End-to-End Musical Key Estimation Using a Convolutional Neural Network

Understand

We present an end-to-end system for musical key estimation, based on a convolutional neural network.

• The proposed system not only out-performs existing key estimation methods proposed in the academic literature; it is also capable of learning a unified model for diverse musical genres that performs comparably to existing systems specialised for specific genres.
• Our experiments confirm that different genres do differ in their interpretation of tonality, and thus a system tuned e.g.
• for pop music performs subpar on pieces of electronic music.