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Classification of Emotional Content of Sighs in Dyadic Human Interactions
Abstract
Emotions are an important part of human communication and are expressed both verbally and non-verbally. Common nonverbal vocalizations such as laughter, cries and sighs carry important emotional content in conversations. Sighs often are associated with negative emotion. In this work, we show that emotional sighs exist along both ends of the valence axis (positive-emotion vs. negative-emotion sighs) in spontaneous affective dialogs and that they have certain distinct multimodal characteristics. Classification results show that it is possible to differentiate between the two types of emotionally valenced sighs, using a combination of acoustic and gestural features with an overall unweighted accuracy of 58.26%.
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Motion Capture Markers Placement
Motion Capture Markers Placement
Keywords
nonverbal vocalizations | multimodal fusion | support vector machine
Authors
Publication Date
2012/03/25
Conference
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
DOI
10.1109/icassp.2012.6288365
Publisher
IEEE