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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.
| Autorius: | R. D. Shah, Anilkumar Suthar, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2016 |
| Knygos puslapių skaičius: | 72 |
| ISBN-10: | 365993299X |
| ISBN-13: | 9783659932991 |
| Formatas: | 220 x 150 x 5 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Implementation of speech Emotion Recognition SVM kernel using MATLAB“
