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• W2184921380 abstract "In this paper Emotion recognition often refers to the science and technology of developing algorithms and implementing them on machines to recognize the Emotions. Research in the field of Emotion recognition has made a number of significant advances in the last two decades. emotion recognition results from speech signals, with particular focus on extracting emotion features from the short utterances typical of Interactive Voice Response (IVR) applications. This paper proposes a new approach to emotion recognition, making use of two of the emotional dimensions, arousal and valence and their relationship with different kind of features. The classification of various types of emotions such as sadness, boredom, happy, and cold anger. Emotion has used a dimensional theory proposed a dimensional model of emotion that is founded on a biological organization of appetitive and defensive motivational connections in the human cognitive system. We use a database from the Linguistic Data Consortium at University of Pennsylvania, which is recorded by 8 actors expressing 15 emotions. Results indicate that hot anger and neutral utterances can be distinguished with over 90% accuracy. We show results from recognizing other emotions. We also illustrate which emotions can be clustered together using the selected prosodic features." @default.
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• W2184921380 date "2005-01-01" @default.
• W2184921380 modified "2023-09-24" @default.
• W2184921380 title "Emotion Recognition System for English Dialects using Dimensional Theory" @default.
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