An automated glottal waveform estimation algorithm is presented that improves on a previous manual glottal extraction technique which produced excellent glottal waveform estimates. The algorithm uses only basic approximations of glottal closure regions and successive iterations to find the best candidate for a glottal waveform estimate within a speech frame. Visual comparisons of the glottal waveform estimates created by the algorithm and those generated from the use of glottal closure information provided by an electroglottograph (EGG) reveal that the algorithm produced virtually identical estimates.