pyAudioProcessing

A Python based library for processing audio data into features and building Machine Learning models.

Getting Started

Clone the project and get it setup

git clone git@github.com:jsingh811/pyAudioProcessing.git
pip install -e .

Get the requirements by running

pip install -r requirements/requirements.txt

Choices

Feature options :
You can choose between mfcc, gfcc or gfcc,mfcc features to extract from your audio files.
Classifier options :
You can choose between svm, svm_rbf, randomforest, logisticregression, knn, gradientboosting and extratrees.

Examples

Command line example of using gfcc feature and svm classifier.

Training:

python pyAudioProcessing/run_classification.py -f "data_samples/training" -clf "svm" -clfname "svm_clf" -t "train" -feats "gfcc"

Classifying:

python pyAudioProcessing/run_classification.py -f "data_samples/testing" -clf "svm" -clfname "svm_clf" -t "classify" -feats "gfcc"

Code example of using gfcc feature and svm classifier.

from pyAudioProcessing.run_classification import train_and_classify
# Training
train_and_classify("data_samples/training", "train", ["gfcc"], "svm", "svm_clf")
# Classify data
train_and_classify("data_samples/testing", "classify", ["gfcc"], "svm", "svm_clf")

Author

Jyotika Singh
Data Scientist
https://twitter.com/jyotikasingh_/ https://www.linkedin.com/in/jyotikasingh/