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. IOS Press 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) |
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Division/Institute: |
School of Engineering and Computer Science > Institute for Patient-centered Digital Health School of Engineering and Computer Science |
Name: |
Denecke, Kerstin 0000-0001-6691-396X; May, Richard and Deng, Yihan |
ISSN: |
1879-8365 |
Publisher: |
IOS Press |
Language: |
English |
Submitter: |
Kerstin Denecke |
Date Deposited: |
26 Nov 2019 08:32 |
Last Modified: |
15 Jan 2024 15:18 |
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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