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Discrete Wavelet Transforms and Artificial Neural Networks for Recognition of Isolated Spoken Words

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 38 - Number 9
Year of Publication: 2012
Sonia Sunny
David Peter S
K Poulose Jacob

Sonia Sunny, David Peter S and Poulose K Jacob. Article: Discrete Wavelet Transforms and Artificial Neural Networks for Recognition of Isolated Spoken Words. International Journal of Computer Applications 38(9):9-13, January 2012. Full text available. BibTeX

	author = {Sonia Sunny and David Peter S and K Poulose Jacob},
	title = {Article: Discrete Wavelet Transforms and Artificial Neural Networks for Recognition of Isolated Spoken Words},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {38},
	number = {9},
	pages = {9-13},
	month = {January},
	note = {Full text available}


Speech recognition is a fascinating application of Digital Signal Processing and has many real-world applications. In this paper, a speech recognition system is developed for isolated spoken words using Discrete Wavelet Transforms (DWT) and Artificial Neural Networks (ANN). Speech signals are one-dimensional and are random in nature. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Daubechies wavelets are employed here. A multi-layer neural network trained with back propagation training algorithm is used for classification purpose. The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results show good recognition accuracy and the efficiency of combining these two techniques.


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