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

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 KaiserBessel 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 lowoverlap windows. Our experiments demonstrate that the proposed windows provide notable improvements in terms of reduction in side-lobe magnitude.