This paper presents a real-time emotion recognition concept of voice streams. A comprehensive solution based on Bayesian Quadratic Discriminate Classifier(QDC) is developed. The developed system supports Advanced Driver Assistance Systems (ADAS) to detect the mood of the driver based on the fact that aggressive behavior on road leads to traffic accidents. We use only 12 features to classify between 5 different classes of emotions. We illustrate that the extracted emotion features are highly overlapped and how each emotion class is effecting the recognition ratio. Finally, we show that the Bayesian Quadratic Discriminate Classifier is an appropriate solution for emotion detection systems, where a real-time detection is deeply needed with a low number of features.

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http://dx.doi.org/10.1007/978-3-642-24806-1_21 under the license http://www.springer.com/tdm
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Published on 01/01/2011

Volume 2011, 2011
DOI: 10.1007/978-3-642-24806-1_21
Licence: CC BY-NC-SA license

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