Causal-anticausal decomposition of speech using complex cepstrum for glottal source estimation

This study investigates the possibility of using complex cepstrum for glottal flow estimation. Via a systematic study of the windowing effects on the deconvolution quality, we show that the complex cepstrum causal-anticausal decomposition can be effectively used for glottal flow estimation when specific windowing criteria are met. It is also shown that this complex cepstral decomposition gives similar glottal estimates as obtained with the Zeros of the Z-Transform (ZZT) technique, but uses FFT operations instead of requiring the factoring of high-degree polynomials. The resulting method is consequently much faster for achieving the same decomposition quality. Finally in our tests on a large corpus of real expressive speech, we show that the proposed method has the potential to be used for voice quality analysis.