Malayalam Vowel Recognition Based on Linear Predictive Coding Parameters and k-NN Algorithm
T. M. Thasleema, V. Kabeer, N. K. Narayanan · 2007
Accurate vowel recognition forms the backbone of most successful speech recognition systems. A collection of techniques exists to extract the relevant features from the steady-state regions of the vowels both in time as well as in frequency domains. In this paper we present a novel and accurate feature extraction technique for recognizing Malayalam spoken vowels based on Linear Predictive Coding method and compared the result with wavelet packet decomposition method. Recognition is performed using k-NN pattern classifier. The classification is conducted for 5 Malayalam vowel sounds using training and test set consisting of 50 ( 10 from each class) samples each. The overall recognition accuracy obtained for the vowel using LPC feature extraction method is 94%. The proposed method is efficient and computationally less expensive. The experimental results demonstrate the efficiency of the proposed algorithm