Emotion Recognition - A Tool to Improve Meeting Experience for Visually Impaired
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Author / Producer
Date
2022
Publication Type
Conference Paper
ETH Bibliography
yes
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Abstract
Facial expressions play an important role in human communication since they enrich spoken information and help convey additional sentiments e.g. mood. Among others, they non-verbally express a partner’s agreement or disagreement to spoken information. Further, together with the audio signal, humans can even detect nuances of changes in a person’s mood. However, facial expressions remain inaccessible to the blind and visually impaired, and also the voice signal alone might not carry enough mood information. Emotion recognition research mainly focused on detecting one of seven emotion classes. Such emotions are too detailed, and having an overall impression of primary emotional states such as positive, negative, or neutral is more beneficial for the visually impaired person in a lively discussion within a team. Thus, this paper introduces an emotion recognition system that allows a real-time detection of the emotions “agree”, “neutral”, and “disagree”, which are seen as the most important ones during a lively discussion. The proposed system relies on a combination of neural networks that allow extracting emotional states while leveraging the temporal information from videos.
Permanent link
Publication status
published
External links
Book title
Computers Helping People with Special Needs
Journal / series
Volume
13341
Pages / Article No.
305 - 312
Publisher
Springer
Event
Joint International Conference on Digital Inclusion, Assistive Technology & Accessibility (ICCHP-AAATE 2022),
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Emotion recognition; neural networks; Non-verbal communication
Organisational unit
08844 - Kunz, Andreas (Tit.-Prof.) / Kunz, Andreas (Tit.-Prof.)