Affective computing
User Modeling and User-Adapted Interaction
Emotion Detection from Speech to Enrich Multimedia Content
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
ICALT '01 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Prosody based audiovisual coanalysis for coverbal gesture recognition
IEEE Transactions on Multimedia
Automatic inference of complex affective states
Computer Speech and Language
Emotion recognition from speech: a review
International Journal of Speech Technology
Computer Speech and Language
Hi-index | 0.00 |
This paper presents robust recognition of a subset of emotions by animated agents from salient spoken words. To develop and evaluate the model for each emotion from the chosen subset, both the prosodic and acoustic features were used to extract the intonational patterns and correlates of emotion from speech samples. The computed features were projected using a combination of linear projection techniques for compact and clustered representation of features. The projected features were used to build models of emotions using a set of classifiers organized in hierarchical fashion. The performances of the models were obtained using number of classifiers from the WEKA machine learning toolbox. Empirical analysis indicated that the lexical information computed from both the prosodic and acoustic features at word level yielded robust classification of emotions.