  Statistical parametric speech synthesizers have recently shown their ability
to produce natural-sounding and flexible voices. Unfortunately the delivered
quality suffers from a typical buzziness due to the fact that speech is
vocoded. This paper proposes a new excitation model in order to reduce this
undesirable effect. This model is based on the decomposition of
pitch-synchronous residual frames on an orthonormal basis obtained by Principal
Component Analysis. This basis contains a limited number of eigenresiduals and
is computed on a relatively small speech database. A stream of PCA-based
coefficients is added to our HMM-based synthesizer and allows to generate the
voiced excitation during the synthesis. An improvement compared to the
traditional excitation is reported while the synthesis engine footprint remains
under about 1Mb.
