Reference : Design of nonlinear predictors for adaptive predictive coding of speech signals

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/40894

Title :	Design of nonlinear predictors for adaptive predictive coding of speech signals
Language :	English
Author, co-author :	Despotovic, Vladimir [University of Belgrade > Technical Faculty in Bor]
	Peric, Zoran [University of Nis > Faculty of Electronic Engineering]
Publication date :	Nov-2013
Main document title :	Proceedings of the 21st Telecommunications Forum Telfor (TELFOR)
Publisher :	IEEE
Pages :	490-497
Peer reviewed :	Yes
On invitation :	Yes
Audience :	International
ISBN :	978-1-4799-1420-3
Event name :	21st Telecommunications Forum Telfor (TELFOR)
Event date :	from 26-11-2013 to 28-11-2013
Event place (city) :	Belgrade
Event country :	Serbia
Keywords :	[en] 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.
Permalink :	http://hdl.handle.net/10993/40894
DOI :	10.1109/TELFOR.2013.6716274
Other URL :	https://ieeexplore.ieee.org/document/6716274?tp=&arnumber=6716274&url=http:%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6716274

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	Fulltext file(s): File Commentary Version Size Access Limited access TELFOR 2013.pdf Publisher postprint 1.5 MB Request a copy

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