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Nadya Amalia
Lambung Mangkurat University
Computer Science & IT Electrical & Electronics Engineering

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Indonesian Vowel Recognition Using Artificial Neural Network Based On the Wavelet Features Nadya Amalia; Arfan E. Fahrudi; Amar V. Nasrulloh
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 2: April 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

There are six vowels in Indonesian language, i.e. /a/, /i/, /u/, /e/, /ə/ and /o/. This paper presents Indonesian vowel recognition using artificial neural network (ANN) based on the wavelet features. The wavelet features were the wavelet coefficients of vowel signal which were extracted by using discrete wavelet transform (DWT). Vowel samples were recorded from native Indonesian speakers, 10 males and 10 females. Db4 and sym4 were used as the mother wavelet, and decomposition level 2, 4 and 6 were implemented for each vowel sample. Minimum, maximum, mean and standard deviation value of the wavelet coefficients then were used as input vectors of ANN with 2 hidden layers. Backpropagation algorithm was used to training the ANN. From the experimental results, an overall recognition rate of 70.83% could be achieved. In case of male speakers the highest recognition rate is 90% and in case of female speakers the highest recognition rate is 80%.DOI:http://dx.doi.org/10.11591/ijece.v3i2.2325
Co-Authors Amar V. Nasrulloh Arfan E. Fahrudi