Music Transcription Model

Overview

This repository contains a simple Convolutional Neural Network (CNN) model that is designed to identify 37 different guitar notes individually.

Features

• Guitar Note Recognition: The model is capable of identifying 37 distinct guitar notes, enabling accurate transcription of guitar music.
• Simplicity: The model is kept simple for ease of understanding and modification, making it suitable for beginner developers.

Getting Started

1. Clone the Repository:

   git clone https://github.com/lomash-relia/music-transcription.git
   

2. Install Dependencies:

   pip3 install torch torchaudio torchsummary scikit-learn
   

3. Run the Model:

   python inference.py
   

Model Training

If you wish to train the model with your own dataset, follow these steps:

1. Prepare Dataset: Organize your guitar note dataset with labeled examples for each of the 37 notes.

2. Configure Training Settings: Adjust the hyperparameters and training settings in the train.py file according to your dataset and preferences.

3. Train the Model:

   python train.py
   

   This will initiate the training process.

Contribution Guidelines

Contributions are welcome! If you have suggestions, enhancements, or bug fixes, please follow these guidelines:

• Fork the repository.
• Create a new branch for your changes.
• Make your changes and test thoroughly.
• Create a pull request, explaining the changes made and providing any necessary context.

Feel free to explore, use, and contribute to enhance the functionality of this music transcription model. Happy coding!