  Conventional Frequency Domain Linear Prediction (FDLP) technique models the
squared Hilbert envelope of speech with varied degrees of approximation which
can be sampled at the required frame rate and used as features for Automatic
Speech Recognition (ASR). Although previously the complex cepstrum of the
conventional FDLP model has been used as compact frame-wise speech features, it
has lacked interpretability in the context of the Hilbert envelope. In this
paper, we propose a modification of the conventional FDLP model that allows
easy interpretability of the complex cepstrum as temporal modulations in an
all-pole model approximation of the power of the speech signal. Additionally,
our "complex" FDLP yields significant speed-ups in comparison to conventional
FDLP for the same degree of approximation.
