1. The document describes a study that uses a Convolutional Neural Network (CNN) model to classify music genres based on labeled Mel spectrograms of audio clips. 2. A CNN model is trained on a dataset of 1000 audio clips across 10 genres. The trained model is then used to classify new, unlabeled audio clips by genre based on their Mel spectrogram representation. 3. CNNs are well-suited for this task as their convolutional layers can extract hierarchical features from the Mel spectrogram images that are indicative of different genres. The study aims to develop an automated music genre classification system using deep learning techniques.