Abstract
In this paper, a speech based emotion classification method is presented. Five basic human emotions including anger, fear, happiness, sadness and neutral are investigated. This paper explores use of Adaptive Neuro-Fuzzy Inference System (ANFIS) to design a classifier that can discriminate between various emotions. The results found to be are significant, both in cognitive science and in speech technology. For emotion recognition, we selected statistics of the pitch like, first and second formants, and Energy and speaking rate as the base features. ANFIS based recognizer is created. Ensembles of such recognizer are used as an important part of decision support system for prioritizing voice messages and assigning a proper agent to response the message. The recognition of emotion in human speech has gained increasing attention in recent years due to the wide variety of applications that benefit from such technology such as emotional robot or Computer system.
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Giripunje, S., Bawane, N. (2007). ANFIS Based Emotions Recognision in Speech. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_10
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DOI: https://doi.org/10.1007/978-3-540-74819-9_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74817-5
Online ISBN: 978-3-540-74819-9
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