Title :
Design of nonlinear predictors for adaptive predictive coding of speech signals
Author :
Despotovic, Vladimir ; Peric, Zoran
Author_Institution :
Tech. Fac. in Bor, Univ. of Belgrade, Belgrade, Serbia
Abstract :
Linear predictive coding is probably the most frequently used technique in speech signal processing. Its main advantage comes from the analogy of the simplified vocal tract model with speech production system. However, this neglects nonlinearities in the speech production process. The paper deals with nonlinear prediction of speech based on truncated Volterra series. Long-term one-tap Volterra predictor is designed in order to decrease computational complexity. Further improvements are obtained using frame/subframe structure and fractional delay.
Keywords :
Volterra series; adaptive codes; linear codes; speech coding; adaptive predictive coding; computational complexity; fractional delay; linear predictive coding; nonlinear predictor; nonlinear speech prediction; one tap Volterra predictor; simplified vocal tract model; speech production process; speech signal processing; subframe structure; truncated Volterra series; Adaptation models; Complexity theory; Gain; Predictive models; Speech; Speech coding; Speech processing; Nonlinear speech processing; Pitch period; Prediction; Volterra series;
Conference_Titel :
Telecommunications Forum (TELFOR), 2013 21st
Conference_Location :
Belgrade
Print_ISBN :
978-1-4799-1419-7
DOI :
10.1109/TELFOR.2013.6716274
