function data = exp_osses2021(varargin)
%EXP_OSSES2021 -
%
% Usage: data = exp_osses2021(flags)
%
% exp_osses2021 reproduces Figs. 4, 11 and 14 from Osses and Kohlrausch (2021),
% where a modified version of the dau1997 model is used.
% The figures are similar to Figs. 4.14, C.9B, and C.11B from Osses (2018).
%
%
% The following flags can be specified:
%
% 'redo' Recomputes data for specified figure
%
% 'plot' Plot the output of the experiment. This is the default.
%
% 'no_plot' Don't plot, only return data.
%
% 'fig4_osses2020' Reproduce Fig. 4 of Osses et al. (2020).
%
% 'fig14_osses2020' Reproduce Fig. 14 of Osses et al. (2020).
% 'fig4' Reproduce Fig. 4 of Osses and Kohlrausch (2021). This is the
% same figure as Fig. 4 of Osses and Kohlrausch (2020, preprint)
%
% 'fig11' Reproduce Fig. 11 of Osses and Kohlrausch (2021). This is the
% same figure as Fig. 14 of Osses and Kohlrausch (2020, preprint)
%
% 'fig14' Reproduce Fig. 14 of Osses and Kohlrausch (2021).
%
% Fig. 4 - Two internal representations of a piano sound ('P1') using the
% PEMO model with two configurations of the adaptation loops are shown:
% Overshoot limitation with a factor of 5, as suggested in Osses and
% Kohlrausch (2021), and with a factor of 10 (see Dau et al., 1997).
% To display Fig. 4 of Osses and Kohlrausch (2021) use :
%
% out = exp_osses2021('fig4'); % same as: out = exp_dau1997('fig4_osses2020');
%
% Fig. 11 - The effect of the overshoot limitation with factors of 5 and 10
% are shown for a 4-kHz pure tone of 70 dB SPL that includes 2.5-ms up/down
% ramps. For these plots the outer and middle ear stages are skipped. One
% gammatone filter at 4 kHz is used, followed by the IHC stage (ihc_breebaart2001),
% and the adaptation loops (adt_osses2021 for lim=5, adt_dau1997 for lim=10).
%
% To display Fig. 11 of Osses and (2020) use :
%
% out = exp_osses2021('fig11'); % same as: out = exp_dau1997('fig14_osses2020');
%
% Fig. 14 - Modulation transfer functions for the 12 modulation filters in
% modfilterbank.m. This figure is obtained for a click of unit amplitude
% while all modules in osses2021 are by-passed except for the modulation
% filter bank. In the modulation filter bank, the phase insensitivity for
% filters with mfc>10 is disabled (see App. C of Osses and Kohlrausch, 2021)
% in a way that the outputs of the modulation filter are the complex valued
% filtered signals for each mfc.
% To display Fig. 14 of Osses and Kohlrausch (2021) use :
%
% out = exp_osses2021('fig14');
%
%
% Url: http://amtoolbox.org/amt-1.1.0/doc/experiments/exp_osses2021.php
% Copyright (C) 2009-2021 Piotr Majdak, Clara Hollomey, and the AMT team.
% This file is part of Auditory Modeling Toolbox (AMT) version 1.1.0
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
% References: osses2021 Osses2020b Osses2018 dau1997mapI jepsen2008
%
% #Author: Alejandro Osses (2020, 2021)
data = [];
definput.import={'amt_cache'};
definput.flags.type={'missingflag','fig4','fig11','fig14'}; % Osses and Kohlrausch 2021, JASA
definput.flags.plot={'plot','no_plot'};
[flags,keyvals] = ltfatarghelper({},definput,varargin);
if flags.do_missingflag
flagnames=[sprintf('%s, ',definput.flags.type{2:end-2}),...
sprintf('%s or %s',definput.flags.type{end-1},definput.flags.type{end})];
error('%s: You must specify one of the following flags: %s.',upper(mfilename),flagnames);
end
%% ------ FIG 4 Osses and Kohlrausch 2021 ---------------------------------
if flags.do_fig4
% Goes to 'http://sofacoustics.org/data/amt-0.10.0/auxdata/' and loads
% the data under the folder 'dau1997', with name 'P1-GH05-Cd5_1-dur-1300-ms.wav'
[insig, fs] = amt_load('dau1997','P1-GH05-Cd5_1-dur-1300-ms.wav');
tobs = 0.25; % s, only the first 0.25 s of the waveform
insig = insig(1:fs*tobs);
subfs = 16000; % sampling frequency for the internal representation
%%% Using osses2021:
flags_common = {'afb_osses2021','ihc_breebaart2001','mfb_jepsen2008'};
[outsig05,fc,mfc] = osses2021(insig,fs,'subfs',subfs,flags_common{:},'adt_osses2021');
outsig10 = osses2021(insig,fs,'subfs',subfs,flags_common{:},'adt_dau1997');
N = length(fc); % number of audio frequencies
K = length(mfc);
%%% Memory allocation:
Ik_05 = zeros(1,K); % one value for each modulation frequency
Ik_10 = zeros(1,K); % one value for each modulation frequency
Im_05 = zeros(1,N); % one value for each audio frequency
Im_10 = zeros(1,N); % one value for each audio frequency
%%%
for j = 1:N
Im_05(j) = Im_05(j)+1/subfs*sum(outsig05{j}(:).^2); % all mod. filters together
Im_10(j) = Im_10(j)+1/subfs*sum(outsig10{j}(:).^2);
end
for i = 1:K
for j = 1:N
Nr_mod_filters = size(outsig05{j},2);
if i <= Nr_mod_filters
% summed up only if the mod filter i is present.
Ik_05(i) = Ik_05(i)+1/subfs*sum(outsig05{j}(:,i).^2);
Ik_10(i) = Ik_10(i)+1/subfs*sum(outsig10{j}(:,i).^2);
else
% Nothing to do, in this case mfc(i) > 1/4*fc(j)
end
end
end
Itot_05 = sum(Ik_05);
Itot_10 = sum(Ik_10);
fc_erb = freqtoaud(fc);
mfc_nr = 1:K;
if flags.do_plot
% Panel A
figure;
plot(fc_erb,100*Im_05/Itot_05,'ro-'); hold on; grid on;
plot(fc_erb,100*Im_10/Itot_10,'bs--');
set(gca,'XTick',3:33);
set(gca,'YTick',0:1:10);
ylim([-1 11])
xlim([2 34])
legend('lim=5 (Osses2021)','lim=10');
Pos = get(gcf,'Position');
Pos(3) = 800;
set(gcf,'Position',Pos); % setting width of the figure
xlabel('Audio centre frequency f_c (ERB_N)');
ylabel('Percentage (%)');
title('A. Information-based audio-frequency analysis')
% Panel B
figure;
plot(mfc_nr,100*Ik_05/Itot_05,'ro-'); hold on; grid on;
plot(mfc_nr,100*Ik_10/Itot_10,'bs--');
set(gca,'XTick',1:12);
set(gca,'YTick',0:3:24);
xlim([0 13])
ylim([-1 27])
legend('lim=5 (Osses2021)','lim=10');
xlabel('Modulation centre frequency mf_c (Nr.)');
ylabel('Percentage (%)');
title('B. Information-based modulation-frequency analysis')
end
data.figure_flag = 'do_fig4';
data.fc = fc;
data.mfc = mfc;
data.Ik_05 = Ik_05;
data.Ik_10 = Ik_10;
data.Ik = 'Model Units (MU)';
data.Im_05 = Im_05;
data.Im_10 = Im_10;
data.Im_unit = 'Model Units (MU)';
data.Itot_05 = Itot_05;
data.Itot_10 = Itot_10;
data.Itot_unit = 'Model Units (MU)';
data.description = 'Energy content (MU) for each audio frequency band n, and each modulation frequency band k';
end
%% ------ FIG 11 Osses and Kohlrausch 2021 --------------------------------
if flags.do_fig11
% 1. Stimulus creation:
fs = 44100;
dur = 300e-3; % 300 ms
lvl = 70;
dBFS = 100; % AMT default
t = (1:dur*fs)/fs; t = t(:); % creates 't' as a column array
fc = 4000;
dur_ramp_ms = 2.5;
dur_ramp = round((dur_ramp_ms*1e-3)*fs); % duration ramp in samples
insig = sin(2*pi*fc.*t);
insig = scaletodbspl(insig,lvl,dBFS); % calibration before applying the ramp
rp = ones(size(insig));
rp(1:dur_ramp) = rampup(dur_ramp);
rp(end-dur_ramp+1:end) = rampdown(dur_ramp);
insig = rp.*insig;
insig = [zeros(50e-3*fs,1); insig; zeros(200e-3*fs,1)]; % 50 and 200 ms
% of silence before and after the sine tone
t = (1:length(insig))/fs; t = t(:); % creates 't' as a column array
kv_here = {'basef',fc,'flow',fc,'fhigh',fc};
flags_here = {'no_outerear','no_middleear','ihc','adt','no_mfb'};
outsig05 = osses2021(insig,fs,kv_here{:},flags_here{:});
outsig10 = osses2021(insig,fs,kv_here{:},'adt_dau1997',flags_here{:});
%%%
onset05 = max(outsig05);
onset10 = max(outsig10);
id_steady = find(t>=.330-dur_ramp_ms*1e-3 & t<=.350-dur_ramp_ms*1e-3);
steady05 = mean(outsig05(id_steady));
steady10 = mean(outsig10(id_steady));
ra05 = onset05/steady05;
ra10 = onset10/steady10;
fprintf('Lim 5: Onset = %.1f MU, steady = %.1f MU\n',onset05,steady05);
fprintf('Lim 10: Onset = %.1f MU, steady = %.1f MU\n',onset10,steady10);
if flags.do_plot
leg4plot{1} = sprintf('lim = 5: ratio onset/steady=%.1f',ra05);
leg4plot{2} = sprintf('lim = 10: ratio onset/steady=%.1f',ra10);
figure;
plot(t,outsig05,'r-','LineWidth',2); hold on, grid on;
plot(t,outsig10,'b-')
xlabel('Time (s)');
ylabel('Amplitude \Psi (Model Units)')
legend(leg4plot);
set(gca,'XTick',[50:50:450]*1e-3);
xlim([0.025 0.475]);
ylim([-300 1480])
set(gca,'YTick',-200:100:1400)
end
data.figure_flag = 'do_fig11';
data.ra05 = ra05;
data.onset05 = onset05;
data.steady05 = steady05;
data.ra10 = ra10;
data.onset10 = onset10;
data.steady10 = steady10;
data.onset_unit = 'Model Units (MU)';
data.steady_unit = 'Model Units (MU)';
end
%% ------ FIG 14 Osses and Kohlrausch 2021 --------------------------------
if flags.do_fig14
% From local file: g20210330_characterising_MFB_review2021.m
N = 2^16; % arbitrary number of samples: more samples = more FFT resolution,
% (no zero-padding or whatsoever)
K = N/2;
fs = 44100;
insig = [zeros(N/2-1,1); 1; zeros(N/2,1)]; % temporally centred dirac
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 1.1 Calculation with impulse responses:
kv = {'silent_mode',0}; % to activate the screen display
flags_common = {'no_outerear','no_middleear','no_afb','no_ihc','no_adt','mfb','no_phase_insens'};
[out1,~,~,~] = osses2021(insig,fs,kv{:},'mfb_dau1997' ,flags_common{:});
[out2,~,mfc,params] = osses2021(insig,fs,kv{:},'mfb_jepsen2008' ,flags_common{:});
[out3,~,~,~] = osses2021(insig,fs,kv{:},'mfb_osses2021_att_gain',flags_common{:});
out1 = out1{1};
out2 = out2{1};
out3 = out3{1};
for k = 1:size(out1,2)
HdB(:,k) = 20*log10(abs(freqz(out1(:,k),1,K))); % mfb_dau1997 % HdB = To_dB(abs(hresp));
HdB_tot(:,k) = 20*log10(abs(freqz(out2(:,k),1,K))); % mfb_jepsen2008
HdB_new(:,k) = 20*log10(abs(freqz(out3(:,k),1,K))); % mfb_osses2021_att_gain
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 1.2 Calculation using the coefficients:
f = (0:K-1)/K*(fs/2);
for k = 1:size(out1,2)
h_here = filter(params.mfb_b(k,:),params.mfb_a(k,:),insig);
HdB_coeff(:,k) = 20*log10(abs(freqz(h_here,1,K))); % mfb_dau1997 % HdB = To_dB(abs(hresp));
insig_filt = filter(params.b_lp_150_Hz,params.a_lp_150_Hz,insig);
h_here = filter(params.mfb_b(k,:),params.mfb_a(k,:),insig_filt);
HdB_tot_coeff(:,k) = 20*log10(abs(freqz(h_here,1,K))); % mfb_jepsen2008
hlpf = freqz(insig_filt,1,K);
hlpf_dB = 20*log10(abs(hlpf));
gain_mfcs = interp1(f,hlpf_dB,mfc); % gains according to the 150-Hz filter bank
gain_lin = 10.^(gain_mfcs/20);
h_here = filter(gain_lin(k)*params.mfb_b(k,:),params.mfb_a(k,:),insig);
HdB_new_coeff(:,k) = 20*log10(abs(freqz(h_here,1,K))); % mfb_osses2021_att_gain
end
if flags.do_plot
%%% 2. Plotting
% Trick to add XTick labels
XLT = [];
XL = [0.1 1 2.5 5 10 20 50 125 250 500 1000 2000];
for i = 1:length(XL)
if XL(i) < 1000
XLT{i} = num2str(XL(i));
else
XLT{i} = [num2str(XL(i)/1000) 'k'];
end
end
h = [];
N_mfb_types = 3;
figure;
for j = 1:N_mfb_types
% figure(j);
subplot(3,1,j);
for i = 1:12;
switch j
case 1 % No LPF
HdB_here = HdB(:,i);
HdB_here2 = HdB_coeff(:,i);
case 2 % With LPF
HdB_here = HdB_tot(:,i);
HdB_here2 = HdB_tot_coeff(:,i);
case 3 % With LPF as suggested
HdB_here = HdB_new(:,i);
HdB_here2 = HdB_new_coeff(:,i);
end
if i >= 10
LW = 2;
else
LW = 1;
end
semilogx(f,HdB_here ,'k','LineWidth',LW); hold on, grid on
plot(f,HdB_here2,'r--','LineWidth',2);
switch j
case 1
title('MTFs: dau1997')
case 2
title('MTFs: osses2021 (as used by Osses & Kohlrausch, 2021)')
case 3
title('MTFs: osses2021-att-gain (as suggested for further development)')
end
if j == 2 || j == 3
plot(f,hlpf_dB,':','LineWidth',2,'Color',0.5*[1 1 1]); hold on
end
end
h(end+1) = gcf;
ylim([-53 3]);
xlim([.9 2200])
set(gca,'XTick',XL)
set(gca,'XTickLabel',XLT)
xlabel('Frequency (Hz)')
ylabel({'','Amplitude (dB)'})
ylim([-20 6])
set(gca,'YTick',-18:3:3);
end
set(gcf,'Position',[0 0 570 700]);
legend('from insig','from filter coeff.','150-Hz LPF');
end
data.figure_flag = 'do_fig14';
data.figure_description = 'Modulation transfer function of the modulation filters using three configurations';
end