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Application of k-Nearest-Neighbor Decision Rule in Vowel Recognition
February 1983 (vol. 5 no. 2)
pp. 229-231
K. K. Paliwal, Speech and Digital Systems Group, Tata Institute of Fundamental Research, Bombay 400005, India.
P. V. S. Rao, Speech and Digital Systems Group, Tata Institute of Fundamental Research, Bombay 400005, India.
The k-nearest-neighbor decision rule is known to provide a useful nonparametric procedure for pattern classification. This rule is applied here to a vowel recognition problem and the effect of the number (k) of nearest neighbors, the size of the trained set and the type of the distance measure on vowel recognition performance is studied. It is shown that the vowel recognition performance remains approximately constant for all the values of k. The recognition performance initially improves with the size of the training set and then converges to an asymptotic value. Selection of a better distance measure leads to a significant improvement in vowel recognition performance.
Citation:
K. K. Paliwal, P. V. S. Rao, "Application of k-Nearest-Neighbor Decision Rule in Vowel Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 5, no. 2, pp. 229-231, Feb. 1983, doi:10.1109/TPAMI.1983.4767378
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