Key detection in electronic dance music is important for producers and DJ’s who want to mix their tracks harmonically or organise their music collection by tonal content. In this paper, we present an algorithm that improves the performance of an existing method by introducing a system of multiple profiles, addressing difficult minor tracks as well as possibly amodal ones. After the explanation of our method, we use three independent datasets of electronic dance music to evaluate its performance, comparing it to other academic algorithms and commercially available solutions.

Comunicació presentada a: 2017 AES International Conference on Semantic Audio, celebrada del 22 al 24 de juny de 2017 a Erlangen, Alemanya.

This research has been partially supported the EUfunded GiantSteps project (FP7-ICT-2013-10 grant agreement number 610591).