Determining polarity of speech signals based on gradient of spurious glottal waveforms

Speech polarity is crucial in many speech processing fields. We present a novel method to determine the polarity of speech signals from the gradient of spurious glottal waveforms. We use the iterative adaptive LPC inverse filtering to cancel the effect of vocal tract transfer function while maintaining most of the properties of source excitation. Then we take the first-derivative (gradient component) of spurious glottal waveforms to capture the sharp gradient near the glottal closure instant. By using the gradient components of the spurious glottal waveforms, we detect speech polarity, i.e., the polarity of glottal waveforms, by finding whether the glottal closure instants are located above or below the zero-line. Furthermore, a frame-based decision technique is applied to get robust results. Experimental results with a wide variety of speech utterances reveal a high performance and the computation complexity is much less than a previously proposed method