A comparative study between linear and nonlinear speech prediction

Abstract

This paper is focused on nonlinear prediction coding, which consists on the prediction of a speech sample based on a nonlinear combination of previous samples. It is known that in the generation of the glottal pulse, the wave equation does not behave linearly [2], [10], and we model these effects by means of a nonlinear prediction of speech based on a parametric neural network model. This work is centred on the neural net weight's quantization and on the compression gain.

11 pages, published in Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg

References in corpus (1)

• A comparative study between linear and nonlinear speech prediction

Cited by in corpus (3)

• Nonlinear prediction with neural nets in ADPCM
• A comparative study between linear and nonlinear speech prediction
• Adaptive hybrid speech coding with a MLP LPC structure