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Python port of Lyon's model from AuditoryToolbox

Project description

Lyon's auditory model for Python

Python port of Lyon's model calculation from Auditory Toolbox. Original version of Auditory Toolbox is written in C and MATLAB by Malcolm Slaney.

Package contents

  • Modified soscascade.c, agc.c and sosfilters.c (removed MEX-related part).
  • ctypes wrapper for soscascade(), agc() and sosfilters() calls.
  • Translation from MATLAB to Python for files necessary for successfull call to LyonPassiveEar().


If you plan to build manually and run tests, you'll need libcheck installed. On Ubuntu 18.10 run:

sudo apt-get install check



Build a library:

make lib

This would result in shared library. Verify that library is properly built by running a test suite:

make test


The following code computes cochleogram for a sample sound:

from lyon import LyonCalc

calc = LyonCalc()
waveform, sample_rate = load('audio/file/path.wav')
decimation_factor = 64
coch = calc.lyon_passive_ear(waveform, sample_rate, decimation_factor)

The code above should output shape of resulting auditory nerve response: [<number of samples / decimation_factor>, 86].

See for examples on running other functions.


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Filename, size & hash SHA256 hash help File type Python version Upload date
lyon-1.0.0-py3-none-any.whl (12.9 kB) Copy SHA256 hash SHA256 Wheel py3
lyon-1.0.0.tar.gz (9.3 kB) Copy SHA256 hash SHA256 Source None

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