Filip Korzeniowski, David Sears, Gerhard Widmer,
"A Large-Scale Study of Language Models for Chord Prediction"
: In Proceedings of the 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018
A Large-Scale Study of Language Models for Chord Prediction
Sprache des Titels:
In Proceedings of the 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
We conduct a large-scale study of language models for chord prediction.
Specifically, we compare N-gram models to various flavours
of recurrent neural networks on a comprehensive dataset comprising
all publicly available datasets of annotated chords known to us.
This large amount of data allows us to systematically explore hyperparameter
settings for the recurrent neural networks?a crucial step
in achieving good results with this model class. Our results show
not only a quantitative difference between the models, but also a
qualitative one: in contrast to static N-gram models, certain RNN
configurations adapt to the songs at test time. This finding constitutes
a further step towards the development of chord recognition
systems that are more aware of local musical context than what was