ASU Electronic Theses and Dissertations
- 1 English
While discrete emotions like joy, anger, disgust etc. are quite popular, continuous emotion dimensions like arousal and valence are gaining popularity within the research community due to an increase in the availability of datasets annotated with these emotions. Unlike the discrete emotions, continuous emotions allow modeling of subtle and complex affect dimensions but are difficult to predict. Dimension reduction techniques form the core of emotion recognition systems and help create a new feature space that is more helpful in predicting emotions. But these techniques do not necessarily guarantee a better predictive capability as most of them are unsupervised, especially in …
- Lade, Prasanth, Panchanathan, Sethuraman, Davulcu, Hasan, et al.
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