Music Tradition

Music tradition research focuses on analyzing and modeling diverse musical styles, particularly those underrepresented in existing datasets, to address biases in AI music generation and analysis. Current research employs deep learning models, including convolutional neural networks and transformers, leveraging transfer learning and data augmentation techniques to adapt models trained on dominant genres to less-represented musical traditions. This work is crucial for fostering inclusivity in AI systems and providing valuable insights into the structure and cultural significance of diverse musical practices worldwide. The resulting datasets and models contribute to a more comprehensive understanding of music across cultures and enhance the capabilities of music information retrieval systems.