Implementation of speech Emotion Recognition SVM kernel using MATLAB

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Details

Speech emotion recognition is a very important speech technology. an extensive research is made by using different speech information and signal for human emotion recognition. We develop a speech-based emotion classification method using SVM by using standard EMA database. In order to achieve a high emotion classification accuracy we have used SVM with kernel functions, From result obtained by using different kernels functions . From result we conclude that RBF Kernel function in which we got 94.96%, 96.02%, 98.96%, 98.76% accuracy results for Angry, Happy, Neutral, Sad emotions respectively using energy, formant and MFCC features. Our result shows that classification accuracy will be improve using kernel functions.

Autorentext

Ms. R. D. Shah is a Post-Graduate Student in Electronics & Communication Engg.(CSE) & Dr. Anilkumar C. Suthar is a Guide and Director of LJIET.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783659932991
    • Genre Electrical Engineering
    • Sprache Englisch
    • Anzahl Seiten 72
    • Herausgeber LAP LAMBERT Academic Publishing
    • Größe H220mm x B150mm x T5mm
    • Jahr 2016
    • EAN 9783659932991
    • Format Kartonierter Einband
    • ISBN 365993299X
    • Veröffentlichung 09.08.2016
    • Titel Implementation of speech Emotion Recognition SVM kernel using MATLAB
    • Autor R. D. Shah , Anilkumar Suthar
    • Gewicht 125g

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