Frame-by-frame Phoneme Classification Using Mlp
نویسنده
چکیده
In this paper, we present some practical experiments for continuous speech frame-by-frame phoneme classification using Multi Layer Perceptron (MLP) neural networks. We used to train and test our software application, the the OASIS Numbers speech database. In our experiments, we tried to classify all the existing 32 phonemes together, from OASIS Numbers database dictionary. We also used different MLP configurations to compare the achieved results. For classification, we used 13 MFCC coefficients and their first and second order derivatives (delta parameters) extracted from speech signal using our Matlab based feature extractor software application.
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