Design of nonlinear predictors for adaptive predictive coding of speech signals

Vladimir Despotovic, Zoran Peric

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2013 21st Telecommunications Forum Telfor, TELFOR 2013 - Proceedings of Papers
Pages490-497
Number of pages8
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 21st Telecommunications Forum Telfor, TELFOR 2013 - Belgrade, Serbia
Duration: 26 Nov 201328 Nov 2013

Publication series

Name2013 21st Telecommunications Forum Telfor, TELFOR 2013 - Proceedings of Papers

Conference

Conference2013 21st Telecommunications Forum Telfor, TELFOR 2013
Country/TerritorySerbia
CityBelgrade
Period26/11/1328/11/13

Keywords

  • Nonlinear speech processing
  • Pitch period
  • Prediction
  • Volterra series

Fingerprint

Dive into the research topics of 'Design of nonlinear predictors for adaptive predictive coding of speech signals'. Together they form a unique fingerprint.

Cite this