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Design of nonlinear predictors for adaptive predictive coding of speech signals
Despotovic, Vladimir; Peric, Zoran
2013In Proceedings of the 21st Telecommunications Forum Telfor (TELFOR)
Peer reviewed
 

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Keywords :
Nonlinear speech processing; Pitch period; Prediction; Volterra series
Abstract :
[en] 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.
Disciplines :
Computer science
Author, co-author :
Despotovic, Vladimir ;  University of Belgrade > Technical Faculty in Bor
Peric, Zoran;  University of Nis > Faculty of Electronic Engineering
External co-authors :
yes
Language :
English
Title :
Design of nonlinear predictors for adaptive predictive coding of speech signals
Publication date :
November 2013
Event name :
21st Telecommunications Forum Telfor (TELFOR)
Event place :
Belgrade, Serbia
Event date :
from 26-11-2013 to 28-11-2013
By request :
Yes
Audience :
International
Main work title :
Proceedings of the 21st Telecommunications Forum Telfor (TELFOR)
Publisher :
IEEE
ISBN/EAN :
978-1-4799-1420-3
Pages :
490-497
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 07 November 2019

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