Abstract—In this paper, we propose a new scheme for recognition of isolated words in Hindi Language speech, based on the Discrete Wavelet Transform. We first compute the Discrete Wavelet Transform coefficients of the speech signal. Then, Linear Predictive Coding Coefficients of the Discrete Wavelet Transform coefficients are calculated. Our scheme then uses K Means Algorithm on the obtained Linear Predictive Coding Coefficients to form a Vector Quantized codebook. Recognition of a spoken Hindi word is carried out by first calculating its Discrete Wavelet Transform Coefficients, followed by Linear Predictive Coding Coefficient calculation of these Coefficients, and then deciding in favor of the Hindi word whose corresponding centroid (in the Vector Quantized codebook) gives a minimum squared Euclidean distance error with respect to the word under test.
Index Terms—discrete wavelet transform; linear predicitive coding; vector quantization; hindi ;speech recognition
Shivesh Ranjan is with Electronics and Communication Engineering, Manipal Institute of Technology, Manipal 576104, India (email:srjn1@yahoo.com)
Cite: Shivesh Ranjan, "Exploring the Discrete Wavelet Transform as a Tool for Hindi Speech Recognition," International Journal of Computer Theory and Engineering vol. 2, no. 4, pp. 642-646, 2010.
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