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

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


Research units


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.


Original languageEnglish
Title of host publicationICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publication statusPublished - 1 May 2019
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech, and Signal Processing - Brighton, United Kingdom
Duration: 12 May 201917 May 2019
Conference number: 44

Publication series

NameProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X


ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing
Abbreviated titleICASSP
CountryUnited Kingdom

    Research areas

  • time-frequency processing, windowing, discrete prolate spherical sequences

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