Malay syllable recognition based on multilayer perceptron and dynamic time warping

Attempts at creating and using the first database for Malay syllables are presented. The speech vocabulary consists of 16 Malay syllables which are initialized with plosives and followed by succeeding vowels. The paper investigates the use of multilayer perceptron (MLP) and dynamic time warping (DTW) in recognizing these Malay syllable sounds that are quite similar to each other. From the experimental results, DTW and MLP achieved 77.09% and 90.82% respectively in overall average recognition rate.