The long-term spectrum and perceived emotion
Speech Communication
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Predicting student emotions in computer-human tutoring dialogues
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
EmoReSp: an online emotion recognizer based on speech
Proceedings of the 11th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing on International Conference on Computer Systems and Technologies
Emotion recognition from speech by combining databases and fusion of classifiers
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
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We developed acoustic and lexical classifiers, based on a boosting algorithm, to assess the separability on arousal and valence dimensions in spontaneous emotional speech. The spontaneous emotional speech data was acquired by inviting subjects to play a first-person shooter video game. Our acoustic classifiers performed significantly better than the lexical classifiers on the arousal dimension. On the valence dimension, our lexical classifiers usually outperformed the acoustic classifiers. Finally, fusion between acoustic and lexical features on feature level did not always significantly improve classification performance.