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Version 0.1.3

Please use the latest version 0.1.3 of the model initiative available here. This version includes corrections to previous bugs present in older versions.

For a quick start with Matlab see quick_start.txt and quick_example.txt in the model_initiative folder.


This document aims to describe how to use matlab/octave and/or python to launch auditory pathway models and detectors in the context of a model comparison framework described in more details below.

A: A classical experiment in psychoacoustics B: Structure of the model comparison framework: models process the sound files generated by the experiment side. The output of the model is then fed to the detector which comes up with a decision.

From the figure above two sides can be observed: the experiment side and the model/detector side.

Launching the experiment side

The experiment side is in charge of generating the sound files (.wav) located in the fileexchange folder which will then be processed by the model side. Launching the experiment side requires a couple of matlab toolboxes (note that they are not all mandatory for a quick start):

Setting up the AFC toolbox

The easiest way to set it up is probably to uncompress the afc folder after downloading it and copy/paste it in the main model_initiative repo (ie where the other folders model_server, fileexchange... are). You can now open a matlab instance, navigate to the main model_initiative folder and run the model_initiative_init_experiment script to add the necessary paths to the matlab path. Then run AFC_init. After that navigate to the afc folder and run the afc_addpath script. You can then run for instance the following:


The available afc experiments are located in the /experiments/afc folder.

Setting up the AMT toolbox

Download the latest version, place the uncompressed folder in the model_initiative folder.You can now open a matlab instance, navigate to the main model_initiative folder and run the model_initiative_init_experiment script to add the necessary paths to the matlab path. Then follow the instructions provided in the readme files in the thirdparty folder of folder to install ltfat and sfs.Then add the amt folder to your matlab path and run the AMT_init script to set up AMT. The AMT toolbox is needed if the user wants to run the Breebaart 2001 model and detector. AMT can also run experiments. For instance: exp_breebaart2001('bfig3','redo','BInit','directory',simwork.iopath); if this error occurs : Error using ltfatarghelper [ERROR] (../../mex/ltfatarghelper.c:491:) struc is NULL, please close matlab, go to ltfat/mex and delete the file ltfatarghelper.mexw64. You can then restart matlab and things should work.

Setting up the binaural cross-correlogram toolbox

After downloading the toolbox, it is recommended to place it in the pathway_model folder (although any other directory in the matlab path would work as well). Additional files to run the Bernstein_Trahiotis_crosscor_2012 pathway model and the centroid_lateralization detector can be found in the /pathway_models/additional_Bernstein_Trahiotis_files folder.

Launching the model/detector side

Comparing different computational models can be challenging when models are written in different languages. The model_initiative library addresses that issue by allowing the user to launch matlab/octave models and detectors as well as python models and detectors from a common command line (either matlab or python command line). The main idea behind that is to create threads in which models and detectors run. These threads are created and closed automatically when the user runs either the model_server matlab function or the model_server_python function. Because the way to launch matlab,octave or python threads varies with the platform that the user runs (Windows, MacOS, Linux), some small editing/configuring might be necessary to use the library. These edits will be explained further in the following subsections.

Minimum requirements for the matlab user

  • Matlab, above R2013a

To run python examples, the python requirements must be satisfied as well

Minimum requirements for the octave user

Minimum requirements for the python2 user

Both libraries should be installed to guarantee full functionality. To run matlab examples, matlab requirements must be satisfied as well.

Set up and configuration depending on the user’s OS

The model and detector threads are launched from the python_model_server_call.m, and from the and detector_interface_matlab.m functions located in the model_server folder(see call graph below).

  • For Windows users: If you want to use Octave, you might have to add to your PATH environment variable the bin folder of the Octave library. Once this is done, everything should work normally. To do so please follow the instructions:
  1. Go to the Windows Start Menu
  2. Right Click ”Computer”
  3. Select ”Properties”
  4. A dialogue should pop up with a link on the left called ”Advanced system settings”. Click it.
  5. In the System Properties dialogue, click the button called ”Environment Variables”.
  6. In the Environment Variables dialogue look for ”Path” under the System Variables window.
  7. Add ;C:\Octave-4.0.0\bin to the end of it. The semicolon is the path separator on windows.
  8. Click Ok and close the dialogues.
  • For Linux users: Matlab runs bash commands using its own version of libstdc++, that version might be incompatible with the one that exists on your system. A fix to it is to export to your library PATH the path to the directory where the file is. On many computers that path is located in the directory /usr/lib/i386-linux-gnu . If on your computer that path is located somewhere else then please edit the detector_interface_matlab.m and the python_model_server_call.m and change the path in all commands starting with export LD_LIBRARY_PATH=/usr/lib/i386-linux-gnu with your own path. Everything else should work well after that change.

  • For the MacOS users: it is assumed that Matlab and Octave were installed by the user in the Applications folder (default folder used by MacOS when software is installed). The matlab and octave binary files are not directly callable from the command line. To change that, a couple of symbolic links must be set up.

    • For matlab: Open a terminal window, from there type: sudo ln -s /path to your matlab bin /usr/local/bin/matlab The matlab binary file is usually located at /Applications/ where XXXX is the version of matlab.

    • For Octave: Open a terminal window,from there type: sudo ln -s /path to your octave-cli-XXX bin /usr/local/bin/octave-cli Usually, the octave-cli-XXX binary file is located at: /Applications/, where X.X.X is the version number.

Quick description of the organization of the library

  • fileexchange folder hosts the different files that are exchanged between the experiment side, the model side and the detector side.
  • pathway_model folder stores the available models written in any language (matlab,octave or python).
  • decision_stage folder stores the available detectors written in any language.
  • Experiment files (either AFC, AMT or your own) can be found in the experiment folder.
  • model_server folder stores the matlab and python functions used to interface experiments, models and detectors (see call graph).
  • data folder stores the results produced on the experiment side.
  • plot routine folder contains a set of function to plot the results store in the data folder.

Quick start

Once the requirements are satisfied, assuming the experiment side is already launched:

For the matlab/octave user

  1. Open a matlab/octave desktop
  2. Navigate to the main folder of the library and run the model_initiative_init_model script
  3. Run the model server matlab function with the right set of arguments. model_server(no_intervals,model_name_and_args,detector_name_and_args, model_language,detector_language) If the model and the detector are both in matlab, there is no need to precise the detector language, just use: model_server(2,'klein_hennig_2011(wave,fs,0.18,0)','argmin(pathway_out)','matlab')

however if the model and the detector are written in different languages use for instance:

model_server(2,'klein_hennig_2011_python(wave,fs,0.18,None)','argmin(pathway_out)','python','matlab') or model_server(2,'klein_hennig_2011(wave,fs,0.18,0)','argmin_python(pathway_out)','matlab','python') or model_server(2,'goodman_brette_2010_python(wave,fs,20,0.05)','argmax_python(pathway_out)','python','python')

For the python2 user

  1. using a command terminal, navigate to the model_server folder
  2. From there run for instance: python -c "from model_server_python import model_server_python; model_server_python(2,'klein_hennig_2011_python(wave,fs,0.18,None)','argmin_python(pathway_out)','python','python')" or python -c "from model_server_python import model_server_python; model_server_python(2,'klein_hennig_2011(wave,fs,0.18,0)','argmin_python(pathway_out)','matlab','python')" or python -c "from model_server_python import model_server_python; model_server_python(2,'goodman_brette_2010_python(wave,fs,20,0.05)','argmax_python(pathway_out)','python','python')"

You can also check the available detectors and models by running the check_available_detectors and check_available_models function located in the model_server folder. Note though that all detectors will not work with all pathway models (see table in appendix)

Features to be aware of

Choice of model and model arguments, detector and detector arguments

Amongst the arguments of the model server function, two of them are of particular importance:

  • model_name_and_args refers to the name of the chosen model and the set of arguments chosen by the user to run the model with. The first argument should always be wave, which refers to the dual channel sound array, the second argument should always be the samplerate fs.

  • detector_name_and_args refers to the name of the chosen detector and the set of arguments chosen by the user to run the detector with. The first argument of the detector function should always be pathway_out.
    pathway_out is the name of the structure that the pathway model output. If the model is in matlab, pathway_out is a cell.

Model language and detector language arguments

When the model_server_python function is used to call the model and detector, the model language and the detector language must be provided as the two last arguments of the function. The different choices the user can pick are : matlab,octave and python. When the model_server (ie the matlab/octave model server) function is used to call the model and detector, only the model language field is mandatory if both model and detector are both run with the same language (matlab or octave). If the model and the detector are written in different languages or if they are both written in python then the detector language should be provided as well.

Call graph



If you would like to contribute to the project by adding experiment, model or detector scripts, please check out the theinterface.pdf document in the model_initiative directory for more technical information on how to do so.


If you have any question regarding the project, or the matlab part of the code, please contact Mathias Dietz at :

For any question regarding the python part, please contact Jean-Hugues Lestang at:


Table of compatible experiments/models/detectors