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Springer Nature Singapore
Reference109 articles.
1. Ang, J., Dhillon, R., Krupski, A., Shriberg, E., & Stolcke, A. (2002). Prosody-based automatic detection of annoyance and frustration in human-computer dialog. Paper presented in the Seventh International Conference on Spoken Language Processing.
2. Arroyo, I., Woolf, B., Cooper, D., Burleson, W., Muldner, K., & Christopherson, R. (2009). Emotion sensors go to school. In V. Dimitrova, R. Mizoguchi, B. du Boulay, & A. Graesser (Eds.), Proceedings of the International Conference on Artificial Intelligence in Education (pp. 17–24). IOS Press.
3. Asai, H., & Yamana, H. (2013). Detecting student frustration based on handwriting behavior. In Proceedings of the Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology (pp. 77–78). ACM.
4. Asteriadis, S., Karpouzis, K., & Kollias S. (2009). Feature extraction and selection for inferring user engagement in an HCI environment. In J. A. Jacko (Ed.), Human-Computer Interaction. New Trends. HCI 2009. Lecture Notes in Computer Science (Vol. 5610, pp. 22–29). Springer.
5. Backs, R. W., & Boucsein, W. (Eds.). (1999). Engineering psychophysiology. Erlbaum.