期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：4
出版社：S.S. Mishra
摘要：In human machine interaction automatic speech emotion recognition is yet challenging but important task which paid close attention in current research area. As the role of speech is an increase in human computer interface. Speech is attractive and effective medium due to its several features expressing attitude and emotions trough speech is possible. Here study is carried out using Gaussian mixture model and Hidden Markov model classifiers used for identification of five basic emotional states of speaker"s as anger, happiness, sad, surprise and neutral. in this paper to recognize emotions through speech various features such as prosodic features like pitch , energy and spectral features such as Mel frequency cepstrum coefficient were extracted and based on this features emotional classification and perfo rmance of classification using Gaussian mixture model and Hidden Markov Model is discussed.
关键词：Emotion recognition; Feature extraction; Gaussian mixture model; Hidden markov model; MFCC; ;spectral features and prosodic features
