Abstract
The paper presents the comparison of scores for emotional state automatic recognition tests. 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 features based on F0, intensity, formants and LPC coefficients were applied in seven chosen classifiers. The highest scores were reached for SVM, ANN and DTC classifiers.
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Staroniewicz, P. (2011). Automatic Recognition of Emotional State in Polish Speech. In: Esposito, A., Esposito, A.M., Martone, R., Müller, V.C., Scarpetta, G. (eds) Toward Autonomous, Adaptive, and Context-Aware Multimodal Interfaces. Theoretical and Practical Issues. Lecture Notes in Computer Science, vol 6456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18184-9_30
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DOI: https://doi.org/10.1007/978-3-642-18184-9_30
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