Speech Emotion Recognition by Gaussian Mixture Model
نویسنده
چکیده
In the field of human computer interaction automatic speech emotion recognition is a current research topic. Emotion recognition in speech is a challenging problem because it is unclear that which features are effective for speech emotion recognition. In this paper we proposed an approach in which we extract the features of energy, spectral and acoustic domains and then merging these features by Principal Component Analysis(PCA) and then we get a new hybrid feature that feed into a Gaussian mixture model with kernel approach and analysis its accuracy, precision, recall and ROC curve.
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