Multi-label Music Genre Classification from Audio, Text, and Images Using Deep Features

Understand

Music genres allow to categorize musical items that share common characteristics.

• Although these categories are not mutually exclusive, most related research is traditionally focused on classifying tracks into a single class.
• Furthermore, these categories (e.g., Pop, Rock) tend to be too broad for certain applications.
• In this work we aim to expand this task by categorizing musical items into multiple and fine-grained labels, using three different data modalities: audio, text, and images.