Regularized linear prediction of speech

L. Anders Ekman, W. Bastiaan Kleijn, Manohar N. Murthi

Research output: Contribution to journalArticle

31 Scopus citations

Abstract

All-pole spectral envelope estimates based on linear prediction (LP) for speech signals often exhibit unnaturally sharp peaks, especially for high-pitch speakers. In this paper, regularization is used to penalize rapid changes in the spectral envelope, which improves the spectral envelope estimate. Based on extensive experimental evidence, we conclude that regularized linear prediction outperforms bandwidth-expanded linear prediction. The regularization approach gives lower spectral distortion on average, and fewer outliers, while maintaining a very low computational complexity.

Original languageEnglish (US)
Article number4378273
Pages (from-to)65-73
Number of pages9
JournalIEEE Transactions on Audio, Speech and Language Processing
Volume16
Issue number1
DOIs
StatePublished - Jan 1 2008

Keywords

  • Bandwidth expansion
  • Envelope estimation
  • Linear prediction (LP)
  • Regularization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Acoustics and Ultrasonics

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