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In most current approaches of speech processing, information is extractedfrom the magnitude spectrum. However recent perceptual studies have underlinedthe importance of the phase component. The goal of this paper is to investigatethe potential of using phase-based features for automatically detecting voicedisorders. It is shown that group delay functions are appropriate forcharacterizing irregularities in the phonation. Besides the respect of themixed-phase model of speech is discussed. The proposed phase-based features areevaluated and compared to other parameters derived from the magnitude spectrum.Both streams are shown to be interestingly complementary. Furthermorephase-based features turn out to convey a great amount of relevant information,leading to high discrimination performance.

Phase-based Information for Voice Pathology Detection