  Some glottal analysis approaches based upon linear prediction or complex
cepstrum approaches have been proved to be effective to estimate glottal source
from real speech utterances. We propose a new approach employing both an
all-pole odd-order linear prediction to provide a coarse estimation and phase
decomposition based causality/anti-causality separation to generate further
refinements. The obtained measures show that this method improved performance
in terms of reducing source-filter separation in estimation of glottal flow
pulses (GFP). No glottal model fitting is required by this method, thus it has
wide and flexible adaptation to retain fidelity of speakers's vocal features
with computationally affordable resource. The method is evaluated on real
speech utterances to validate it.
