Towards Emotion-Sensitive Conversational User Interfaces in Healthcare Applications

Denecke, Kerstin; May, Richard; Deng, Yihan (2019). Towards Emotion-Sensitive Conversational User Interfaces in Healthcare Applications Studies in health technology and informatics, 264, pp. 1164-1168. 10.3233/SHTI190409

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Perception of emotions and adequate responses are key factors of a successful conversational agent. However, determining emotions in a healthcare setting depends on multiple factors such as context and medical condition. Given the increase of interest in conversational agents integrated in mobile health applications, our objective in this work is to introduce a concept for analyzing emotions and sentiments expressed by a person in a mobile health application with a conversational user interface. The approach bases upon bot technology (Synthetic intelligence markup language) and deep learning for emotion analysis. More specifically, expressions referring to sentiments or emotions are classified along seven categories and three stages of strengths using treebank annotation and recursive neural networks. The classification result is used by the chatbot for selecting an appropriate response. In this way, the concerns of a user can be better addressed. We describe three use cases where the approach could be integrated to make the chatbot emotion-sensitive.

Item Type:

Journal Article (Original Article)

Division/Institute:

Engineering and Information Technology > Institut für Medizininformatik I4MI
Engineering and Information Technology

Name:

Denecke, Kerstin;
May, Richard and
Deng, Yihan

ISSN:

1879-8365

Language:

English

Submitter:

Kerstin Denecke

Date Deposited:

26 Nov 2019 08:32

Last Modified:

29 Jan 2020 11:14

Publisher DOI:

10.3233/SHTI190409

PubMed ID:

31438108

Uncontrolled Keywords:

Conversational user interface deep learning natural language processing sentiment analysis

ARBOR DOI:

10.24451/arbor.9016

URI:

https://arbor.bfh.ch/id/eprint/9016

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