Paper ID: 2203.16962

A comparative study between linear and nonlinear speech prediction

Marcos Faundez-Zanuy, Enric Monte, Francesc Vallverdú

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.

Submitted: Mar 31, 2022