue datasets.
Anthology ID:
2022.findings-emnlp.533
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2022
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
7199–7211
Language:
URL:
https://aclanthology.org/2022.findings-emnlp.533
DOI:
10.18653/v1/2022.findings-emnlp.533
Bibkey:
Cite (ACL):
Yue Feng, Gerasimos Lampouras, and Ignacio Iacobacci. 2022. Topic-Aware Response Generation in Task-Oriented Dialogue with Unstructured Knowledge Access. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 7199–7211, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
Topic-Aware Response Generation in Task-Oriented Dialogue with Unstructured Knowledge Access (Feng et al., Findings 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/naacl-24-ws-corrections/2022.findings-emnlp.533.pdf
PDF Search