Optimal cepstrum estimation using multiple windows
(2009) ICASSP: International Conference on Acoustics, Speech and Signal Processing 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:
https://lup.lub.lu.se/record/1304171
- author
- Sandsten, Maria LU and Sandberg, Johan LU
- organization
- publishing date
- 2009
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- speech analysis, multitaper, multiple windows, cepstrum analysis
- host publication
- 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
- conference location
- Taipei, Taiwan
- conference dates
- 2009-04-19 - 2009-04-24
- 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
- 2016-04-01 14:57:28
- date last changed
- 2022-04-22 06:03:47
@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}}, keywords = {{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}}, doi = {{10.1109/ICASSP.2009.4960274}}, year = {{2009}}, }