Abstract
This paper presents the implementation of a neural network with error back propagation algorithm for the speech recognition application with Phase Space Point Distribution as the input parameter. By utilizing nonlinear or chaotic signal processing techniques to extract time domain based phase space features, a method is suggested for speech recognition. Two sets of experiments are presented in this paper. In the first, exploiting the theoretical results derived in nonlinear dynamics, a processing space called phase space is generated and a recognition parameter called Phase Space Point Distribution (PSPD) is extracted. In the second experiment Phase Space Map at a phase angle p/2 is reconstructed and PSPD is calculated. The output of a neural network with error back propagation algorithm demonstrate that phase space features contain substantial discriminatory power
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Dellar, J.R., Hansen, J.H.L., Proakis, J.G.: Discrete- Time processing of Speech Signals, 908 p. IEEE Press, New York (2000)
Abarbanel, H.D.I.: Analysis of observed chaotic data, 272 p. Springer, New York (1996)
Sauer, T., Yorke, J.A., Casdagli, M.: Embedology. Journal of Statistical Physics 65(3/4), 576–616 (1991)
Narayanan, N.K., Sridhar, C.S.: Parametric Representation of Dynamical Instabilities and Deterministic Chaos in Speech. In: Proceedings Symposium on Signals, Systems and Sonars, NPOL, Cochin, pp. B4.3/1 (1988)
Johnson, M.T., Lindgren, A.C., Povinelli, R.J., Yuan, X.: Performance of nonlinear speech enhancements using Phase Space Reconstruction. Presented at IEEE International conference on Acoustics, Speech and Signal Processing, Hong Kong, China (2003)
Narayanan, N.K.: PhD thesis, CUSAT (1990)
Banbrook, M., McLaughlin, S., Mann, I.: Speech Characterization and Synthesis by Nonlinear Methods. IEEE Transactions on Speech and Audio Processing 7(1) (January 1999)
Takens, F.: Detecting strange attractors in turbulence. Dynamical Systems and Turbulence 898, 366–381 (1980)
Datta, A.K.: A time domain approach to on-line Re-Synthesis of Continuous Speech. JASI XXX, 129–134 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Prajith, P., Sreekanth, N.S., Narayanan, N.K. (2004). Phase Space Parameters for Neural Network Based Vowel Recognition. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_187
Download citation
DOI: https://doi.org/10.1007/978-3-540-30499-9_187
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23931-4
Online ISBN: 978-3-540-30499-9
eBook Packages: Springer Book Archive