Hindi paired word recognition using probabilistic neural network Online publication date: Thu, 26-Aug-2010
by Dinesh Kumar Rajoriya, R.S. Anand, R.P. Maheshwari
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 1, No. 3, 2010
Abstract: Automatic speech recognition has been a subject of active research interest since last few decades. In the present paper, spoken Hindi (Indian national language) Paired Word Recognition (HPWR) has been examined with the help of intelligent hybrid computing scheme based on wavelet transform and Probabilistic Neural Network (PNN). This type of network is a combination of radial basis layer and a competitive transfer function layer, which picks up the maximum probabilities as a final result. For the experimental purpose, six hundred and fifty Hindi paired word samples from individuals with different gender and age groups have been recorded. Pre-processing procedure has been performed on the samples using accurate endpoint detection algorithm. For feature extraction of samples, wavelet transform has been used. PNN algorithm is used as a classifier. The proposed intelligent hybrid computing scheme based on wavelet-probabilistic neural network has produced practically good recognition rate.
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