Overlap-add Windows with Maximum Energy Concentration for Speech and Audio Processing

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Overlap-add Windows with Maximum Energy Concentration for Speech and Audio Processing. / Bäckström, T.

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. p. 491-495 8683577 (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Bäckström, T 2019, Overlap-add Windows with Maximum Energy Concentration for Speech and Audio Processing. in ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)., 8683577, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, pp. 491-495, IEEE International Conference on Acoustics, Speech, and Signal Processing, Brighton, United Kingdom, 12/05/2019. https://doi.org/10.1109/ICASSP.2019.8683577

APA

Bäckström, T. (2019). Overlap-add Windows with Maximum Energy Concentration for Speech and Audio Processing. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 491-495). [8683577] (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing). IEEE. https://doi.org/10.1109/ICASSP.2019.8683577

Vancouver

Bäckström T. Overlap-add Windows with Maximum Energy Concentration for Speech and Audio Processing. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. 2019. p. 491-495. 8683577. (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing). https://doi.org/10.1109/ICASSP.2019.8683577

Author

Bäckström, T. / Overlap-add Windows with Maximum Energy Concentration for Speech and Audio Processing. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. pp. 491-495 (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing).

Bibtex - Download

@inproceedings{8307ee9eb2bd4857a9f2ec6595348a7a,
title = "Overlap-add Windows with Maximum Energy Concentration for Speech and Audio Processing",
abstract = "Processing of speech and audio signals with time-frequency representations require windowing methods which allow perfect reconstruction of the original signal and where processing artifacts have a predictable behavior. The most common approach for this purpose is overlap-add windowing, where signal segments are windowed before and after processing. Commonly used windows include the half-sine and a Kaiser-Bessel derived window. The latter is an approximation of the discrete prolate spherical sequence, and thus a maximum energy concentration window, adapted for overlap-add. We demonstrate that performance can be improved by including the overlap-add structure as a constraint in optimization of the maximum energy concentration criteria. The same approach can be used to find further special cases such as optimal low-overlap windows. Our experiments demonstrate that the proposed windows provide notable improvements in terms of reduction in side-lobe magnitude.",
keywords = "time-frequency processing, windowing, discrete prolate spherical sequences",
author = "T. B{\"a}ckstr{\"o}m",
year = "2019",
month = "5",
day = "1",
doi = "10.1109/ICASSP.2019.8683577",
language = "English",
isbn = "978-1-4799-8132-8",
series = "Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing",
publisher = "IEEE",
pages = "491--495",
booktitle = "ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",

}

RIS - Download

TY - GEN

T1 - Overlap-add Windows with Maximum Energy Concentration for Speech and Audio Processing

AU - Bäckström, T.

PY - 2019/5/1

Y1 - 2019/5/1

N2 - Processing of speech and audio signals with time-frequency representations require windowing methods which allow perfect reconstruction of the original signal and where processing artifacts have a predictable behavior. The most common approach for this purpose is overlap-add windowing, where signal segments are windowed before and after processing. Commonly used windows include the half-sine and a Kaiser-Bessel derived window. The latter is an approximation of the discrete prolate spherical sequence, and thus a maximum energy concentration window, adapted for overlap-add. We demonstrate that performance can be improved by including the overlap-add structure as a constraint in optimization of the maximum energy concentration criteria. The same approach can be used to find further special cases such as optimal low-overlap windows. Our experiments demonstrate that the proposed windows provide notable improvements in terms of reduction in side-lobe magnitude.

AB - Processing of speech and audio signals with time-frequency representations require windowing methods which allow perfect reconstruction of the original signal and where processing artifacts have a predictable behavior. The most common approach for this purpose is overlap-add windowing, where signal segments are windowed before and after processing. Commonly used windows include the half-sine and a Kaiser-Bessel derived window. The latter is an approximation of the discrete prolate spherical sequence, and thus a maximum energy concentration window, adapted for overlap-add. We demonstrate that performance can be improved by including the overlap-add structure as a constraint in optimization of the maximum energy concentration criteria. The same approach can be used to find further special cases such as optimal low-overlap windows. Our experiments demonstrate that the proposed windows provide notable improvements in terms of reduction in side-lobe magnitude.

KW - time-frequency processing

KW - windowing

KW - discrete prolate spherical sequences

UR - http://www.scopus.com/inward/record.url?scp=85068967048&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2019.8683577

DO - 10.1109/ICASSP.2019.8683577

M3 - Conference contribution

SN - 978-1-4799-8132-8

T3 - Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing

SP - 491

EP - 495

BT - ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

PB - IEEE

ER -

ID: 33980868