Abstract
This paper investigates on the use of Wavelet Transform (WT) to model and recognize the utterances of Consonant – Vowel (CV) speech units in noisy environments. The peculiarity of the proposed method lies in the fact that using WT, non stationary nature of the speech signal can be accurately considered. A hybrid feature extraction namely Normalized Wavelet Hybrid Feature (NWHF) using the combination of Classical Wavelet Decomposition (CWD) and Wavelet Packet Decomposition (WPD) along with z-score normalization technique are studied here. CV speech unit recognition tasks performed for noisy speech units using Artificial Neural Network (ANN) and k – Nearest Neighborhood (k – NN) are also presented. The result indicates the robustness of the proposed technique based on WT in additive noisy condition.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gold, B., Morgan, N.: Speech and Audio Signal Processing. John Wiley & Sons Inc., New York (2000)
Ramachandran, H.P.: Encyclopedia of Language and Linguistics. Pergamon Press, Oxford
Bourlard, H., Dupont, S.: Subband-based speech recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP Signal Processing (ICASSP 1997), Munich, Germany, vol. 2, pp. 1251–1254 (April 1997)
Gupta, M., Gilbert, A.: Robust speech recognition using wavelet coefficient features. In: IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU 2001), Madonna di Campiglio, Trento, Italy, pp. 445–448 (December 2001)
Sarikaya, R., Pellom, B.L., Hansen, J.H.L.: Wavelet packet transform features with application to speaker Identification. In: 3rd IEEE Nordic Signal Processing Symposium (NORSIG 1998), Vigsø, Denmark, pp. 81–84 (June 1998)
Grossman, A., Morlet, J., Gaoupillaud, P.: Cycle octave and related transforms in seismic signal Analysis. Geoexploration 23, 85–102 (1984)
Mallat, S.: A wavelet Tour of Signal Processing, The Sparse Way. Academic, New York (2009)
Soman, K.P., Ramachandran, K.I.: Insight into Wavelets, from Theory to Practice. Prentice Hall of India (2005)
Vetterly, M., Herley, C.: Wavelets and Filter banks: Theory and Design. IEEE Trans. on Signal Processing 40(9), 2207–2232 (1992)
Shensa, M.J.: Affine Wavelets: Wedding the Atrous and mallat Algorithms. IEEE Trans. on Signal Processing 40, 2464–2482 (1992)
Mallat, S.: Multi frequency Channel Decomposition of Images and Wavelet Models. IEEE. Trans on Acoustics, Speech and Signal Processing 37, 2091–2110 (1989)
Duda, R.O., Hart, P.E.: Pattern Classification and Scene Analysis. Wiley Inter Science, New York (1973)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer India
About this paper
Cite this paper
Thasleema, T.M., Narayanan, N.K. (2013). Normalized Wavelet Hybrid Feature for Consonant Classification in Noisy Environments. In: Kumar M., A., R., S., Kumar, T. (eds) Proceedings of International Conference on Advances in Computing. Advances in Intelligent Systems and Computing, vol 174. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0740-5_34
Download citation
DOI: https://doi.org/10.1007/978-81-322-0740-5_34
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-0739-9
Online ISBN: 978-81-322-0740-5
eBook Packages: EngineeringEngineering (R0)