Classifying audio using Wavelet transform and deep learning

Last update: Nov 29, 2022

Overview

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

Owner

Aditya Dutt

ML PhD Researcher

GitHub Repository

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