Optimal cepstrum estimation using multiple windows

Maria Sandsten, Johan Sandberg

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

The aim of this paper is to find a multiple window estimator
that is mean square error optimal for cepstrum estimation.
The estimator is compared with some known multiple window
methods as well as with the parametric AR-estimator.
The results show that the new estimator has high performance,
especially for data with large spectral dynamics, and that it is
also robust against parameter choices. Simulated speech data
is used for the evaluation. It is also shown that the windows
of the estimator can be approximated with the sinusoidal multiple
windows and that the weighting factors of the different
periodograms can be analytically computed.
Original languageEnglish
Title of host publicationInternational Conference on Acoustics Speech and Signal Processing ICASSP
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages3077-3080
Number of pages4
ISBN (Print)978-1-4244-2353-8
DOIs
Publication statusPublished - 2009
EventICASSP: International Conference on Acoustics, Speech and Signal Processing - Taipei, Taiwan
Duration: 2009 Apr 192009 Apr 24

Publication series

Name
ISSN (Print)1520-6149

Conference

ConferenceICASSP: International Conference on Acoustics, Speech and Signal Processing
Country/TerritoryTaiwan
CityTaipei
Period2009/04/192009/04/24

Subject classification (UKÄ)

  • Probability Theory and Statistics

Free keywords

  • speech analysis
  • multitaper
  • multiple windows
  • cepstrum analysis

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