Audio Classification using Wavelet Transform and Deep Learning

A step-by-step tutorial to classify audio signals using continuous wavelet transform (CWT) as features.

• Steps to use this repository:

  • Create a virtual environment by using the command: virtualenv venv
  • Activate the environment: source venv/bin/activate
  • Install the requirements.txt file by typing: pip install -r requirements.txt
  • Extract the recordings.zip file

• Files Description

  • recordings.zip: The contains recordings from the Free Spoken Digit Dataset (FSDD). You can also find this data here.
  • training_raw_audio.npz: We are only classifying 3 speakers here: george, jackson, and lucas. All the training data from these 3 speakers is in this numpy zip file.
  • testing_raw_audio.npz: We are only classifying 3 speakers here: george, jackson, and lucas. All the testing data from these 3 speakers is in this numpy zip file.
  • requirements.txt: It contains the required libraries.

classification_report