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Wavelet-scalogram based study of non-periodicity in speech signals as a complementary measure of chaotic content

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Abstract

In recent studies, the chaotic behavior of a signal is confirmed using scalogram analysis of continuous-wavelet transform. Chaotic component of a speech signal can be verified through scalogram analysis, since, it investigates the periodicity content of a signal. The periodicity analysis helps in proving that a signal is not periodic, which is an essential condition on chaotic activity. In this work, a scale-index based on scalogram-analysis is calculated for a set of recordings of Arabic vowels. Also, Largest-Lyapunov Exponents (LLE) are computed for these recordings. The obtained measures are, then, compared. The comparison proves the efficacy of scale index for confirming chaotic behavior even for highly-periodic waveforms which is the case in speech vowels. Additionally, it is noted that both LLE and scale-index exhibit classification ability for Arabic vowels.

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Authors and Affiliations

  1. Eng. Math & Physics Dept., Faculty of Engineering, Cairo University, Giza, 12613, Egypt

    M. Hesham

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  1. M. Hesham
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Hesham, M. Wavelet-scalogram based study of non-periodicity in speech signals as a complementary measure of chaotic content. Int J Speech Technol 16, 353–361 (2013). https://doi.org/10.1007/s10772-013-9187-3

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  • DOI: https://doi.org/10.1007/s10772-013-9187-3

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