  The objective of the present work is to propose a method to automatically
detect polarity of the speech signals by estimating instants of significant
excitation of the vocaltract and the cosine phase of the analytic signal
representation. The phase changes in the analytic signal around the Hilbert
envelope (HE) peaks are found to vary according to the polarity of the given
speech signal. The relevant HE peaks for the Hilbert phase analysis are
selected by estimating the instants of significant excitation in speech. The
speech polarity identification rate obtained for the proposed method is almost
equal to the state of the art residual skewness method for speech polarity
detection. The proposed method also provides the same results for the polarity
detection in electro-glottogram signals. Finally, the robustness of the
proposed method is confirmed from the reduced detection error rates obtained in
noisy environments with various signal to noise ratios (SNRs). The MATLAB codes
used for implementing the proposed method are available for download from the
following link: http://nlp.amrita.edu:8080/TTS/polarityprograms.zip
