An app for gender classification that utilizes machine learning mainly Support Vector Machine (SVM) to distinguish between male and female voices using MFCC-based feature extraction.
A simple audio classification model that identifies the speaker's gender by primarily extracting Mel-frequency cepstral coefficients (MFCC) features. It uses traditional machine learning algorithms Support Vector Machines (SVM). A simple interface was created to test the model.This mini project was part of the Digital Signal Processing course to practice the course content.
- Fast audio classification.
- Accurate gender detection of speaker.
- Simple interface to allow users to test the model.
- you must install ffmpeg first before running the project for audio processing here is a link on how to install https://phoenixnap.com/kb/ffmpeg-windows
- Clone the repository to your local machine:
git clone https://github.com/mohammedshady/audio-gender-classification.git - Navigate to the repo directory:
cd audio-gender-classification - Install the required dependencies in the requriements.txt:
pip install -r requirements.txt - Start the Flask server:
python server.py
- Navigate to the client directory:
cd front-end - Install the required dependencies:
npm install - Start the React development server:
npm run dev - Access the application in your web browser at
http://localhost:5173.
- Mohammed Shady - GitHub Profile: mohammedshady | Email: mohatech777@gmail.com
If you encounter any issues or have suggestions for improvements, please reach out via email. Your feedback is valuable and helps us enhance the app for everyone.