Wavelet Based Feature Extraction for The Indonesian CV Syllables Sound

Abstract

This paper proposes the comb ined methods of Wavelet Transform (WT) and Euclidean Distance (ED) to estimate the expected value of the possib ly feature vector of Indonesian syllab les. This research aims to find the b est properties in effectiveness and efficiency on performing feature extraction of each syllab le sound to b e applied in the speech recognition systems. This proposed approach which is the state-of-the-art of the previous study consist of three main phase. In the first phase, the speech signal is segmented and normalized. In the second phase, the signal is transformed into frequency domain b y using the WT. In the third phase, to estimate the expected feature vector, the ED algorithm is used. Th e result shows the list of features of each syllab les can b e used for the next research, and some recommendations on the most effective and efficient WT to b e used in performing syllab le sound recognition.