Over-smoothing is one of the major sources of quality degradation in statistical
parametric speech synthesis. Many methods have been proposed to compensate
over-smoothing with the speech parameter generation algorithm considering Global
Variance (GV) being one of the most successfull. This paper models over-smoothing
as a radial relocation of poles and zeros of the spectral envelope towards the
origin of the z-plane and uses radial scaling to enhance spectral peaks and to
deepen spectral valeys. The radial scaling technique is improved by introducing
over-emphasis, spectral-tilt compensation and frequency weighting. Listening test
results indicate that the proposed method is 11%-13% more preferable than GV while
it has less algorithmic delay (only 5 ms) and computational complexity.