endfunction
-% Alternative mask function that uses parabolas for fast computetion.
+% Alternative mask function that uses parabolas for fast computation
function maskdB = parabolic_resonator(freq_tone_kHz, mask_sample_freqs_kHz)
% decimate frame rate of mask, use linear interpolation in the log domain
-function maskdB_ = decimate_frame_rate(model, decimate, f, frames, mask_sample_freqs_kHz)
+function maskdB_ = decimate_frame_rate(model, decimate, f, frames)
max_amp = 80;
Wo = model(f,1);
left_fraction = 1 - mod((f-1),decimate)/decimate;
right_fraction = 1 - left_fraction;
- printf("f: %d left_f: %d right_f: %d left_fraction: %f right_fraction: %f \n", f, left_f, right_f, left_fraction, right_fraction)
+ printf("f: %d left_f: %d right_f: %d left_fraction: %3.2f right_fraction: %3.2f \n", f, left_f, right_f, left_fraction, right_fraction)
% fit splines to left and right masks
% determine mask for left and right frames, sampling at Wo for this frame
sample_freqs_kHz = (1:L)*Wo*4/pi;
- maskdB_left = interp1(left_sample_freqs_kHz, left_AmdB, sample_freqs_kHz);
- maskdB_right = interp1(right_sample_freqs_kHz, right_AmdB, sample_freqs_kHz);
+ maskdB_left = interp1(left_sample_freqs_kHz, left_AmdB, sample_freqs_kHz, "extrap");
+ maskdB_right = interp1(right_sample_freqs_kHz, right_AmdB, sample_freqs_kHz, "extrap");
maskdB_ = left_fraction*maskdB_left + right_fraction*maskdB_right;
endfunction
amp(3) = AmdB(mx_ind);
AmdB_ = max(AmdB_, parabolic_resonator(mx_ind*Wo*4/pi, mask_sample_freqs_kHz) + amp(3));
fr3 = mx_ind*Wo*4/pi;
-
+
% 4th resonator
fmin = fr3 - 0.300;
plot(mask_sample_freqs_kHz*1000, e)
endfunction
+
+% Non linear sampling of frequency axis, reducing the "rate" is a
+% first step before VQ
+
+function mel = ftomel(fHz)
+ mel = floor(2595*log10(1+fHz/700)+0.5);
+endfunction
+
+
+function [rate_K_surface rate_K_sample_freqs_kHz] = resample_const_rate_f_mel(model, K)
+ [frames nc] = size(model);
+ mel_start = ftomel(200); mel_end = ftomel(3700);
+ step = (mel_end-mel_start)/(K-1);
+ mel = mel_start:step:mel_end;
+ rate_K_sample_freqs_Hz = 700*((10 .^ (mel/2595)) - 1);
+ rate_K_sample_freqs_kHz = rate_K_sample_freqs_Hz/1000;
+
+ rate_K_surface = resample_const_rate_f(model, rate_K_sample_freqs_kHz);
+endfunction
+
+
+% Resample Am from time-varying rate L=floor(pi/Wo) to fixed rate K. This can be viewed
+% as a 3D surface with time, freq, and ampitude axis.
+
+function [rate_K_surface rate_K_sample_freqs_kHz] = resample_const_rate_f(model, rate_K_sample_freqs_kHz)
+
+ % convert rate L=pi/Wo amplitude samples to fixed rate K
+
+ max_amp = 80;
+ [frames col] = size(model);
+ K = length(rate_K_sample_freqs_kHz);
+ rate_K_surface = zeros(frames, K);
+
+
+ for f=1:frames
+ Wo = model(f,1);
+ L = min([model(f,2) max_amp-1]);
+ Am = model(f,3:(L+2));
+ AmdB = 20*log10(Am);
+ %pre = 10*log10((1:L)*Wo*4/(pi*0.3));
+ %AmdB += pre;
+
+ % clip between peak and peak -50dB, to reduce dynamic range
+
+ AmdB_peak = max(AmdB);
+ AmdB(find(AmdB < (AmdB_peak-50))) = AmdB_peak-50;
+
+ rate_L_sample_freqs_kHz = (1:L)*Wo*4/pi;
+
+ rate_K_surface(f,:) = interp1(rate_L_sample_freqs_kHz, AmdB, rate_K_sample_freqs_kHz, "spline", "extrap");
+
+ %printf("\r%d/%d", f, frames);
+ end
+ %printf("\n");
+endfunction
+
+
+% Take a rate K surface and convert back to time varying rate L
+
+function [model_ AmdB_] = resample_rate_L(model, rate_K_surface, rate_K_sample_freqs_kHz)
+ max_amp = 80;
+ [frames col] = size(model);
+
+ model_ = zeros(frames, max_amp+3);
+ for f=1:frames
+ Wo = model(f,1);
+ L = model(f,2);
+ rate_L_sample_freqs_kHz = (1:L)*Wo*4/pi;
+
+ % back down to rate L
+
+ AmdB_ = interp1(rate_K_sample_freqs_kHz, rate_K_surface(f,:), rate_L_sample_freqs_kHz, "spline", 0);
+
+ model_(f,1) = Wo; model_(f,2) = L; model_(f,3:(L+2)) = 10 .^ (AmdB_(1:L)/20);
+ end
+endfunction
%model_ = experiment_filter(model);
%model_ = experiment_filter_dec_filter(model);
- [model_ surface] = experiment_mel_freq(model, 0);
+
+ [model_ surface] = experiment_mel_freq(model, 1);
+
+ % extract energy
+
+ % interpolate
+
+ model_ = experiment_dec_linear(model_);
+
+ % add energy back in
+
%[model_ surface] = experiment_mel_diff_freq(model, 0);
- %model_ = experiment_dec_linear(model_);
%[model_ rate_K_surface] = experiment_closed_loop_mean(model);
% ----------------------------------------------------
Am_ = zeros(1,max_amp);
Am_(2:L) = Am(1:L-1);
- % post filter, boosts higher amplitudes more than lower, improving
- % shape of formants and reducing muffling. Note energy normalisation
+ % optional post filter on linear {Am}, boosts higher amplitudes more than lower,
+ % improving shape of formants and reducing muffling. Note energy
+ % normalisation
if postfilter
e1 = sum(Am_(2:L).^2);
endfunction
-% Non linear sampling of frequency axis, reducing the "rate" is a
-% first step before VQ
-
-function mel = ftomel(fHz)
- mel = floor(2595*log10(1+fHz/700)+0.5);
-endfunction
-
-
-function [rate_K_surface rate_K_sample_freqs_kHz] = resample_const_rate_f_mel(model, K)
- [frames nc] = size(model);
- mel_start = ftomel(200); mel_end = ftomel(3700);
- step = (mel_end-mel_start)/(K-1);
- mel = mel_start:step:mel_end;
- rate_K_sample_freqs_Hz = 700*((10 .^ (mel/2595)) - 1);
- rate_K_sample_freqs_kHz = rate_K_sample_freqs_Hz/1000;
-
- rate_K_surface = resample_const_rate_f(model, rate_K_sample_freqs_kHz);
-endfunction
+% experiment to resample freq axis on mel scale, then optionally vq
-function [model_ rate_K_surface] = experiment_mel_freq(model, vq_en=0)
+function [model_ rate_K_surface] = experiment_mel_freq(model, vq_en=0, plots=1)
[frames nc] = size(model);
K = 20;
- [rate_K_surface rate_K_sample_freqs_kHz] = resample_const_rate_f_mel(model, K);
+ [rate_K_surface rate_K_sample_freqs_kHz] = resample_const_rate_f_mel(model, K);
- figure(1); clf; mesh(rate_K_surface);
+ if plots
+ figure(1); clf; mesh(rate_K_surface);
+ end
+
+ for f=1:frames
+ mean_f(f) = mean(rate_K_surface(f,:));
+ rate_K_surface_no_mean(f,:) = rate_K_surface(f,:) - mean_f(f);
+ end
if vq_en
melvq;
- load surface_vq; m=5;
-
- for f=1:frames
- mean_f(f) = mean(rate_K_surface(f,:));
- rate_K_surface_no_mean(f,:) = rate_K_surface(f,:) - mean_f(f);
- end
-
- [res rate_K_surface_ ind] = mbest(surface_vq, rate_K_surface_no_mean, m);
+ load train_120_vq; m=5;
+
+ [res rate_K_surface_ ind] = mbest(train_120_vq, rate_K_surface_no_mean, m);
% pf, needs some energy equalisation, does gd things for hts1a
rate_K_surface_ *= 1.2;
model_ = resample_rate_L(model, rate_K_surface, rate_K_sample_freqs_kHz);
- %figure(2); clf; mesh(model_);
+ if plots
+ figure(2); clf; mesh(rate_K_surface_no_mean);
+ end
-
for f=1:frames
rate_K_surface(f,:) -= mean(rate_K_surface(f,:));
end
-% Resample Am from time-varying rate L=floor(pi/Wo) to fixed rate K. This can be viewed
-% as a 3D surface with time, freq, and ampitude axis.
-
-function [rate_K_surface rate_K_sample_freqs_kHz] = resample_const_rate_f(model, K=50)
-
- % convert rate L=pi/Wo amplitude samples to fixed rate K
-
- max_amp = 80;
- [frames col] = size(model);
- rate_K_sample_freqs_kHz = (1:K)*4/K;
- rate_K_surface = zeros(frames, K);
-
- for f=1:frames
- Wo = model(f,1);
- L = min([model(f,2) max_amp-1]);
- Am = model(f,3:(L+2));
- AmdB = 20*log10(Am);
- rate_L_sample_freqs_kHz = (1:L)*Wo*4/pi;
-
- rate_K_surface(f,:) = interp1(rate_L_sample_freqs_kHz, AmdB, rate_K_sample_freqs_kHz, "spline", "extrap");
- end
-endfunction
-
-
-function [rate_K_surface rate_K_sample_freqs_kHz] = resample_const_rate_f(model, rate_K_sample_freqs_kHz)
-
- % convert rate L=pi/Wo amplitude samples to fixed rate K
-
- max_amp = 80;
- [frames col] = size(model);
- K = length(rate_K_sample_freqs_kHz);
- rate_K_surface = zeros(frames, K);
-
- for f=1:frames
- Wo = model(f,1);
- L = min([model(f,2) max_amp-1]);
- Am = model(f,3:(L+2));
- AmdB = 20*log10(Am);
- rate_L_sample_freqs_kHz = (1:L)*Wo*4/pi;
-
- rate_K_surface(f,:) = interp1(rate_L_sample_freqs_kHz, AmdB, rate_K_sample_freqs_kHz, "spline", 0);
- end
-endfunction
-
-
-% Take a rate K surface and convert back to time varying rate L
-
-function model_ = resample_rate_L(model, rate_K_surface, rate_K_sample_freqs_kHz)
- max_amp = 80;
- [frames col] = size(model);
-
- model_ = zeros(frames, max_amp+3);
- for f=1:frames-1
- Wo = model(f,1);
- L = min(pi/Wo, max_amp-1);
- rate_L_sample_freqs_kHz = (1:L)*Wo*4/pi;
-
- % back down to rate L
-
- AmdB_ = interp1(rate_K_sample_freqs_kHz, rate_K_surface(f,:), rate_L_sample_freqs_kHz, "spline", 0);
-
- model_(f,1) = Wo; model_(f,2) = L; model_(f,3:(L+2)) = 10 .^ (AmdB_(1:L)/20);
- end
-endfunction
% early test, devised to test rate K<->L changes along frequency axis
function newamp1_fbf(samname, f=10)
newamp;
more off;
- quant_en = 0;
+ quant_en = 0; pf_en = 0;
+ melvq;
- load vq;
+ K=20; load train_120_vq; m=5;
% load up text files dumped from c2sim ---------------------------------------
figure(1);
clf;
s = [ Sn(2*f-1,:) Sn(2*f,:) ];
- size(s);
plot(s);
axis([1 length(s) -20000 20000]);
title('Time Domain Speech');
AmdB = 20*log10(Am);
Am_freqs_kHz = (1:L)*Wo*4/pi;
- #{
- [maskdB Am_freqs_kHz] = mask_model(AmdB, Wo, L);
- AmdB_ = maskdB;
- [mx mx_ind] = max(AmdB_);
- AmdB_(mx_ind) += 6;
- #}
+ % plots for mel sampling
- if quant_en
- [AmdB_ residual fvec fvec_] = piecewise_model(AmdB, Wo, vq, 2);
+ [rate_K_vec rate_K_sample_freqs_kHz] = resample_const_rate_f_mel(model(f,:), K);
+
+ mean_f = mean(rate_K_vec);
+ rate_K_vec_no_mean = rate_K_vec - mean_f;
+
+ if quant_en == 2
+ [res rate_K_vec_no_mean_ ind] = mbest(train_120_vq, rate_K_vec_no_mean, m);
else
- [AmdB_ residual fvec] = piecewise_model(AmdB, Wo);
+ rate_K_vec_no_mean_ = rate_K_vec_no_mean;
end
+ if pf_en
+ % pf, needs some energy equalisation, does gd things for hts1a
+ rate_K_surface_ *= 1.2;
+ end
+
+ rate_K_vec_ = rate_K_vec_no_mean_ + mean_f;
+ [model_ AmdB_] = resample_rate_L(model(f,:), rate_K_vec_, rate_K_sample_freqs_kHz);
+
+ % plots ----------------------------------
+
figure(2);
clf;
- title('Frequency Domain');
+ title('Frequency Domain 1');
axis([1 4000 -20 80]);
hold on;
- plot((1:L)*Wo*4000/pi, AmdB,";Am;r+-");
- plot(Am_freqs_kHz*1000, AmdB_, ';model;c');
- plot(fvec*1000, 60*ones(1,4), ';fvec;go');
- if quant_en
- plot(fvec_*1000, 60*ones(1,4), ';fvec q;ro');
+ plot((1:L)*Wo*4000/pi, AmdB,";Am;b+-");
+ plot(rate_K_sample_freqs_kHz*1000, rate_K_vec, ';rate K mel;g+-');
+ if quant_en >= 1
+ plot((1:L)*Wo*4000/pi, AmdB_,";Am quant;k+-");
+ end
+ if quant_en == 2
+ plot(rate_K_sample_freqs_kHz*1000, rate_K_vec_, ';rate K mel quant;r+-');
end
hold off;
+ figure(3);
+ clf;
+ title('Frequency Domain 2');
+ axis([1 4000 -80 80]);
+ hold on;
+ plot((1:L)*Wo*4000/pi, AmdB,";Am;b+-");
+ plot(rate_K_sample_freqs_kHz*1000, rate_K_vec_no_mean, ';rate K mel no mean;g+-');
+ if quant_en == 2
+ plot(rate_K_sample_freqs_kHz*1000, rate_K_vec_no_mean_, ';rate K mel no mean quant;r+-');
+ end
+ hold off;
+
% interactive menu ------------------------------------------
- printf("\rframe: %d menu: n-next b-back q-quit m-quant_en", f);
+ printf("\rframe: %d menu: n-next b-back q-quit m-quant_en[%d]", f, quant_en);
fflush(stdout);
k = kbhit();
if (k == 'm')
- if quant_en
+ quant_en++;
+ if quant_en > 2
quant_en = 0;
- else
- quant_en = 1;
end
endif
if (k == 'n')
endfunction
+#{ Piecewise model stuff, organise later if rqd
+ [maskdB Am_freqs_kHz] = mask_model(AmdB, Wo, L);
+ AmdB_ = maskdB;
+ [mx mx_ind] = max(AmdB_);
+ AmdB_(mx_ind) += 6;
+
+
+ if quant_en
+ [AmdB_ residual fvec fvec_] = piecewise_model(AmdB, Wo, vq, 1);
+ else
+ [AmdB_ residual fvec] = piecewise_model(AmdB, Wo);
+ end
+ fvec
+#}
projects / freetel-svn-tracking.git / commitdiff