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Nonlinear Vectorial Prediction With Neural Nets

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Bio-Inspired Applications of Connectionism (IWANN 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2085))

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Abstract

In this paper we propose a nonlinear vectorial prediction scheme based on a Multi Layer Perceptron. This system is applied to speech coding in an ADPCM backward scheme. In addition a procedure to obtain a vectorial quantizer is given, in order to achieve a fully vectorial speech encoder. We also present several results with the proposed system

This work has been supported by the CICYT TIC2000-1669-C04-02

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References

  1. A. Gersho & R.M. Gray “Vector Quantization and signal compression”. Ed. Kluwer 1992.

    Google Scholar 

  2. M. Faúndez, F. Vallverdu & E. Monte, “Nonlinear prediction with neural nets in ADPCM” International Conference on Acoustic, Speech & Signal Processing, ICASSP-98.SP11.3.Seattle, USA, May

    Google Scholar 

  3. O. Oliva, M. Faúndez “A comparative study of several ADPCM schemes with linear and nonlinear prediction” EUROSPEECH’99, Budapest, Vol. 3, pp.1467–1470.

    Google Scholar 

  4. M. Faúndez-Zanuy, “Nonlinear predictive models computation in ADPCM schemes”. Vol. II, pp 813–816. EUSIPCO 2000, Tampere.

    Google Scholar 

  5. C. Montacié & J.L. Le Floch, “Discriminant AR-Vector models for free-text speaker verification”, pp.161–164, Eurospeech 1993.

    Google Scholar 

  6. S. Haykin, “neural nets. A comprehensive foundation”, 2on edition. Ed. Prentice Hall 1999.

    Google Scholar 

  7. N.S. Jayant and P. Noll “Digital Coding of Waveforms”. Ed. Prentice Hall 1984.

    Google Scholar 

  8. D.J.C. Mackay “Bayesian interpolation”, Neural computation, Vol.4, No3, pp.415–447, 1992.

    Article  Google Scholar 

  9. F.D. Foresee and M.T. Hagan, “Gauss-Newton approximation to Bayesian regularization”, proceedings of the 1997 International Joint Conference on Neural Networks, pp.1930–1935, 1997.

    Google Scholar 

  10. V. Cuperman, A. Gersho “Vector predictive coding of speech at 16 kbits/s”. IEEE trans. on Commun. vol. COM-33, pp.685–696, July 1985.

    Article  Google Scholar 

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Faúndez-Zanuy, M. (2001). Nonlinear Vectorial Prediction With Neural Nets. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_91

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  • DOI: https://doi.org/10.1007/3-540-45723-2_91

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42237-2

  • Online ISBN: 978-3-540-45723-7

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