Deep neural network-based phoneme classification of standard Khasi dialect in continuous speech
by Bronson Syiem; L. Joyprakash Singh
International Journal of Applied Pattern Recognition (IJAPR), Vol. 6, No. 1, 2019

Abstract: In this paper, deep neural network (DNN) is used to classify phonemes of the standard Khasi dialect which is one of the commonly used dialects in the state of Meghalaya. For this, clean speech data were recorded in the laboratory from native speakers. In the proposed system, a monophone and a triphone hidden Markov models (HMMs) were also built to compare the results obtained. Our finding showed that DNN outperformed the classification over the other two models with a classification accuracy of 89.70%.

Online publication date: Thu, 26-Dec-2019

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