/Audio-Event-Detection

Primary LanguageJupyter Notebook

Audio Event Detection

Team-39

Submitted By

  • Ashtik Mahapatra
  • Manish Mishra
  • Md. Azharuddin
  • Sekhar Das
  • Soumya Ranjan Naik

Order of Execution

  1. data pickler.ipynb
  2. final model.ipynb
  3. demo.ipynb

file contents

data pickler.ipynb:

Contains the code to convert audio files into mfcc and store them in a pickled file.

final model.ipynb

Trains the model then saves it for future use and also evaluates it for overfitting.

demo.ipynb

Contains the code to implement it in a real time audio detection model.