Year: 2010
Type: article
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..
DOI: 10.5120/431-636
Institution: Vishwakarma Institute of Technology
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W2159408788