DSP System Toolbox
This example shows how to simulate a digital audio multiband dynamic range compression system.
Dynamic range compression reduces the dynamic range of a signal by attenuating the level of strong peaks, while leaving weaker peaks unchanged. Compression has applications in audio recording, mixing, and in broadcasting.
Multiband compression compresses different audio frequency bands separately, by first splitting the audio signal into multiple bands and then passing each band through its own independently adjustable compressor. Multiband compression is widely used in audio mastering and is often included in audio workstations.
The multiband compressor in this example first splits an audio signal into different bands using a multiband crossover filter. Linkwitz-Riley crossover filters are used to obtain an overall allpass frequency response. Each band is then compressed using a separate dynamic range compressor. Key compressor characteristics, such as the compression ratio, the attack and release time, the threshold and the knee width, are independently tunable for each band. The effect of compression on the dynamic range of the signal is showcased.
A Linkwitz-Riley crossover filter consists of a combination of a lowpass and highpass filter, each formed by cascading two lowpass or highpass Butterworth filters. Summing the response of the two filters yields a gain of 0 dB at the crossover frequency, so that the crossover acts like an allpass filter (and therefore introducing no distortion in the audio signal).
dspdemo.LinkwitzRileyFilter implements a Linkwitz-Riley System object. Here is an example where an eighth order Linkwitz-Riley crossover is used to filter a signal. Notice that the lowpass and highpass sections each have a -6 dB gain at the crossover frequency. The sum of the lowpass and highpass sections is allpass.
Fs = 44.1e3; % Linkwitz-Riley filter hlr = dspdemo.LinkwitzRileyFilter( 'FilterOrder',8,... 'SampleRate',Fs,... 'CrossoverFrequency',5e3); % Transfer function estimator htfe = dsp.TransferFunctionEstimator('FrequencyRange','onesided',... 'SpectralAverages',20); frameLength = 1024; hplot = dsp.ArrayPlot(... 'PlotType','Line',... 'YLimits', [-40 1],... 'YLabel','Magnitude (dB)',... 'XScale','log',... 'SampleIncrement', (Fs/2)/(frameLength/2+1),... 'XLabel','Frequency (Hz)',... 'Title','Eighth order Linkwitz-Riley Crossover Filter',... 'ShowLegend', true); for i=1:50 in = randn(1024,1); % Return lowpass and highpass responses of the crossover filter [ylp,yhp] = step(hlr,in); % sum the responses y = ylp+yhp; v = step(htfe,repmat(in,1,3),[ylp yhp y]); step(hplot,20*log10(abs(v))); end
dspdemo.MultibandCrossoverFilter implements a multiband crossover filter by combining Linkwitz-Riley crossover filters and allpass filters in a tree-like structure. The filter divides the spectrum into multiple bands such that their sum is a perfect allpass filter.
The example below shows a four-band crossover filter formed of eighth order Linkwitz-Riley crossover filters. Notice the allpass response of the sum of the four bands.
Fs = 44100; hCrossOver = dspdemo.MultibandCrossoverFilter ... ('NumBands',4,... 'CrossoverFrequencies',[2e3 5e3 10e3],... 'SampleRate' , Fs); htfe = dsp.TransferFunctionEstimator... ('FrequencyRange','onesided',... 'SpectralAverages',20); L = 2^14; hplot = dsp.ArrayPlot('PlotType','Line',... 'XOffset',0,... 'YLimits',[-120 5], ... 'XScale','log',... 'SampleIncrement', .5 * Fs/(L/2 + 1 ),... 'YLabel','Frequency Response (dB)',... 'XLabel','Frequency (Hz)',... 'Title','Four-Band Crossover Filter',... 'ShowLegend',true); for i=1:10 in = randn(L,1); % Split the signal into four bands [ylp,ybp1,ybp2,yhp] = step(hCrossOver,in); y = ylp + ybp1 + ybp2 + yhp; z = step(htfe,repmat(in,1,5),[ylp,ybp1,ybp2,yhp,y]); step(hplot,20*log10(abs(z))) end
dspdemo.DynamicRangeCompressor is a dynamic range compressor System object. The input signal is compressed when it exceeds the specified threshold. The amount of compression is controlled by the specified compression ratio. The attack and release times determine how quickly the compressor starts or stops compressing. The knee width provides a smooth transition for the compressor gain around the threshold. Finally, a make-up gain can be applied at the output of the compressor. This make-up gain amplifies both strong and weak peaks equally.
The static compression characteristic of the compressor depends on the compression ratio, the threshold and the knee width. The example below illustrates the static compression characteristic for different values of the knee width.
xdB = (-10:0.01:5).'; hcomp = dspdemo.DynamicRangeCompressor('Threshold',-3,... 'CompressionRatio',5); % Vary the knee width and record the static compression characteristic hcomp.KneeWidth = 0; y0dB = xdB + computeGain(hcomp,xdB); hcomp.KneeWidth = 5; y5dB = xdB + computeGain(hcomp,xdB); hcomp.KneeWidth = 10; y10dB = xdB + computeGain(hcomp,xdB); hplot = dsp.ArrayPlot(... 'SampleIncrement',.01,... 'PlotType','Line',... 'XOffset',-10,... 'XLabel','Input (dB)',... 'YLabel','Output (dB)',... 'YLimits',[-10 0],... 'Title','Static Compression Characteristic for Different Knee Widths',... 'ShowLegend',true); step(hplot,[y0dB y5dB y10dB]);
The compressor's attack time is defined as the time (in sec) it takes for the compressor's envelope detector to rise from 10% to 90% of its final value when the signal level exceeds the threshold. The compressor's release time is defined as the time (in sec) it takes the compressor's envelope detector to drop from 90% to 10% its final value when the signal level drops below the threshold. The example below illustrates the signal envelope for different release and attack times:
Fs = 44100; % Construct a simple step-like input x = [ones(Fs,1);zeros(Fs,1)]; hcomp = dspdemo.DynamicRangeCompressor('SampleRate',Fs,'KneeWidth',0); % Vary the attack and release times of the compressor, and record the % output envelope. hcomp.AttackTime = 0.01; hcomp.ReleaseTime = .02; [~,yen1] = step(hcomp,x); reset(hcomp); hcomp.AttackTime = 0.05; hcomp.ReleaseTime = .1; [~,yen2] = step(hcomp,x); reset(hcomp); hcomp.AttackTime = 0.2; hcomp.ReleaseTime = .4; [~,yen3] = step(hcomp,x); hplot = dsp.TimeScope(... 'SampleRate',Fs,... 'PlotType','Line',... 'YLabel','Compressor Gain',... 'YLimits',[0 1],... 'Title','Signal Envelope for different attack and Release times',... 'ShowLegend',true,... 'TimeSpan',2,... 'ShowGrid',true); step(hplot,[x yen1 yen2 yen3]);
The example below illustrates the effect of dynamic range compression on an audio signal. The compession threshold is set to -10 dB, and the compression ratio is 5.
Fs = 22050; hread = dsp.AudioFileReader('speech_dft.mp3'); hcomp = dspdemo.DynamicRangeCompressor('SampleRate',Fs,... 'Threshold',-10,... 'CompressionRatio',5); hplot = dsp.TimeScope('YLimits',[-1 1],... 'SampleRate',22050,... 'TimeSpanOverrunAction','Scroll',... 'BufferLength',5e5,... 'TimeSpan',5,... 'ShowGrid',true,... 'ShowLegend',true,... 'Title','Uncompressed versus Compressed Audio'); while ~isDone(hread) x = step(hread); y = step(hcomp,x); step(hplot,[x,y]); end
The following model implements the multiband dynamic range compression example:
model = 'multibanddynamiccompression'; open_system(model)
In this example, the audio signal is first divided into four bands using a multiband crossover filter. Each band is compressed using a separate compressor. The four bands are then recombined to form the audio output. The dynamic range of the uncompressed and compressed signals (defined as the ratio of the largest absolute value of the signal to the signal RMS) is computed. To hear the difference between the original and compressed audio signals, toggle the switch on the top level.
The multiband crossover filter and the dynamic range compressors are modeled using the dspdemo.MultibandCrossoverFilter and dspdemo.DynamicRangeCompressor System objects used inside a MATLAB System block, respectively.
The model integrates a User Interface (UI) designed to interact with the simulation. The UI allows you to tune parameters and the results are reflected in the simulation instantly. To launch the UI that controls the simulation, click the 'Launch Parameter Tuning UI' link on the model.
The model generates code when it is simulated. Therefore, it must be executed from a folder with write permissions.
currDir = pwd; % Store the current directory address addpath(currDir) mexDir = [tempdir 'multibanddynamiccompressionDir']; % Name of % temporary directory if ~exist(mexDir,'dir') mkdir(mexDir); % Create temporary directory end cd(mexDir); % Change directory set_param(model,'StopTime','(1/44100) * 8192 * 20'); sim(model); cd(currDir);
Close the model:
HelperMultibandCompressionSim is the MATLAB function containing the multiband dynamic range compression example's implementation. It instantiates, initializes and steps through the objects forming the algorithm.
Plotting occurs when the 'plotResults' input to the function is 'true'.
Execute multibandAudioCompressionExampleApp to run the simulation and plot the results on scopes. Note that the simulation runs for as long as the user does not explicitly stop it.
multibandAudioCompressionExampleApp launches a UI designed to interact with the simulation. The UI allows you to tune parameters and the results are reflected in the simulation instantly. For more information on the UI, please refer to HelperCreateParamTuningUI.
MATLAB Coder can be used to generate C code for the function HelperMultibandCompressionSim. In order to generate a MEX-file for your platform, execute the following:
currDir = pwd; % Store the current directory address mexDir = [tempdir 'multibanddynamiccompressionDir']; % Name of % temporary directory if ~exist(mexDir,'dir') mkdir(mexDir); % Create temporary directory end cd(mexDir); % Change directory codegen('HelperMultibandCompressionSim');
By calling the wrapper function multibandAudioCompressionExampleApp with
'true' as an argument, the generated MEX-file can be used instead of
HelperMultibandCompressionSim for the simulation. In this scenario, the UI is still running inside the MATLAB environment, but the main processing algorithm is being performed by a MEX-file. Performance is improved in this mode without compromising the ability to tune parameters.
 'Digital Dynamic Range Compressor Design - Tutorial and Analysis', Giannoulis, Dimitrios; Massberg, Michael; Reiss, Joshua D., JAES Volume 60 Issue 6 pp. 399-408; June 2012
 'Complementary N-Band IIR Filterbank Based on 2-Band Complementary Filters', Favrot, Alexis ; Faller, Christof, IWAENC 2010 Proceedings.
 'An Extension of the Linkwitz-Riley Crossover Filters for Audio Systems and their Sampled Data Implementation', Harris, Fred; Venosa, Elettra ; Chen, Xiaofei ; Muthyala, Prafulla ; Dick, Chris, IWSSIP 2013 Proceedings.