Majority of speech processing algorithms that employ the short-time Fourier transform process the short-time magnitude spectrum, while either discarding the short-time phase spectrum or leaving it unchanged. This is in-part due to a long-standing belief among speech researchers that the short-time phase spectrum, computed over small analysis window durations of 20–40 ms, contains little useful information and is thus (mostly) unimportant for speech processing (though it is accepted that the phase spectrum does contribute to some extent to naturalness and quality aspects of speech). The above belief has been supported by numerous studies presented in the literature. Results of recent speech perception experiments suggest, however, that the phase spectrum (at small analysis window durations of 20–40 ms) does contain significant amount of useful information, provided that the analysis window function is carefully selected. It was reported that the use of non-tapered analysis windows functions (such as the rectangular window) significantly improves intelligibility of the phase spectrum. This improvement was attributed to the spectral characteristics of the non-tapered analysis windows and—in particular—to their low spectral dynamic range. The main aim of the research presented in this dissertation is to further examine the importance of the short-time phase spectrum for human speech perception. It is hoped that results of such an examination can provide an incentive for further research in this direction. Three studies that investigate the usefulness of the phase spectrum for human speech perception are presented in this thesis. These studies employ human listening tests to explore the importance of the phase spectrum for speech intelligibility, speaker dependent speech information and speech quality. In each of these studies the effect of the spectral dynamic range of an analysis window function is systematically examined.