Music Genre Classification Using Convolutional Neural Network | Python IEEE Final Year Project

Music Genre Classification Using Convolutional Neural Network | Python IEEE Final Year Project 2024.
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🔬Our Proposed Project Title: Enhanced Music Genre Classification Using Artificial Neural Networks.
💡Implementation Code: PYTHON.
🔬Algorithm / Model Used: Artificial Neural Networks Model (ANN Model).
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.5000/.

📘Project Abstract:
Music genres play a vital role in organizing and understanding music based on shared characteristics and traditions. The ability to accurately classify music genres not only enhances the overall music experience but also enables better evaluation of artistic innovation and quality.
In this project, we present an enhanced music genre classification system utilizing an Artificial Neural Networks Model (ANN Model). To accomplish this, we collected a comprehensive and properly classified music dataset, such as the widely-used GTZAN Music Genre dataset. By extracting spectral representations of the music data, we generated feature maps which were then utilized for training the ANN Model. The model exhibited impressive performance with a training accuracy of 97% and a validation accuracy of 89%, highlighting its effectiveness in accurately classifying music genres.

📌IEEE Base Paper Title: Music Genre Classification Using Convolutional Neural Network.

📌REFERENCE:
Nitin Choudhury; Deepjyoti Deka; Satyajit Sarmah; Parismita Sarma, “Music Genre Classification Using Convolutional Neural Network”, 2023 4th International Conference on Computing and Communication Systems (I3CS), IEEE Conference, 2023.

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