Filip Korzeniowski, Gerhard Widmer,
"Improved Chord Recognition by Combining Duration and Harmonic Language Models"
: Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), 2018
Original Titel:
Improved Chord Recognition by Combining Duration and Harmonic Language Models
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR)
Original Kurzfassung:
Chord recognition systems typically comprise an acoustic
model that predicts chords for each audio frame, and a temporal
model that casts these predictions into labelled chord
segments. However, temporal models have been shown to
only smooth predictions, without being able to incorporate
musical information about chord progressions. Recent research
discovered that it might be the low hierarchical level
such models have been applied to (directly on audio frames)
which prevents learning musical relationships, even for expressive
models such as recurrent neural networks (RNNs).
However, if applied on the level of chord sequences, RNNs
indeed can become powerful chord predictors. In this paper,
we disentangle temporal models into a harmonic language
model?to be applied on chord sequences?and a chord
duration model that connects the chord-level predictions of
the language model to the frame-level predictions of the
acoustic model. In our experiments, we explore the impact
of each model on the chord recognition score, and show that
using harmonic language and duration models improves the
results.