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Emotion Recognition From Speech Using Perceptual Filter and Neural Network

Emotion Recognition From Speech Using Perceptual Filter and Neural Network

Revathi A., Sasikaladevi N.
Copyright: © 2020 |Pages: 14
ISBN13: 9781799811596|ISBN10: 179981159X|ISBN13 Softcover: 9781799811602|EISBN13: 9781799811619
DOI: 10.4018/978-1-7998-1159-6.ch004
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MLA

A., Revathi, and Sasikaladevi N. "Emotion Recognition From Speech Using Perceptual Filter and Neural Network." Neural Networks for Natural Language Processing, edited by Sumathi S. and Janani M., IGI Global, 2020, pp. 78-91. https://doi.org/10.4018/978-1-7998-1159-6.ch004

APA

A., R. & N., S. (2020). Emotion Recognition From Speech Using Perceptual Filter and Neural Network. In S. S. & J. M. (Eds.), Neural Networks for Natural Language Processing (pp. 78-91). IGI Global. https://doi.org/10.4018/978-1-7998-1159-6.ch004

Chicago

A., Revathi, and Sasikaladevi N. "Emotion Recognition From Speech Using Perceptual Filter and Neural Network." In Neural Networks for Natural Language Processing, edited by Sumathi S. and Janani M., 78-91. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-1159-6.ch004

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Abstract

This chapter on multi speaker independent emotion recognition encompasses the use of perceptual features with filters spaced in Equivalent rectangular bandwidth (ERB) and BARK scale and vector quantization (VQ) classifier for classifying groups and artificial neural network with back propagation algorithm for emotion classification in a group. Performance can be improved by using the large amount of data in a pertinent emotion to adequately train the system. With the limited set of data, this proposed system has provided consistently better accuracy for the perceptual feature with critical band analysis done in ERB scale.

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