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Performance Analysis of Emotion Recognition from Speech Using Combined Prosodic Features

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Study of human emotion is a highly complex task. Many ways are there like image analysis, brain signal analysis and voice analysis. Out of all these the emotion recognition from speech is a challenge. In this paper, authors have attempted with such task. Efficient feature based analysis is the major aim of this work. Standard prosodic features have been analyzed initially. Next to it, the combinations of the features have been verified in the neural network based classifier. It has found that the combined features have been shown better performance than the standard features. The results have been compared and shown in this work.
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Keywords: FEATURE COMBINATION; MLP; MSE; PROSODIC FEATURES

Document Type: Research Article

Publication date: February 1, 2016

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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