Abstract
In this paper, a speech emotion recognition system and its application for call-center system is proposed. In general, a speech captured by cellular-phone contains noises due to the mobile network and speaker environment. In order to minimize the effect of these noises and so improve the system performance, we employ a simple MA filter at the feature domain. Two pattern classification methods, k-NN and SVM with probability estimate, are compared to distinguish two emotional states- neutral and anger- for call-center application. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance and it promises the feasibility of the agent for mobile communication services.
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Yoon, WJ., Park, KS. (2007). A Study of Emotion Recognition and Its Applications. In: Torra, V., Narukawa, Y., Yoshida, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2007. Lecture Notes in Computer Science(), vol 4617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73729-2_43
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DOI: https://doi.org/10.1007/978-3-540-73729-2_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73728-5
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