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Comparative Analysis of Speaker Identification using row mean of DFT, DCT, DST and Walsh Transforms

Author(s): H B Kekre, | Vaishali Kulkarni

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

Volume: 9;
Issue: 1;
Start page: 102;
Date: 2011;
Original page

Keywords: Euclidean distance | Row mean | Speaker Identification | Speaker Recognition

In this paper we propose Speaker Identification using four different Transform Techniques. The feature vectors are the row mean of the transforms for different groupings. Experiments were performed on Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Sine Transform (DST) and Walsh Transform (WHT). All the Transform give an accuracy of more than 80% for the different groupings considered. Accuracy increases as the number of samples grouped is increased from 64 onwards. But for groupings more than 1024 the accuracy again starts decreasing. The results show that DST performs best. The maximum accuracy obtained for DST is 96% for a grouping of 1024 samples while taking the transform.
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