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Optimal cepstrum estimation using multiple windows

Sandsten, Maria LU and Sandberg, Johan LU (2009) ICASSP: International Conference on Acoustics, Speech and Signal Processing In International Conference on Acoustics Speech and Signal Processing ICASSP p.3077-3080
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.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
speech analysis, multitaper, multiple windows, cepstrum analysis
in
International Conference on Acoustics Speech and Signal Processing ICASSP
pages
4 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
ICASSP: International Conference on Acoustics, Speech and Signal Processing
external identifiers
  • wos:000268919201309
  • scopus:70349223791
ISSN
1520-6149
ISBN
978-1-4244-2353-8
DOI
10.1109/ICASSP.2009.4960274
language
English
LU publication?
yes
id
b0bd076b-7263-4ef8-8725-d0e23c437b5a (old id 1304171)
alternative location
http://ltswww.epfl.ch/ltsftp/ICASSP2009/pdfs/0003077.pdf
date added to LUP
2009-05-11 14:00:07
date last changed
2017-03-13 13:12:15
@inproceedings{b0bd076b-7263-4ef8-8725-d0e23c437b5a,
  abstract     = {The aim of this paper is to find a multiple window estimator<br/><br>
that is mean square error optimal for cepstrum estimation.<br/><br>
The estimator is compared with some known multiple window<br/><br>
methods as well as with the parametric AR-estimator.<br/><br>
The results show that the new estimator has high performance,<br/><br>
especially for data with large spectral dynamics, and that it is<br/><br>
also robust against parameter choices. Simulated speech data<br/><br>
is used for the evaluation. It is also shown that the windows<br/><br>
of the estimator can be approximated with the sinusoidal multiple<br/><br>
windows and that the weighting factors of the different<br/><br>
periodograms can be analytically computed.},
  author       = {Sandsten, Maria and Sandberg, Johan},
  booktitle    = {International Conference on Acoustics Speech and Signal Processing ICASSP},
  isbn         = {978-1-4244-2353-8},
  issn         = {1520-6149},
  keyword      = {speech analysis,multitaper,multiple windows,cepstrum analysis},
  language     = {eng},
  pages        = {3077--3080},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Optimal cepstrum estimation using multiple windows},
  url          = {http://dx.doi.org/10.1109/ICASSP.2009.4960274},
  year         = {2009},
}