📃: Music Genre Classification Model

Avdhesh-Varshney / AI-Code

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🔴 Title : Music Genre Classification Model 🔴 Aim : Develop a model to classify songs into different genres based on audio features. 🔴 Brief Explanation :

Link of the dataset Perfoming EDA Attach any blog for reading related to the topic Explain the features properly Add necessary comments for the code understanding Attach your notebook links Applying atleast 3-4 models and compairing them. NOTE: Follow this readme template

Screenshots 📷 ✅ To be Mentioned while taking the issue :

Full name : What is your participant role? (Mention the Open Source Program name. Eg. GSOC, GSSOC, SSOC, JWOC, etc.) Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

Full name : Filbert Shawn What is your participant role? SSOC' 24 Data Collection: I will use datasets like the GTZAN genre dataset, which contains audio files of various genres. Link - GTZAN Dataset Feature Extraction: Use a library like librosa to extract audio features such as

Mel-frequency cepstral coefficients (MFCC)

Chromagram

Spectral contrast

Tonnetz

Zero-crossing rate,

Tempo

Data Preprocessing: Normalize the features and handle missing values. Ensure the dataset is balanced. Model Selection: Starting with a simple model like a Decision Tree, and then move to more complex models like Random Forest, Support Vector Machine (SVM), or Neural Networks. Training and Evaluation: Split the data into training and testing sets. Using metrics like accuracy, precision, recall, and F1-score for evaluation.

Avdhesh-Varshney / AI-Code

📃: Music Genre Classification Model #52