Mercurial > hg > pmhd
view code Kat/hpsmodel.m @ 13:844d341cf643 tip
Back up before ISMIR
author | Yading Song <yading.song@eecs.qmul.ac.uk> |
---|---|
date | Thu, 31 Oct 2013 13:17:06 +0000 |
parents | 881c3acf1164 |
children |
line wrap: on
line source
function [y,yh,ys,fr0] = hpsmodel(x,fs,w,N,t,nH,minf0,maxf0,f0et,maxhd,stocf) %=> analysis/synthesis of a sound using the sinusoidal harmonic model % x: input sound, fs: sampling rate, w: analysis window (odd size), % N: FFT size (minimum 512), t: threshold in negative dB, % nH: maximum number of harmonics, minf0: minimum f0 frequency in Hz, % maxf0: maximim f0 frequency in Hz, % f0et: error threshold in the f0 detection (ex: 5), % maxhd: max. relative deviation in harmonic detection (ex: .2) % stocf: decimation factor of mag spectrum for stochastic analysis % y: output sound, yh: harmonic component, ys: stochastic component M = length(w); % analysis window size Ns = 1024; % FFT size for synthesis H = 256; % hop size for analysis and synthesis N2 = N/2+1; % half-size of spectrum soundlength = length(x); % length of input sound array hNs = Ns/2; % half synthesis window size hM = (M-1)/2; % half analysis window size pin = max(hNs+1,1+hM); % initialize sound pointer to middle of analysis window pend = soundlength-max(hM,hNs); % last sample to start a frame fftbuffer = zeros(N,1); % initialize buffer for FFT yh = zeros(soundlength+Ns/2,1); % output sine component ys = zeros(soundlength+Ns/2,1); % output residual component w = w/sum(w); % normalize analysis window sw = zeros(Ns,1); ow = triang(2*H-1); % overlapping window ovidx = Ns/2+1-H+1:Ns/2+H; % overlap indexes sw(ovidx) = ow(1:2*H-1); bh = blackmanharris(Ns); % synthesis window bh = bh ./ sum(bh); % normalize synthesis window wr = bh; % window for residual sw(ovidx) = sw(ovidx) ./ bh(ovidx); sws = H*hanning(Ns); % synthesis window for stochastic i = 0; while pin<pend i = i+1; %-----analysis-----% xw = x(pin-hM:pin+hM).*w(1:M); % window the input sound fftbuffer(1:(M+1)/2) = xw((M+1)/2:M); % zero-phase window in fftbuffer fftbuffer(N-(M-1)/2+1:N) = xw(1:(M-1)/2); X = fft(fftbuffer); % compute the FFT mX = 20*log10(abs(X(1:N2))); % magnitude spectrum pX = unwrap(angle(X(1:N/2+1))); % unwrapped phase spectrum ploc = 1 + find((mX(2:N2-1)>t) .* (mX(2:N2-1)>mX(3:N2)) ... .* (mX(2:N2-1)>mX(1:N2-2))); % find peaks [ploc,pmag,pphase] = peakinterp(mX,pX,ploc); % refine peak values f0 = f0detection(mX,fs,ploc,pmag,f0et,minf0,maxf0); % find f0 fr0(i)=f0; hloc = zeros(nH,1); % initialize harmonic locations hmag = zeros(nH,1)-100; % initialize harmonic magnitudes hphase = zeros(nH,1); % initialize harmonic phases hf = (f0>0).*(f0.*(1:nH)); % initialize harmonic frequencies hi = 1; % initialize harmonic index npeaks = length(ploc); % number of peaks found while (f0>0 && hi<=nH && hf(hi)<fs/2) % find harmonic peaks [dev,pei] = min(abs((ploc(1:npeaks)-1)/N*fs-hf(hi))); % closest peak if ((hi==1 || ~any(hloc(1:hi-1)==ploc(pei))) && dev<maxhd*hf(hi)) hloc(hi) = ploc(pei); % harmonic locations hmag(hi) = pmag(pei); % harmonic magnitudes hphase(hi) = pphase(pei); % harmonic phases end hi = hi+1; % increase harmonic index end hloc(1:hi-1) = (hloc(1:hi-1)~=0).*((hloc(1:hi-1)-1)*Ns/N+1); % synth. locs ri= pin-hNs; % input sound pointer for residual analysis xr = x(ri:ri+Ns-1).*wr(1:Ns); % window the input sound Xr = fft(fftshift(xr)); % compute FFT for residual analysis Yh = genspecsines(hloc(1:hi-1),hmag,hphase,Ns); % generate sines Yr = Xr-Yh; % get the residual complex spectrum mYr = abs(Yr(1:Ns/2+1)); % magnitude spectrum of residual %mYs = stochenvelope(mYr,stocf); %-----transformations-----% mYsenv = decimate(mYr,stocf,1); % decimate the magnitude spectrum %-----synthesis-----% mYs = interp(mYsenv,stocf,1); % interpolate to original size % n=1:N/2+1; % plot(n/N*Ns,mX); %plotting the original spectrum % hold on; % plot(20*log10(abs(mYs)), 'r'); %plotting the approximation done by the decimate function % % hold on; % plot(hloc, hmag, 'g*'); % hold off; % pause roffset = ceil(stocf/2)-1; % interpolated array offset mYs = [ mYs(1)*ones(roffset,1); mYs(1:Ns/2+1-roffset) ]; pYs = 2*pi*rand(Ns/2+1,1); % generate phase random values mYs1 = [mYs(1:Ns/2+1); mYs(Ns/2:-1:2)]; % create magnitude spectrum pYs1 = [pYs(1:Ns/2+1); -1*pYs(Ns/2:-1:2)]; % create phase spectrum Ys = mYs1.*cos(pYs1)+1i*mYs1.*sin(pYs1); % compute complex spectrum yhw = fftshift(real(ifft(Yh))); % sines in time domain using IFFT ysw = fftshift(real(ifft(Ys))); % stoc. in time domain using IFFT yh(ri:ri+Ns-1) = yh(ri:ri+Ns-1)+yhw(1:Ns).*sw; % overlap-add for sines ys(ri:ri+Ns-1) = ys(ri:ri+Ns-1)+ysw(1:Ns).*sws; % overlap-add for stoch. pin = pin+H; % advance the sound pointer end %ys=tanh(10*ys); y= yh+ys; % sum sines and stochastic