A Co-Attentive Cross-Lingual Neural Model for Dialogue Breakdown Detection

Qian Lin, Souvik Kundu, Hwee Tou Ng

Abstract
Ensuring smooth communication is essential in a chat-oriented dialogue system, so that a user can obtain meaningful responses through interactions with the system. Most prior work on dialogue research does not focus on preventing dialogue breakdown. One of the major challenges is that a dialogue system may generate an undesired utterance leading to a dialogue breakdown, which degrades the overall interaction quality. Hence, it is crucial for a machine to detect dialogue breakdowns in an ongoing conversation. In this paper, we propose a novel dialogue breakdown detection model that jointly incorporates a pretrained cross-lingual language model and a co-attention network. Our proposed model leverages effective word embeddings trained on one hundred different languages to generate contextualized representations. Co-attention aims to capture the interaction between the latest utterance and the conversation history, and thereby determines whether the latest utterance causes a dialogue breakdown. Experimental results show that our proposed model outperforms all previous approaches on all evaluation metrics in both the Japanese and English tracks in Dialogue Breakdown Detection Challenge 4 (DBDC4 at IWSDS2019).
Anthology ID:
2020.coling-main.371
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
4201–4210
Language:
URL:
https://aclanthology.org/2020.coling-main.371
DOI:
10.18653/v1/2020.coling-main.371
Bibkey:
Cite (ACL):
Qian Lin, Souvik Kundu, and Hwee Tou Ng. 2020. A Co-Attentive Cross-Lingual Neural Model for Dialogue Breakdown Detection. In Proceedings of the 28th International Conference on Computational Linguistics, pages 4201–4210, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
A Co-Attentive Cross-Lingual Neural Model for Dialogue Breakdown Detection (Lin et al., COLING 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.coling-main.371.pdf
Code
 nusnlp/cxm
PDF Search Code