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Complex cepstrum is known in the literature for linearly separating causaland anticausal components. Relying on advances achieved by the Zeros of theZ-Transform (ZZT) technique, we here investigate the possibility of usingcomplex cepstrum for glottal flow estimation on a large-scale database. Via asystematic study of the windowing effects on the deconvolution quality, we showthat the complex cepstrum causal-anticausal decomposition can be effectivelyused for glottal flow estimation when specific windowing criteria are met. Itis also shown that this complex cepstral decomposition gives similar glottalestimates as obtained with the ZZT method. However, as complex cepstrum usesFFT operations instead of requiring the factoring of high-degree polynomials,the method benefits from a much higher speed. Finally in our tests on a largecorpus of real expressive speech, we show that the proposed method has thepotential to be used for voice quality analysis.

Causal-Anticausal Decomposition of Speech using Complex Cepstrum for Glottal Source Estimation