music-genre-gtzan-classification

An transformer based audio classification system fine-tuned on distilBERT with Tesla T4 GPU

Music Genre Classifier

An Transformer based audio classification system fine-tuned on distilBERT with Tesla T4 GPU
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Contributing
4. License
5. Contact

About The Project

The Music Genre Classifier is an advanced audio classification system, utilizing a Transformer-based model fine-tuned with distilBERT, powered by a Tesla T4 GPU. This cutting-edge technology automatically assigns music tracks to specific genres, making it invaluable for music streaming platforms, recommendation systems, and music enthusiasts.

Key Features:

Transformer-Based Model: Leveraging the Transformer architecture, renowned for its success in natural language processing, this system adapts it to audio data, effectively capturing music characteristics.
Fine-Tuned distilBERT: The distilBERT model's efficiency and performance are harnessed to understand the intricate features unique to different music genres, enhancing genre prediction accuracy.
Tesla T4 GPU: The Tesla T4 GPU accelerates both training and inference, ensuring rapid processing even with extensive audio datasets.

With seamless data preprocessing, model training, and efficient inference, the system predicts music genres, enhancing music recommendations, playlist creation, and genre-based searches. Enjoy more personalized music experiences with this Music Genre Classifier, offering precision and speed in audio genre classification.

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Built With

• Transformers
• DistilBERT
• Numpy
• gradio
• librosa
• HuggingFace

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Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Prerequisites

To run this project, you need to have python installed on your system. If you don't have python installed, you can install it from here

Installation

1. Clone the repo and cd into the directory

   git clone https://github.com/mahimairaja/music-genre-gtzan-classification.git

   cd music-genre-gtzan-classification

2. Create a virtual environment

   python -m venv venv

3. Activate the virtual environment

   source venv/bin/activate

4. Install the required packages

   pip install -r requirements.txt

5. Run the app

   python app.py

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Mahimai Raja J - @mahimairaja3 - info@mahimairaja.in

Project Link: mahimairaja/music-genre-gtzan-classification

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