Speech Emotion Recognition using Support Vector Machine

Yashpalsing Chavhan · Manikrao Laxmanrao Dhore · Pallavi Yesaware

139 citations0/0 files storedInternational Journal of Computer Applications

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Emotion and Mood Recognition Speech Recognition and Synthesis Speech and Audio Processing

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..

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2001Emotion recognition in human-computer interaction 2005A database of German emotional speech 2005Speech emotion recognition based on HMM and SVM

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