Reference : Low-Order Volterra Long-Term Predictors
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Low-Order Volterra Long-Term Predictors
Despotovic, Vladimir mailto [University of Belgrade > Technical Faculty in Bor]
Goertz, Norbert [Technische Universit├Ąt Wien = Vienna University of Technology - TU Vienna > Institute of Telecommunications]
Peric, Zoran [University of Nis > Faculty of Electronic Engineering]
Proceedings of the 10. ITG Symposium on Speech Communication
VDE Verlag
10. ITG Symposium on Speech Communication
from 26-09-2012 to 28-09-2012
[en] Models based on linear prediction have been used for several decades in different areas of speech signal processing. While the linear approach has led to great advances in the last 40 years, it neglects nonlinearities present in the speech production mechanism. This paper compares the results of long-term nonlinear prediction based on second-order and third-order Volterra filters. Additional improvement can be obtained using fractionaldelay long-term prediction. Experimental results reveal that the proposed method outperforms linear long-term prediction techniques in terms of prediction gain.

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