Loading scripts/binauralRenderer_interface/matlab_hrir_generation_scripts/SHD_2_ROM.m +6 −4 Original line number Diff line number Diff line Loading @@ -54,8 +54,9 @@ end % convert sphere-sampled HRIRs to SHD HRIRs hrir_len = 128; ambi_order = 3; write_out_sofa = 0; [sofa_path,sofa_name, sofa_ext] = fileparts(sofa_file); IR = generate_HOA_HRIRs_MOD_lens(ambi_order, py_path, sofa_path, [sofa_name,sofa_ext], hrir_len); IR = generate_HOA_HRIRs_MOD_lens(ambi_order, py_path, sofa_path, [sofa_name,sofa_ext], hrir_len, write_out_sofa); % load([thispath,'HRIR_128_48000_dolby_SBA3.mat'],'IR'); gives the same data as the above with default sofa file %% SHD -> CLDFB via least squares error optimization Loading @@ -63,10 +64,11 @@ IR = generate_HOA_HRIRs_MOD_lens(ambi_order, py_path, sofa_path, [sofa_name,sofa num_cldfb_taps = 3; IR_cldfb = zeros(60,num_cldfb_taps,num_ears,num_ch); % 60 frequency bands eval_flag = 0; % optional, = 1 requires signal processing toolbox (fftfilt) legacy_flag = 1; % = 1 used to indicate slightly too short buffers as used to generate tested coefficients for pos = 1:num_ch disp(['Channel ',num2str(pos),'/',num2str(num_ch)]) for ear = 1:num_ears IR_cldfb(:,:,ear,pos) = fir_to_cldfb_fir( IR(:,ear,pos), num_cldfb_taps, eval_flag ); IR_cldfb(:,:,ear,pos) = fir_to_cldfb_fir( IR(:,ear,pos), num_cldfb_taps, eval_flag, legacy_flag ); end end Loading Loading @@ -98,13 +100,13 @@ writeData3L(fid, ['const float rightHRIRImag_' order '[BINAURAL_CONVBANDS][' ord fclose(fid); rmpath(fullfile(thispath,'..','param_bin')); function F = fir_to_cldfb_fir( target_fir, num_cldfb_taps, eval_flag ) function F = fir_to_cldfb_fir( target_fir, num_cldfb_taps, eval_flag, legacy_flag ) [pFilter, D, S, L] = get_cldfb_filter; cldfb_delay = D - S + 1; % processing delay given stride pFilt = sqrt(S)/L * pFilter(:); N = length(pFilt); legacy_flag = 1; % = 1 used to indicate slightly too short buffers as used to generate tested coefficients %legacy_flag = 1; % = 1 used to indicate slightly too short buffers as used to generate tested coefficients % Filter Bank analysis / synthesis filters cldfb_mod_mat = exp(1i*((0:N-1)'-D/2) * ((0:L-1)+0.5) * pi/L ); % N x L modulation matrix with alternating sign periodicity of 2*L in time (row) direction Loading scripts/binauralRenderer_interface/matlab_hrir_generation_scripts/fir_to_cldfb_fir.m 0 → 100644 +300 −0 Original line number Diff line number Diff line %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % (C) 2022-2023 Baseline Development Group with portions copyright Dolby International AB, Ericsson AB, % Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V., Huawei Technologies Co. LTD., % Koninklijke Philips N.V., Nippon Telegraph and Telephone Corporation, Nokia Technologies OY, Orange, % Panasonic Corporation, Qualcomm Technologies, Inc., VoiceAge Corporation. All Rights Reserved. % % This software is protected by copyright law and by international treaties. % The Baseline Development Group consisting of Dolby International AB, Ericsson AB, % Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V., Huawei Technologies Co. LTD., % Koninklijke Philips N.V., Nippon Telegraph and Telephone Corporation, Nokia Technologies OY, Orange, % Panasonic Corporation, Qualcomm Technologies, Inc., and VoiceAge Corporation retain full ownership % rights in their respective contributions in the software. No license of any kind, including but not % limited to patent license, of any foregoing parties is hereby granted by implication, estoppel or % otherwise. % % This software is provided "AS IS", without any express or implied warranties. The software is in the % development stage. It is intended exclusively for experts who have experience with such software and % solely for the purpose of inspection. All implied warranties of non-infringement, merchantability % and/or fitness for a particular purpose are hereby disclaimed and excluded. % % Any dispute, controversy or claim arising under or in relation to providing this software shall be % submitted to and settled by the final, binding jurisdiction of the courts of Munich, Germany in % accordance with the laws of the Federal Republic of Germany excluding its conflict of law rules and % the United Nations Convention on Contracts on the International Sales of Goods. % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function F = fir_to_cldfb_fir( target_fir, num_cldfb_taps, eval_flag, legacy_flag ) % F = fir_to_cldfb_fir( target_fir, num_cldfb_taps, eval_flag, legacy_flag ) % % computes complex-valued FIR coefficients to be applied in the CLDFB analysis domain % which approximate time domain filtering with given target FIR coefficients % in a least squares sense. [pFilter, D, S, L] = get_cldfb_filter; cldfb_delay = D - S + 1; % processing delay given stride pFilt = sqrt(S)/L * pFilter(:); N = length(pFilt); %legacy_flag = 1; % = 1 used to indicate slightly too short buffers as used to generate tested coefficients % Filter Bank analysis / synthesis filters cldfb_mod_mat = exp(1i*((0:N-1)'-D/2) * ((0:L-1)+0.5) * pi/L ); % N x L modulation matrix with alternating sign periodicity of 2*L in time (row) direction cldfb_ansyn_filters = pFilt .* cldfb_mod_mat; % all (L) analysis/synthesis filters target_fir = target_fir(:); fir_length = length(target_fir); %% brute force least squares if legacy_flag num_slots = ceil(fir_length/S) + 10; % used to generate tested IVAS coefficients in CLDFB HRIR ROM with slightly too short buffers inp_len = S * num_slots; len = inp_len - cldfb_delay; idx_opt = cldfb_delay + (1:len); pos_offset = 200; else num_slots = ceil((fir_length + 2 * N - 1) / S); % convolution with target fir, analysis + synthesis filters (of length N each) len = S * num_slots; inp_len = len; idx_opt = (1:len); % use all output samples in the optimization, including the filter bank delay pos_offset = 0; end % Big trial and error Nbins = num_cldfb_taps * L; Vreal = zeros(S*len, Nbins); % all real for all shifts concatenated for each mask bin, Vimag = zeros(S*len, Nbins); % then all imag r = zeros(S*len,1); % right hand side all shifts concatenated x = zeros(inp_len,1); for pos = 1:S % input dirac pulse x(:) = 0; % target impulse response y0 for input pulse at pos out = x; out(pos+pos_offset+(0:fir_length-1)) = target_fir; y0 = [zeros(cldfb_delay,1);out(1:end-cldfb_delay)]; r(len*(pos-1)+(1:len)) = y0(idx_opt); fprintf('.'); % CLDFB analysis for impulse input x(pos+pos_offset) = 1; X = zeros(L,num_slots); frm_idx = (1:N)'; x_tmp = [zeros(N-S,1);x]; for slt = 1:num_slots X(:,slt) = sum(cldfb_ansyn_filters.*flipud(x_tmp(frm_idx))).'; frm_idx = frm_idx + S; end for cldfb_bin = 1:Nbins cldfb_band = rem(cldfb_bin-1,L)+1; cldfb_lag = fix((cldfb_bin-1)/L); % real-valued filter contribution of a single tap frm_idx = cldfb_lag * S + (1:N)'; y_tmp = zeros( num_slots * S + N - S,1); for slt = cldfb_lag+1:num_slots y_tmp(frm_idx) = y_tmp(frm_idx) + real(X(cldfb_band,slt-cldfb_lag) * cldfb_ansyn_filters(:,cldfb_band)); frm_idx = frm_idx + S; end Vreal(len*(pos-1)+1:len*pos,cldfb_bin) = y_tmp(idx_opt); % imaginary-valued filter contribution of a single tap frm_idx = cldfb_lag * S + (1:N)'; y_tmp(:) = 0; for slt = cldfb_lag+1:num_slots y_tmp(frm_idx) = y_tmp(frm_idx) + real(1i*X(cldfb_band,slt-cldfb_lag) * cldfb_ansyn_filters(:,cldfb_band)); frm_idx = frm_idx + S; end Vimag(len*(pos-1)+1:len*pos,cldfb_bin) = y_tmp(idx_opt); end % bin end % pos fprintf('\n'); % solve lsq V = [Vreal,Vimag]; M = V'*V; Mrel = M + 1e-8*norm(M)*eye(size(M)); c = Mrel\(V'*r); % map back to mask locations F = zeros(L,num_cldfb_taps); for cldfb_bin = 1:Nbins F(cldfb_bin) = c(cldfb_bin)+1i*c(Nbins+cldfb_bin); end if eval_flag % evaluation (not needed for table generation, needs signal processing toolbox) get_snr( target_fir, F, cldfb_ansyn_filters, cldfb_delay, S ); end function get_snr( target_fir, cldfb_firs, cldfb_ansyn_filters, cldfb_delay, S ) rng(0); num_samples = 5*48000; x = randn(num_samples,1); % Filter noise in time domain y1 = fftfilt(target_fir,x); % Filter noise in CLDFB domain [N,L] = size(cldfb_ansyn_filters); num_slots = ceil((num_samples + cldfb_delay) / S); % analysis X = zeros(L,num_slots); frm_idx = (1:N)'; x_tmp = [zeros(N-S,1);x;zeros(cldfb_delay,1)]; for slt = 1:num_slots X(:,slt) = sum(cldfb_ansyn_filters.*flipud(x_tmp(frm_idx))).'; frm_idx = frm_idx + S; end % filter X = fftfilt(cldfb_firs.',X.').'; % synthesis frm_idx = (1:N)'; y_tmp = zeros( num_slots * S + N - S,1); for slt = 1:num_slots y_tmp(frm_idx) = y_tmp(frm_idx) + real(sum(X(:,slt).' .* cldfb_ansyn_filters,2)); frm_idx = frm_idx + S; end y2 = y_tmp(cldfb_delay+(1:num_samples)); plot(y1), hold on, plot(y2,'r--'), plot(y1-y2,'k'), hold off set(gca,'xlim',[1,num_samples]) fprintf('SNR: %.1f dB \n', 10*log10(sum(y1.^2)/sum((y1-y2).^2))); legend('time domain','CLDFB domain','difference') title('Filtered noise') function [h, D, S, L] = get_cldfb_filter() % const float LDQMF_60[] in \lib_com\rom_com.c, line 5219 S = 60; % stride L = 60; % frequency bands D = 240 + S - 1; % system delay h = [ 0.0000953076, 0.0001230230, 0.0001279964, 0.0001260533, 0.0001211219 0.0001122123, 0.0001010860, 0.0000876540, 0.0000719883, 0.0000545472 0.0000352143, 0.0000145686, -0.0000074264, -0.0000303788, -0.0000539205 -0.0000782743, -0.0001028838, -0.0001275374, -0.0001520015, -0.0001760167 -0.0001997108, -0.0002226708, -0.0002446725, -0.0002655797, -0.0002852145 -0.0003034996, -0.0003203036, -0.0003356283, -0.0003493345, -0.0003614030 -0.0003719004, -0.0003807641, -0.0003881051, -0.0003939842, -0.0003985357 -0.0004019095, -0.0004041938, -0.0004056677, -0.0004065430, -0.0004069925 -0.0004072535, -0.0004075877, -0.0004083676, -0.0004098394, 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0.0011651339, 0.0001925042, -0.0008409545 -0.0019364181, -0.0030950012, -0.0043176264, -0.0056051607, -0.0069584334 -0.0083780792, -0.0098646237, -0.0114185056, -0.0130400723, -0.0147295250 -0.0164868534, -0.0183120724, -0.0202049762, -0.0221651513, -0.0241921283 -0.0262852497, -0.0284437388, -0.0306666382, -0.0329528190, -0.0353010744 -0.0377098918, -0.0401776619, -0.0427025780, -0.0452826768, -0.0479161367 -0.0506004691, -0.0533332452, -0.0561118126, -0.0589331910, -0.0617944039 -0.0646922663, -0.0676232576, -0.0705836788, -0.0735698044, -0.0765774846 -0.0796026587, -0.0826408863, -0.0856874809, -0.0887378305, -0.0917868018 -0.0948293805, -0.0978601947, -0.1008738130, -0.1038645208, -0.1068264544 -0.1097536832, -0.1126400903, -0.1154794544, -0.1182654947, -0.1209914312 -0.1236500666, -0.1262341589, -0.1287376434, -0.1311538219, -0.1334753036 -0.1356947273, -0.1378047168, -0.1397978216, -0.1416664869, -0.1434033662 -0.1450008005, -0.1464512348, -0.1477471888, -0.1488809884, 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0.1068974212 0.0993694067, 0.0921007246, 0.0850901082, 0.0783365741, 0.0718384907 0.0655927584, 0.0595967993, 0.0538481586, 0.0483424664, 0.0430756323 0.0380428955, 0.0332404599, 0.0286619961, 0.0242999699, 0.0201510899 0.0162059069, 0.0124559226, 0.0088928537, 0.0054926532, 0.0023052765 -0.0005515143, -0.0030201224, -0.0052712574, -0.0073737046, -0.0093160523 -0.0111072771, -0.0127562135, -0.0142635731, -0.0156361461, -0.0168790054 -0.0179969221, -0.0189934950, -0.0198726747, -0.0206398536, -0.0212980714 -0.0218509119, -0.0223025978, -0.0226570386, -0.0229178313, -0.0230882075 -0.0231725387, -0.0231746566, -0.0230979007, -0.0229462404, -0.0227237809 -0.0224345829, -0.0220820960, -0.0216706358, -0.0212045144, -0.0206875466 -0.0201238506, -0.0195175279, -0.0188730918, -0.0181944817, -0.0174855441 -0.0167510118, -0.0159947462, -0.0152208358, -0.0144332750, -0.0136361914 -0.0128338682, -0.0120294262, -0.0112272501, -0.0104311826, -0.0096443929 -0.0088709844, -0.0081134979, -0.0073764324, -0.0066623385, -0.0059733889 -0.0053142183, -0.0046856776, -0.0040914025, -0.0035321070, -0.0030089030 -0.0025271603, -0.0020749648, -0.0016621647, -0.0012705614, -0.0008115423 ]; h = h.'; h = h(:); h(1*120+(1:120)) = -h(1*120+(1:120)); h(3*120+(1:120)) = -h(3*120+(1:120)); h(:) = h(end:-1:1); No newline at end of file Loading
scripts/binauralRenderer_interface/matlab_hrir_generation_scripts/SHD_2_ROM.m +6 −4 Original line number Diff line number Diff line Loading @@ -54,8 +54,9 @@ end % convert sphere-sampled HRIRs to SHD HRIRs hrir_len = 128; ambi_order = 3; write_out_sofa = 0; [sofa_path,sofa_name, sofa_ext] = fileparts(sofa_file); IR = generate_HOA_HRIRs_MOD_lens(ambi_order, py_path, sofa_path, [sofa_name,sofa_ext], hrir_len); IR = generate_HOA_HRIRs_MOD_lens(ambi_order, py_path, sofa_path, [sofa_name,sofa_ext], hrir_len, write_out_sofa); % load([thispath,'HRIR_128_48000_dolby_SBA3.mat'],'IR'); gives the same data as the above with default sofa file %% SHD -> CLDFB via least squares error optimization Loading @@ -63,10 +64,11 @@ IR = generate_HOA_HRIRs_MOD_lens(ambi_order, py_path, sofa_path, [sofa_name,sofa num_cldfb_taps = 3; IR_cldfb = zeros(60,num_cldfb_taps,num_ears,num_ch); % 60 frequency bands eval_flag = 0; % optional, = 1 requires signal processing toolbox (fftfilt) legacy_flag = 1; % = 1 used to indicate slightly too short buffers as used to generate tested coefficients for pos = 1:num_ch disp(['Channel ',num2str(pos),'/',num2str(num_ch)]) for ear = 1:num_ears IR_cldfb(:,:,ear,pos) = fir_to_cldfb_fir( IR(:,ear,pos), num_cldfb_taps, eval_flag ); IR_cldfb(:,:,ear,pos) = fir_to_cldfb_fir( IR(:,ear,pos), num_cldfb_taps, eval_flag, legacy_flag ); end end Loading Loading @@ -98,13 +100,13 @@ writeData3L(fid, ['const float rightHRIRImag_' order '[BINAURAL_CONVBANDS][' ord fclose(fid); rmpath(fullfile(thispath,'..','param_bin')); function F = fir_to_cldfb_fir( target_fir, num_cldfb_taps, eval_flag ) function F = fir_to_cldfb_fir( target_fir, num_cldfb_taps, eval_flag, legacy_flag ) [pFilter, D, S, L] = get_cldfb_filter; cldfb_delay = D - S + 1; % processing delay given stride pFilt = sqrt(S)/L * pFilter(:); N = length(pFilt); legacy_flag = 1; % = 1 used to indicate slightly too short buffers as used to generate tested coefficients %legacy_flag = 1; % = 1 used to indicate slightly too short buffers as used to generate tested coefficients % Filter Bank analysis / synthesis filters cldfb_mod_mat = exp(1i*((0:N-1)'-D/2) * ((0:L-1)+0.5) * pi/L ); % N x L modulation matrix with alternating sign periodicity of 2*L in time (row) direction Loading
scripts/binauralRenderer_interface/matlab_hrir_generation_scripts/fir_to_cldfb_fir.m 0 → 100644 +300 −0 Original line number Diff line number Diff line %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % (C) 2022-2023 Baseline Development Group with portions copyright Dolby International AB, Ericsson AB, % Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V., Huawei Technologies Co. LTD., % Koninklijke Philips N.V., Nippon Telegraph and Telephone Corporation, Nokia Technologies OY, Orange, % Panasonic Corporation, Qualcomm Technologies, Inc., VoiceAge Corporation. All Rights Reserved. % % This software is protected by copyright law and by international treaties. % The Baseline Development Group consisting of Dolby International AB, Ericsson AB, % Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V., Huawei Technologies Co. LTD., % Koninklijke Philips N.V., Nippon Telegraph and Telephone Corporation, Nokia Technologies OY, Orange, % Panasonic Corporation, Qualcomm Technologies, Inc., and VoiceAge Corporation retain full ownership % rights in their respective contributions in the software. No license of any kind, including but not % limited to patent license, of any foregoing parties is hereby granted by implication, estoppel or % otherwise. % % This software is provided "AS IS", without any express or implied warranties. The software is in the % development stage. It is intended exclusively for experts who have experience with such software and % solely for the purpose of inspection. All implied warranties of non-infringement, merchantability % and/or fitness for a particular purpose are hereby disclaimed and excluded. % % Any dispute, controversy or claim arising under or in relation to providing this software shall be % submitted to and settled by the final, binding jurisdiction of the courts of Munich, Germany in % accordance with the laws of the Federal Republic of Germany excluding its conflict of law rules and % the United Nations Convention on Contracts on the International Sales of Goods. % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function F = fir_to_cldfb_fir( target_fir, num_cldfb_taps, eval_flag, legacy_flag ) % F = fir_to_cldfb_fir( target_fir, num_cldfb_taps, eval_flag, legacy_flag ) % % computes complex-valued FIR coefficients to be applied in the CLDFB analysis domain % which approximate time domain filtering with given target FIR coefficients % in a least squares sense. [pFilter, D, S, L] = get_cldfb_filter; cldfb_delay = D - S + 1; % processing delay given stride pFilt = sqrt(S)/L * pFilter(:); N = length(pFilt); %legacy_flag = 1; % = 1 used to indicate slightly too short buffers as used to generate tested coefficients % Filter Bank analysis / synthesis filters cldfb_mod_mat = exp(1i*((0:N-1)'-D/2) * ((0:L-1)+0.5) * pi/L ); % N x L modulation matrix with alternating sign periodicity of 2*L in time (row) direction cldfb_ansyn_filters = pFilt .* cldfb_mod_mat; % all (L) analysis/synthesis filters target_fir = target_fir(:); fir_length = length(target_fir); %% brute force least squares if legacy_flag num_slots = ceil(fir_length/S) + 10; % used to generate tested IVAS coefficients in CLDFB HRIR ROM with slightly too short buffers inp_len = S * num_slots; len = inp_len - cldfb_delay; idx_opt = cldfb_delay + (1:len); pos_offset = 200; else num_slots = ceil((fir_length + 2 * N - 1) / S); % convolution with target fir, analysis + synthesis filters (of length N each) len = S * num_slots; inp_len = len; idx_opt = (1:len); % use all output samples in the optimization, including the filter bank delay pos_offset = 0; end % Big trial and error Nbins = num_cldfb_taps * L; Vreal = zeros(S*len, Nbins); % all real for all shifts concatenated for each mask bin, Vimag = zeros(S*len, Nbins); % then all imag r = zeros(S*len,1); % right hand side all shifts concatenated x = zeros(inp_len,1); for pos = 1:S % input dirac pulse x(:) = 0; % target impulse response y0 for input pulse at pos out = x; out(pos+pos_offset+(0:fir_length-1)) = target_fir; y0 = [zeros(cldfb_delay,1);out(1:end-cldfb_delay)]; r(len*(pos-1)+(1:len)) = y0(idx_opt); fprintf('.'); % CLDFB analysis for impulse input x(pos+pos_offset) = 1; X = zeros(L,num_slots); frm_idx = (1:N)'; x_tmp = [zeros(N-S,1);x]; for slt = 1:num_slots X(:,slt) = sum(cldfb_ansyn_filters.*flipud(x_tmp(frm_idx))).'; frm_idx = frm_idx + S; end for cldfb_bin = 1:Nbins cldfb_band = rem(cldfb_bin-1,L)+1; cldfb_lag = fix((cldfb_bin-1)/L); % real-valued filter contribution of a single tap frm_idx = cldfb_lag * S + (1:N)'; y_tmp = zeros( num_slots * S + N - S,1); for slt = cldfb_lag+1:num_slots y_tmp(frm_idx) = y_tmp(frm_idx) + real(X(cldfb_band,slt-cldfb_lag) * cldfb_ansyn_filters(:,cldfb_band)); frm_idx = frm_idx + S; end Vreal(len*(pos-1)+1:len*pos,cldfb_bin) = y_tmp(idx_opt); % imaginary-valued filter contribution of a single tap frm_idx = cldfb_lag * S + (1:N)'; y_tmp(:) = 0; for slt = cldfb_lag+1:num_slots y_tmp(frm_idx) = y_tmp(frm_idx) + real(1i*X(cldfb_band,slt-cldfb_lag) * cldfb_ansyn_filters(:,cldfb_band)); frm_idx = frm_idx + S; end Vimag(len*(pos-1)+1:len*pos,cldfb_bin) = y_tmp(idx_opt); end % bin end % pos fprintf('\n'); % solve lsq V = [Vreal,Vimag]; M = V'*V; Mrel = M + 1e-8*norm(M)*eye(size(M)); c = Mrel\(V'*r); % map back to mask locations F = zeros(L,num_cldfb_taps); for cldfb_bin = 1:Nbins F(cldfb_bin) = c(cldfb_bin)+1i*c(Nbins+cldfb_bin); end if eval_flag % evaluation (not needed for table generation, needs signal processing toolbox) get_snr( target_fir, F, cldfb_ansyn_filters, cldfb_delay, S ); end function get_snr( target_fir, cldfb_firs, cldfb_ansyn_filters, cldfb_delay, S ) rng(0); num_samples = 5*48000; x = randn(num_samples,1); % Filter noise in time domain y1 = fftfilt(target_fir,x); % Filter noise in CLDFB domain [N,L] = size(cldfb_ansyn_filters); num_slots = ceil((num_samples + cldfb_delay) / S); % analysis X = zeros(L,num_slots); frm_idx = (1:N)'; x_tmp = [zeros(N-S,1);x;zeros(cldfb_delay,1)]; for slt = 1:num_slots X(:,slt) = sum(cldfb_ansyn_filters.*flipud(x_tmp(frm_idx))).'; frm_idx = frm_idx + S; end % filter X = fftfilt(cldfb_firs.',X.').'; % synthesis frm_idx = (1:N)'; y_tmp = zeros( num_slots * S + N - S,1); for slt = 1:num_slots y_tmp(frm_idx) = y_tmp(frm_idx) + real(sum(X(:,slt).' .* cldfb_ansyn_filters,2)); frm_idx = frm_idx + S; end y2 = y_tmp(cldfb_delay+(1:num_samples)); plot(y1), hold on, plot(y2,'r--'), plot(y1-y2,'k'), hold off set(gca,'xlim',[1,num_samples]) fprintf('SNR: %.1f dB \n', 10*log10(sum(y1.^2)/sum((y1-y2).^2))); legend('time domain','CLDFB domain','difference') title('Filtered noise') function [h, D, S, L] = get_cldfb_filter() % const float LDQMF_60[] in \lib_com\rom_com.c, line 5219 S = 60; % stride L = 60; % frequency bands D = 240 + S - 1; % system delay h = [ 0.0000953076, 0.0001230230, 0.0001279964, 0.0001260533, 0.0001211219 0.0001122123, 0.0001010860, 0.0000876540, 0.0000719883, 0.0000545472 0.0000352143, 0.0000145686, -0.0000074264, -0.0000303788, -0.0000539205 -0.0000782743, -0.0001028838, -0.0001275374, -0.0001520015, -0.0001760167 -0.0001997108, -0.0002226708, -0.0002446725, -0.0002655797, -0.0002852145 -0.0003034996, -0.0003203036, -0.0003356283, -0.0003493345, -0.0003614030 -0.0003719004, -0.0003807641, -0.0003881051, -0.0003939842, -0.0003985357 -0.0004019095, -0.0004041938, -0.0004056677, -0.0004065430, -0.0004069925 -0.0004072535, -0.0004075877, -0.0004083676, -0.0004098394, 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