Title :
Split-order linear prediction for segmentation and harmonic spectral modeling
Author :
Ramírez, Miguel Arjona ; Minami, Mário
Author_Institution :
Electron. Syst. Eng. Dept., Univ. of Sao Paulo, Brazil
fDate :
4/1/2006 12:00:00 AM
Abstract :
Linear prediction (LP) analysis, split in two stages, is proposed for a combined time-frequency analysis. The first-stage LP is used to obtain the residual signal and extract each one of its cycles, whose harmonic spectrum is then modeled by the second-stage estimate from discrete all-pole algorithms. Thus, harmonic cycle spectra are modeled with less than 1 dB in log spectral distortion (SD). Further, a method is proposed to approximate the log SD target. A linear approximation to the log power spectral ratio in the log SD gradient is shown to provide better model fit to harmonic cycle spectra.
Keywords :
approximation theory; prediction theory; speech processing; time-frequency analysis; discrete all-pole algorithm; harmonic spectrum; linear approximation; linear prediction analysis; second-stage estimation; spectral distortion; time-frequency analysis; Distortion measurement; Harmonic analysis; Harmonic distortion; Linear approximation; Power harmonic filters; Predictive models; Signal analysis; Signal processing algorithms; Signal synthesis; Speech analysis; AR models; discrete all-pole (DAP); linear prediction (LP) analysis; spectral modeling; speech analysis; split-order linear prediction (SOLP);
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2005.863652