Low-Order Volterra Long-Term Predictors

Konferenz: Sprachkommunikation - Beiträge zur 10. ITG-Fachtagung
26.09.2012 - 28.09.2012 in Braunschweig, Deutschland

Tagungsband: Sprachkommunikation

Seiten: 4Sprache: EnglischTyp: PDF

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Despotovic, Vladimir (University of Belgrade, Technical Faculty in Bor, 19210 Bor, Serbia)
Görtz, Norbert (Vienna University of Technology, Institute of Telecommunications, 1040 Vienna, Austria)
Peric, Zoran (University of Nis, Faculty of Electronic Engineering, 18000 Nis, Serbia)

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.