The week's pick
Reseach Article
Speech Emotion Recognition Using Support Vector Machine
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 20 |
| Year of Publication: 2010 |
| Authors: Yashpalsing Chavhan, M. L. Dhore, Pallavi Yesaware |
10.5120/431-636
|
Yashpalsing Chavhan, M. L. Dhore, Pallavi Yesaware . Speech Emotion Recognition Using Support Vector Machine. International Journal of Computer Applications. 1, 20 ( February 2010), 6-9. DOI=10.5120/431-636
Abstract
Automatic Speech Emotion Recognition (SER) is a current research topic in the field of Human Computer Interaction (HCI) with wide range of applications. The speech features such as, Mel Frequency cepstrum coefficients (MFCC) and Mel Energy Spectrum Dynamic Coefficients (MEDC) are extracted from speech utterance. The Support Vector Machine (SVM) is used as classifier to classify different emotional states such as anger, happiness, sadness, neutral, fear, from Berlin emotional database. The LIBSVM is used for classification of emotions. It gives 93.75% classification accuracy for Gender independent case 94.73% for male and 100% for female speech.
References
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