Programmer Guide/Command Reference/EVAL/lpc: Difference between revisions

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{{DISPLAYTITLE:{{SUBPAGENAME}}}}
{{DISPLAYTITLE:{{SUBPAGENAME}}}}
Compute the linear prediction coefficients using the autocorrelation method ("Linear Prediction of Speech", Markel & Gray).
Compute the linear prediction coefficients using the autocorrelation method. This function implements an all-pole filter approximation of the acoustic tube modell of the vocal tract. The implementation is based on the book "Linear Prediction of Speech" (J.D. Markel & A.H. Gray, Springer 1976).
;Usage:<code>lpc(<var>x</var>, <var>m</var>, <var>p</var> {, <var>type</var> {, <var>lfft</var>}})</code>
;Usage:<code>lpc(<var>x</var>, <var>m</var>, <var>p</var> {, <var>type</var> {, <var>lfft</var>}})</code>
:;<var>x</var>the signal vector; this should be a speech signal without windowing function (because the hamming-window is applied to ''x'' by this the function)
:;<var>x</var>:the signal vector; this should be a speech signal without windowing function (because the hamming-window is applied to ''x'' by this function)
:;<var>m</var>:number of coefficients
:;<var>m</var>:number of coefficients
::rule of thumb: ''m'' ~ samplingrate / 1000 * 1.25
::rule of thumb: ''m'' ~ samplingrate / 1000 * 1.25
:;<var>p</var>differentiation factor; 0 <= ''p'' <= 1 (default=0)
:;<var>p</var>:differentiation factor; 0 &le; ''p'' &le; 1 (default=0)
:;<var>type</var>:output selector; 0 <= ''type'' <= 4 (default=0)
:;<var>type</var>:output selector; 0 &le; ''type'' &le; 4 (default=0)
:;<var>lfft</var>:the length of the fft to be used for the computation of the transfer function (amplitude spectrum) of the inverse filter; ''m+1'' < ''lfft''  
:;<var>lfft</var>:the length of the fft to be used for the computation of the transfer function (amplitude spectrum) of the inverse filter; ''m+1'' < ''lfft''  
::note: if necessary, the value of ''lfft'' is automatically corrected to the next possible value
;Description:
;Description:
:# apply differentiation to signal ''x''
# apply differentiation to signal ''x''
:# apply hamming window to signal ''x''
# apply hamming window to signal ''x''
:# use the autocorelation method to compute the inverse filter coefficients ''ai'', the reflection coefficients ''rc'' and the error (or residual) energy ''alpha''
# use the autocorelation method to compute the inverse filter coefficients ''ai'', the reflection coefficients ''rc'' and the error (or residual) energy ''alpha''
:# convert coefficients to the selected result
# convert coefficients to the selected result
;Result:A vector ''y'' containing the result of the function.  
;Result:A vector ''y'' containing the result of the function.  
:{|class="einrahmen"
:{|class="einrahmen"
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|-
|-
|'''1'''  
|'''1'''  
|<code>''y''[0]=''alpha''</code><BR><code>''y''[1..M+1]=''ai[0..''m'']
|<code>''y''[0]=''alpha''</code><BR><code>''y''[1..M+1]=''ai[0..''m'']</code>
|''m''+2
|''m''+2
|the error energy (''alpha'') and the ''m''+1 inverse filter coefficients ''ai''
|the error energy (''alpha'') and the ''m''+1 inverse filter coefficients ''ai''
|-
|-
|'''2'''  
|'''2'''  
|<code>''y''[0]=''alpha''</code><BR><code>''y''[1..M]=''rc[0..''m''-1]
|<code>''y''[0]=''alpha''</code><BR><code>''y''[1..M]=''rc[0..''m''-1]</code>
|''m''+1
|''m''+1
|the error energy (''alpha'') and the ''m'' reflection coefficients ''rc''
|the error energy (''alpha'') and the ''m'' reflection coefficients ''rc''
|-
|-
|'''3'''  
|'''3'''  
|<code>''y''[0]=''alpha''</code><BR><code>''y''[1..M+1]=''ar[0..''m'']
|<code>''y''[0]=''alpha''</code><BR><code>''y''[1..M+1]=''ar[0..''m'']</code>
|''m''+2
|''m''+2
|the error energy (''alpha'') and the ''m'' area coefficients ''ar''<BR>(''ar''[i] ~ area of section i)
|the error energy (''alpha'') and the ''m'' area coefficients ''ar''<BR>(''ar''[i] ~ area of section i)
|-
|-
|'''4'''  
|'''4'''  
|<code>''y''[0]=''alpha''</code><BR><code>''y''[1..M+1]=''lar[0..''m'']
|<code>''y''[0]=''alpha''</code><BR><code>''y''[1..M+1]=''lar[0..''m'']</code>
|''m''+2
|''m''+2
|the error energy (''alpha'') and the ''m'' log. area coefficients ''lar''<BR>(''lar''[i] ~ diameter of section i)
|the error energy (''alpha'') and the ''m'' log. area coefficients ''lar''<BR>(''lar''[i] ~ diameter of section i)
|}
|}
;See also: [[Programmer_Guide/Command_Reference/EVAL/fft|fft]], [[Programmer_Guide/Command_Reference/EVAL/ifft|ifft]], [[Programmer_Guide/Command_Reference/EVAL/dct|dct]], [[Programmer_Guide/Command_Reference/EVAL/cepstrum|cepstrum]], [[Programmer_Guide/Command_Reference/EVAL/lpc|lpc]], [[Programmer_Guide/Command_Reference/EVAL/complex arithmetic|complex arithmetic]]
;See also: [[../fft|fft]], [[../ifft|ifft]], [[../dft|dft]], [[../dct|dct]], [[../cepstrum|cepstrum]]
 
[[../#Functions|<function list>]]

Latest revision as of 09:11, 2 May 2018

Compute the linear prediction coefficients using the autocorrelation method. This function implements an all-pole filter approximation of the acoustic tube modell of the vocal tract. The implementation is based on the book "Linear Prediction of Speech" (J.D. Markel & A.H. Gray, Springer 1976).

Usage
lpc(x, m, p {, type {, lfft}})
x
the signal vector; this should be a speech signal without windowing function (because the hamming-window is applied to x by this function)
m
number of coefficients
rule of thumb: m ~ samplingrate / 1000 * 1.25
p
differentiation factor; 0 ≤ p ≤ 1 (default=0)
type
output selector; 0 ≤ type ≤ 4 (default=0)
lfft
the length of the fft to be used for the computation of the transfer function (amplitude spectrum) of the inverse filter; m+1 < lfft
note: if necessary, the value of lfft is automatically corrected to the next possible value
Description
  1. apply differentiation to signal x
  2. apply hamming window to signal x
  3. use the autocorelation method to compute the inverse filter coefficients ai, the reflection coefficients rc and the error (or residual) energy alpha
  4. convert coefficients to the selected result
Result
A vector y containing the result of the function.
type y nrow(y) description
0 amplitude spectrum of the inverse filter lfft/2+1 this function can be used in speech analysis to compute the transfer function of the vocal tract (e.g. for formant extraction)
1 y[0]=alpha
y[1..M+1]=ai[0..m]
m+2 the error energy (alpha) and the m+1 inverse filter coefficients ai
2 y[0]=alpha
y[1..M]=rc[0..m-1]
m+1 the error energy (alpha) and the m reflection coefficients rc
3 y[0]=alpha
y[1..M+1]=ar[0..m]
m+2 the error energy (alpha) and the m area coefficients ar
(ar[i] ~ area of section i)
4 y[0]=alpha
y[1..M+1]=lar[0..m]
m+2 the error energy (alpha) and the m log. area coefficients lar
(lar[i] ~ diameter of section i)
See also
fft, ifft, dft, dct, cepstrum

<function list>

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