Filip Korzeniowski, Gerhard Widmer,
"Genre-Agnostic Key Classification With Convolutional Neural Networks"
: Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), 2018
Genre-Agnostic Key Classification With Convolutional Neural Networks
Sprache des Titels:
Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR)
We propose modifications to the model structure and training
procedure to a recently introduced Convolutional Neural
Network for musical key classification. These modifications
enable the network to learn a genre-independent
model that performs better than models trained for specific
music styles, which has not been the case in existing work.
We analyse this generalisation capability on three datasets
comprising distinct genres. We then evaluate the model
on a number of unseen data sets, and show its superior
performance compared to the state of the art. Finally, we
investigate the model?s performance on short excerpts of
audio. From these experiments, we conclude that models
need to consider the harmonic coherence of the whole piece
when classifying the local key of short segments of audio.