 MATLAB代做|FPGA代做|python代做-语音信号的LPC算法提取

时间：2019-10-1 19:46:07 点击： 核心提示：function synWave = synlpc2(aCoeff,source,sr,G,fr,fs,preemp)% USAGE: synWave = synlpc(aCoeff,source,s...
function synWave = synlpc2(aCoeff,source,sr,G,fr,fs,preemp)
% USAGE: synWave = synlpc(aCoeff,source,sr,G,fr,fs,preemp);
%
% This function synthesizes a (speech) signal based on a LPC (linear-
% predictive coding) model of the signal. The LPC coefficients are a
% short-time measure of the speech signal which describe the signal as the
% output of an all-pole filter. This all-pole filter provides a good
% description of the speech articulators; thus LPC analysis is often used in
% speech recognition and speech coding systems. The LPC analysis is done
% using the proclpc routine. This routine can be used to verify that the
% LPC analysis produces the correct answer, or as a synthesis stage after
% first modifying the LPC model.
%
% The results of LPC analysis are a new representation of the signal
% s(n) = G e(n) - sum from 1 to L a(i)s(n-i)
% where s(n) is the original data. a(i) and e(n) are the outputs of the LPC
% analysis with a(i) representing the LPC model. The e(n) term represents
% either the speech source's excitation, or the residual: the details of the
% signal that are not captured by the LPC coefficients. The G factor is a
% gain term.
%
% LPC synthesis produces a monaural sound vector (synWave) which is
% sampled at a sampling rate of "sr". The following parameters are mandatory
% aCoeff - The LPC analysis results, a(i). One column of L+1 numbers for each
% frame of data. The number of rows of aCoeff determines L.
% source - The LPC residual, e(n). One column of sr*fs samples representing
% the excitation or residual of the LPC filter.
% G - The LPC gain for each frame.
%
% The following parameters are optional and default to the indicated values.
% fr - Frame time increment, in ms. The LPC analysis is done starting every
% fr ms in time. Defaults to 20ms (50 LPC vectors a second)
% fs - Frame size in ms. The LPC analysis is done by windowing the speech
% data with a rectangular window that is fs ms long. Defaults to 30ms
% preemp - This variable is the epsilon in a digital one-zero filter which
% serves to preemphasize the speech signal and compensate for the 6dB
% per octave rolloff in the radiation function. Defaults to .9378.
%

if (nargin < 5), fr = 20; end;
if (nargin < 6), fs = 30; end;
if (nargin < 7), preemp = .9378; end;

msfs = 180;
msfr = 180;
msoverlap = msfs - msfr;
ramp = [0:1/(msoverlap-1):1]';
[L1 nframe] = size(aCoeff); % L1 = 1+number of LPC coeffs

[row col] = size(source);
if(row==1 | col==1) % continous stream; must be windowed
postFilter = 0; duration = length(source); frameIndex = 1;
for sampleIndex=1:msfr:duration-msfs+1
resid(:,frameIndex) = source(sampleIndex:(sampleIndex+msfs-1))';
frameIndex = frameIndex+1;
end
else
postFilter = 1; resid = source;
end

[row col] = size(resid);
if col<nframe
nframe=col;
end

for frameIndex=1:nframe
A = aCoeff(:,frameIndex);
residFrame = resid(:,frameIndex)*G(frameIndex);
synFrame = filter(1, A', residFrame); % synthesize speech from LPC coeffs

if(frameIndex==1) % add synthesized frames using a trapezoidal window
synWave = synFrame(1:msfr);
else
synWave = [synWave; overlap+synFrame(1:msoverlap).*ramp; ...
synFrame(msoverlap+1:msfr)];
end
if(frameIndex==nframe)
synWave = [synWave; synFrame(msfr+1:msfs)];
else
overlap = synFrame(msfr+1:msfs).*flipud(ramp);
end
end;

if(postFilter)
synWave = filter(1, [1 -preemp], synWave);
end

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