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Optimal cepstrum estimation using multiple windows

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Author

Summary, in English

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.

Department/s

Publishing year

2009

Language

English

Pages

3077-3080

Publication/Series

International Conference on Acoustics Speech and Signal Processing ICASSP

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Probability Theory and Statistics

Keywords

  • speech analysis
  • multitaper
  • multiple windows
  • cepstrum analysis

Conference name

ICASSP: International Conference on Acoustics, Speech and Signal Processing

Conference date

2009-04-19 - 2009-04-24

Conference place

Taipei, Taiwan

Status

Published

Research group

  • Statistical Signal Processing Group

ISBN/ISSN/Other

  • ISSN: 1520-6149
  • ISBN: 978-1-4244-2353-8