Understanding User Utterances in a Dialog System for Caregiving

Yoshihiko Asao, Julien Kloetzer, Junta Mizuno, Dai Saiki, Kazuma Kadowaki, Kentaro Torisawa


Abstract
A dialog system that can monitor the health status of seniors has a huge potential for solving the labor force shortage in the caregiving industry in aging societies. As a part of efforts to create such a system, we are developing two modules that are aimed to correctly interpret user utterances: (i) a yes/no response classifier, which categorizes responses to health-related yes/no questions that the system asks; and (ii) an entailment recognizer, which detects users’ voluntary mentions about their health status. To apply machine learning approaches to the development of the modules, we created large annotated datasets of 280,467 question-response pairs and 38,868 voluntary utterances. For question-response pairs, we asked annotators to avoid direct “yes” or “no” answers, so that our data could cover a wide range of possible natural language responses. The two modules were implemented by fine-tuning a BERT model, which is a recent successful neural network model. For the yes/no response classifier, the macro-average of the average precisions (APs) over all of our four categories (Yes/No/Unknown/Other) was 82.6% (96.3% for “yes” responses and 91.8% for “no” responses), while for the entailment recognizer it was 89.9%.
Anthology ID:
2020.lrec-1.82
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
653–661
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.82
DOI:
Bibkey:
Cite (ACL):
Yoshihiko Asao, Julien Kloetzer, Junta Mizuno, Dai Saiki, Kazuma Kadowaki, and Kentaro Torisawa. 2020. Understanding User Utterances in a Dialog System for Caregiving. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 653–661, Marseille, France. European Language Resources Association.
Cite (Informal):
Understanding User Utterances in a Dialog System for Caregiving (Asao et al., LREC 2020)
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PDF:
https://aclanthology.org/2020.lrec-1.82.pdf