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Circuits, Systems, and Signal Processing

, Volume 32, Issue 6, pp 2915–2938 | Cite as

Analysis of Acoustic Events in Speech Signals Using Bessel Series Expansion

  • Chetana Prakash
  • Dhananjaya N. Gowda
  • Suryakanth V. Gangashetty
Article
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Abstract

In this paper, we propose an approach for the analysis and detection of acoustic events in speech signals using the Bessel series expansion. The acoustic events analyzed are the voice onset time (VOT) and the glottal closure instants (GCIs). The hypothesis is that the Bessel functions with their damped sinusoid-like basis functions are better suited for representing the speech signals than the sinusoidal basis functions used in the conventional Fourier representation. The speech signal is band-pass filtered by choosing the appropriate range of Bessel coefficients to obtain a narrow-band signal, which is decomposed further into amplitude modulated (AM) and frequency modulated (FM) components. The discrete energy separation algorithm (DESA) is used to compute the amplitude envelope (AE) of the narrow-band AM-FM signal. Events such as the consonant and vowel beginnings in an unvoiced stop consonant vowel (SCV) and the GCIs are derived by processing the AE of the signal. The proposed approach for the detection of the VOT using the Bessel expansion is shown to perform better than the conventional Fourier representation. The performance of the proposed GCI detection method using the Bessel series expansion is compared against some of the existing methods for various noise environments and signal-to-noise ratios.

Keywords

Bessel series expansion Voice onset time Glottal closure instant DESA AM-FM 
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Notes

Acknowledgements

The authors would like to thank the Department of Information Technology (DIT), Government of India, and the Defense Research and Development Organization (DRDO), Government of India, for supporting this activity through sponsored research projects. The second author would also like to thank The Academy of Finland (Finnish Centre of Excellence in Computational Inference Research COIN, 251170), and the European community’s seventh framework programme (FP7/2007–2013) under grant agreement no. 287678 (Simple4All) for supporting his stay in Finland as a postdoctoral researcher.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Chetana Prakash
    • 1
  • Dhananjaya N. Gowda
    • 2
  • Suryakanth V. Gangashetty
    • 1
  1. 1.International Institute of Information Technology HyderabadHyderabadIndia
  2. 2.Department of Signal Processing and AcousticsAalto UniversityEspooFinland

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