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- ![ ] ( media/logo.png )
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+ ![ ] ( https://github.com/SuperKogito/spafe/blob/master/ media/logo.png?raw=true )
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# Spafe
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Simplified Python Audio Features Extraction
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[ ![ Build Status] ( https://github.com/SuperKogito/spafe/actions/workflows/ci.yml/badge.svg )] ( https://github.com/SuperKogito/spafe/actions )
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- [ ![ docs.rs] ( https://img.shields.io/docsrs/docs )] ( https://superkogito.github.io/spafe/dev/ )
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+ [ ![ docs.rs] ( https://img.shields.io/docsrs/docs )] ( https://superkogito.github.io/spafe/ )
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[ ![ License] ( https://img.shields.io/badge/license-BSD%203--Clause%20License%20(Revised)%20-blue )] ( https://github.com/SuperKogito/spafe/blob/master/LICENSE )
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[ ![ Python] ( https://img.shields.io/badge/python-3.5%20%7C%203.6%20%7C%203.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-blue )] ( https://www.python.org/doc/versions/ )
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[ ![ codecov] ( https://codecov.io/gh/SuperKogito/spafe/branch/master/graph/badge.svg )] ( https://codecov.io/gh/SuperKogito/spafe )
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spafe aims to simplify features extractions from ** mono audio** files.
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Spafe includes various computations related to filter banks, spectrograms, frequencies and cepstral features .
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The library has the following structure:
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- ![ ] ( media/spafe-structure.png )
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+ ![ ] ( https://github.com/SuperKogito/spafe/raw/master/ media/spafe-structure.png)
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## Filter banks
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- ![ ] ( media/bark_fbanks.png )
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+ ![ ] ( https://github.com/SuperKogito/spafe/blob/master/ media/bark_fbanks.png?raw=true )
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- Bark filter banks
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- Gammatone filter banks
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- Linear filter banks
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- Mel filter banks
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## Spectrograms
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- ![ ] ( media/melspectrogram.png )
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+ ![ ] ( https://github.com/SuperKogito/spafe/blob/master/ media/melspectrogram.png?raw=true )
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- Bark spectrogram
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- CQT spectrogram
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- Erb spectrogram
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- Mel spectrogram
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## Features
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- ![ ] ( media/gfcc.png )
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+ ![ ] ( https://github.com/SuperKogito/spafe/blob/master/ media/gfcc.png?raw=true )
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- Bark Frequency Cepstral Coefficients (BFCCs)
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- Constant Q-transform Cepstral Coefficients (CQCCs)
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- Gammatone Frequency Cepstral Coefficients (GFCCs)
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- Rasta Perceptual Linear Prediction Coefficents (RPLPs)
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The theory behind features computed using spafe can be summmarized in the following graph:
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- ![ ] ( media/features-extraction-algorithms.png )
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+ ![ ] ( https://github.com/SuperKogito/spafe/blob/master/ media/features-extraction-algorithms.png?raw=true )
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## Frequencies
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- ![ ] ( media/dominant_frequencies.png )
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+ ![ ] ( https://github.com/SuperKogito/spafe/blob/master/ media/dominant_frequencies.png?raw=true )
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- Dominant frequencies
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- Fundamental frequencies
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@@ -116,7 +116,7 @@ python setup.py install
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## How to use
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- Various examples on how to use spafe are present in the documentation [ https://superkogito.github.io/spafe/dev/ ] ( https://superkogito.github.io/spafe/dev/ ) .
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+ Various examples on how to use spafe are present in the documentation [ https://superkogito.github.io/spafe/dev/ ] ( https://superkogito.github.io/spafe ) .
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** <!>** Please make sure you are referring to the correct documentation version.
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