Abstract
In this study, a computationally efficient speaker independent isolated word recognition system for Turkish language is designed and implemented. The approach used is a combination of whole-word matching techniques with segmentation into phonetic units before classification. Linear Predictive Coding (LPC) coefficients for an eight-pole model of the short-time signal are used as feature vectors. Computational costs are reduced by a two-step classification strategy where unlikely words are eliminated in the first step by comparing only the first syllable. The Dynamic Time Warping (DTW) method is used in comparisons at both levels.
CPU time spent for word comparisons is reduced by about 40% compared to the time that has to be spent for a one-step whole-word classification without degrading the system performance.
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© 1985 Springer-Verlag Berlin Heidelberg
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Yalabik, N., Ünal, F. (1985). An Efficient Algorithm for Recognizing Isolated Turkish Words. In: De Mori, R., Suen, C.Y. (eds) New Systems and Architectures for Automatic Speech Recognition and Synthesis. NATO ASI Series, vol 16. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-82447-0_16
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DOI: https://doi.org/10.1007/978-3-642-82447-0_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-82449-4
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