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

Volume

13

Issue

4

fYear

2006

fDate

4/1/2006 12:00:00 AM

Firstpage

244

Lastpage

247

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);

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2005.863652

Filename

1605249