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

Thomas Drugman , Baris Bozkurt (1) , T. Dutoit (2)

1 Department of Electrical & Electronics Engineering
2 TCTS - Circuit Theory and Signal Processing Lab

Complex cepstrum is known in the literature for linearly separating causal and anticausal components. Relying on advances achieved by the Zeros of the Z-Transform (ZZT) technique, we here investigate the possibility of using complex cepstrum for glottal flow estimation on a large-scale database. Via a systematic study of the windowing effects on the deconvolution quality, we show that the complex cepstrum causal-anticausal decomposition can be 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 ZZT method. However, as complex cepstrum uses FFT operations instead of requiring the factoring of high-degree polynomials, the method benefits from a much higher speed. 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.

Mots clés: Complex Cepstrum; Homomorphic Analysis; Glottal Source Estimation; Source-Tract Separation

Domaines: Linguistique

Thomas Drugman, Baris Bozkurt, T. Dutoit. Causal-Anticausal Decomposition of Speech using Complex Cepstrum for Glottal Source Estimation. Speech Communication, 2011, 53 (6), pp.855. ⟨10.1016/j.specom.2011.02.004⟩. ⟨hal-00746109⟩