Informed Selection of Frames for Music Similarity Computation.
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
12th International Conference on Digital Audio Effects (DAFx-09)
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
In this paper we present a new method to compute frame based audio
similarities, based on nearest neighbour density estimation. We
do not recommend it is as a practical method for large collections
because of the high runtime. Rather, we use this new method for
a detailed analysis to get a deeper insight on how a bag of frames
approach (BOF) determines similarities among songs, and in particular,
to identify those audio frames that make two songs similar
from a machine’s point of view. Our analysis reveals that audio
frames of very low energy, which are of course not the most salient
with respect to human perception, have a surprisingly big influence
on current similarity measures. Based on this observation we propose
to remove these low-energy frames before computing song
models and show, via classification experiments, that the proposed
frame selection strategy improves the audio similarity measure.
Forschungs-