Automatic Emotion Classification of Malayalam Speech Using Artificial Neural Networks
نویسنده
چکیده
This paper deals with a novel approach towards Automatic Emotion Classification from human utterances. Discrete Wavelet Transform (DWT) is used for feature extraction from speech signals. Malayalam (One of the south Indian languages) is used for the experiment. We have used an elicited dataset of 500 utterances recorded from 10 male and 8 female speakers. Using Artificial Neural Network we have classified the four emotional classes such as neutral, happy, sad and anger correctly. A classification accuracy of 70% is obtained from this work.
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تاریخ انتشار 2010