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DOI: 10.14569/SpecialIssue.2011.010302
PDF

Speaker Identification using Row Mean of Haar and Kekre’s Transform on Spectrograms of Different Frame Sizes

Author 1: H B Kekre
Author 2: Vaishali Kulkarni

International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Artificial Intelligence, 2011.

  • Abstract and Keywords
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Abstract: In this paper, we propose Speaker Identification using two transforms, namely Haar Transform and Kekre’s Transform. The speech signal spoken by a particular speaker is converted into a spectrogram by using 25% and 50% overlap between consecutive sample vectors. The two transforms are applied on the spectrogram. The row mean of the transformed matrix forms the feature vector, which is used in the training as well as matching phases. The results of both the transform techniques have been compared. Haar transform gives fairly good results with a maximum accuracy of 69% for both 25% as well as 50% overlap. Kekre’s Transform shows much better performance, with a maximum accuracy of 85.7% for 25% overlap and 88.5% accuracy for 50% overlap.

Keywords: Speaker Identification; Spectrogram; Haar Transform; Kekre’s Transform; Row Mean; Euclidean distance

H B Kekre and Vaishali Kulkarni, “Speaker Identification using Row Mean of Haar and Kekre’s Transform on Spectrograms of Different Frame Sizes” International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Artificial Intelligence, 2011. http://dx.doi.org/10.14569/SpecialIssue.2011.010302

@article{Kekre2011,
title = {Speaker Identification using Row Mean of Haar and Kekre’s Transform on Spectrograms of Different Frame Sizes},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Artificial Intelligence}
doi = {10.14569/SpecialIssue.2011.010302},
url = {http://dx.doi.org/10.14569/SpecialIssue.2011.010302},
year = {2011},
publisher = {The Science and Information Organization},
volume = {1},
number = {3},
author = {H B Kekre and Vaishali Kulkarni},
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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