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dolpc

(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)

References

See Also

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

Analysis of Music and Speech

v1.3.3
GPL-2 | GPL-3
Authors
Uwe Ligges <ligges@statistik.tu-dortmund.de> with contributions from Sebastian Krey, Olaf Mersmann, Sarah Schnackenberg, Guillaume Guenard, Andrea Preusser, Anita Thieler, Johanna Mielke and Claus Weihs, as well as code fragments and ideas from the former package 'sound' by Matthias Heymann and functions from 'rastamat' by Daniel P. W. Ellis. The included parts of the libmad MPEG audio decoder library are authored by Underbit Technologies.
Initial release
2018-07-03

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