Abstract
The paper presents the comparison of human (listeners test) and automatic (SVM classifier) speech emotion recognition. The database of Polish emotional speech used during tests includes recordings of six acted emotional states (anger, sadness, happiness, fear, disgust, surprise) and the neutral state of 13 amateur speakers (2118 utterances). The automatic classifier used the set of 31 attribute evaluated features, C-SVC algorithm with the Gaussian Radial Basis Function. The mean overall score for human recognition (57.25%) turned out to be lower than for automatic recognition (64.77%).
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Staroniewicz, P. (2009). Recognition of Emotional State in Polish Speech - Comparison between Human and Automatic Efficiency. In: Fierrez, J., Ortega-Garcia, J., Esposito, A., Drygajlo, A., Faundez-Zanuy, M. (eds) Biometric ID Management and Multimodal Communication. BioID 2009. Lecture Notes in Computer Science, vol 5707. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04391-8_5
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DOI: https://doi.org/10.1007/978-3-642-04391-8_5
Publisher Name: Springer, Berlin, Heidelberg
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