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Performance Evaluation of Speaker Identification for Partial Coefficients of Transformed Full, Block and Row Mean of Speech Spectrogram using DCT, WALSH and HAAR

Author(s): H. B. Kekre | Tanuja K. Sarode | Shachi J. Natu | Prachi J. Natu

Journal: International Journal of Computer Science and Information Security
ISSN 1947-5500

Volume: 8;
Issue: 6;
Start page: 186;
Date: 2010;
Original page

Keywords: Speaker Identification | DCT | WALSH | HAAR | Image blocks | Row Mean | Partial feature vector

In this paper an attempt has been made to provide simple techniques for speaker identification using transforms such as DCT, WALSH and HAAR along with the use of spectrograms instead of raw speech waves. Spectrograms form a image database here. This image database is then subjected to different transformation techniques applied in different ways such as on full image, on image blocks and on Row Mean of an image and image blocks. In each method, results have been observed for partial feature vectors of image. From the results it has been observed that, transform on image block is better than transform on full image in terms of identification rate and computational complexity. Further, increase in identification rate and decrease in computations has been observed when transforms are applied on Row Mean of an image and image blocks. Use of partial feature vector further reduces the number of comparisons needed for finding the most appropriate match.
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