Quasi closed phase analysis for glottal inverse filtering

Manu Airaksinen, Brad Story, Paavo Alku

Research output: Contribution to journalConference article

4 Scopus citations

Abstract

This study presents a new glottal inverse filtering (GIF) technique based on the closed phase analysis over multiple fundamental periods. The proposed Quasi Closed Phase Analysis (QCP) method utilizes Weighted Linear Prediction (WLP) with a specific Attenuated Main Excitation (AME) weighting function that attenuates the contribution of the glottal source in the linear prediction model optimization. This enables the use of the autocorrelation criterion in linear prediction in comparison to the conventional covariance criterion used in the closed phase analysis. The proposed method was compared to previously developed methods by using a synthetic vowel database created with a physical modeling approach. The obtained objective measures show that the proposed method improves the GIF performance for both low- And high-pitched vowels.

Original languageEnglish (US)
Pages (from-to)143-147
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
StatePublished - Jan 1 2013
Event14th Annual Conference of the International Speech Communication Association, INTERSPEECH 2013 - Lyon, France
Duration: Aug 25 2013Aug 29 2013

Keywords

  • Glottal inverse filtering
  • Glottal source estimation
  • Linear prediction
  • Speech analysis

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modeling and Simulation

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