lpc: Linear Predictive Coding
In phonTools: Tools for Phonetic and Acoustic Analyses

lpc	R Documentation

Linear Predictive Coding

Description

Predict autoregressive filter coefficients.

Usage

lpc (sound, order = round(fs/1000)+3, fs = 10000, show = FALSE, 
add = FALSE, preemph = TRUE)

Arguments

`sound`	Either a numeric vector representing a sequence of samples taken from a sound wave or a sound object created with the loadsound() or makesound() functions.
`order`	The number of LPC coefficients to be estimated. By default there is 2 per kHz below the Nyquist frequency plus 3 extra coefficients.
`fs`	The sampling frequency in Hz. If a sound object is passed this does not need to be specificed.
`show`	If TRUE, the frequency response of the estimated filter is plotted.
`add`	If TRUE, the frequency response plot is added to an existing plot.
`preemph`	If TRUE, preemphasis of 3 dB per octave is applied to the sound before analysis.

Details

LPC coefficients are estimated using the autocorrelation method. The signal is windowed with a Hanning window prior to analysis.

Value

A vector containing the LPC coefficients is returned.

Author(s)

Santiago Barreda <sbarreda@ucdavis.edu>

Examples

## make a synthetic vowel with a known set of formant frequencies
#sound = vowelsynth (ffs = c(500,1500,2500,3500,4500), 
#fbw = c(30, 80, 150, 200, 220),f0 = 100, dur = 250)

## let the LPC function estimate the filter used to generate the vowel
#coeffs = lpc (sound, show = TRUE)

phonTools documentation built on Nov. 21, 2023, 1:07 a.m.