dolpc: (Perceptive) Linear Prediction
In tuneR: Analysis of Music and Speech

dolpc

R Documentation

(Perceptive) Linear Prediction

Description

Compute autoregressive model from spectral magnitude samples via Levinson-Durbin recursion.

Usage

dolpc(x, modelorder = 8)

Arguments

`x`	Matrix of spectral magnitude samples (each sample/time frame in one column).
`modelorder`	Lag of the AR model.

Value

Returns a matrix of the normalized AR coefficients (depending on the input spectrum: LPC or PLP coefficients). Every column represents one time frame.

Author(s)

Sebastian Krey krey@statistik.tu-dortmund.de

References

Daniel P. W. Ellis: https://www.ee.columbia.edu/~dpwe/resources/matlab/rastamat/

Examples

  testsound <- normalize(sine(400) + sine(1000) + square(250), "16")
  pspectrum <- powspec(testsound@left, testsound@samp.rate)
  aspectrum <- audspec(pspectrum, testsound@samp.rate)$aspectrum
  lpcas <- dolpc(aspectrum, 10)

tuneR documentation built on Nov. 27, 2023, 5:11 p.m.