Error Correction Framerwork based on Drum Pattern Periodicity
We propose a framework for
correcting errors of automatic drum sound detection
focusing on the periodicity of drum patterns.
We define drum patterns as periodic structures
found in onset sequences of bass and snare drum sounds.
Our framework extracts periodic drum patterns
from imperfect onset sequences of detected drum sounds (bottom-up processing)
and corrects errors
using the periodicity of the drum patterns (top-down processing).
We implemented this framework
on our drum-sound detection system.
We first obtained onset sequences of the drum sounds
with our system and extracted drum patterns.
On the basis of our observation that the same drum patterns tend to be repeated,
we detected time points which deviate from the periodicity
as error candidates.
Finally, we verified each error candidate
to judge whether it is an actual onset or not.
Experiments of drum sound detection
for polyphonic audio signals of popular CD recordings
showed that our correction framework
improved the average detection accuracy from 77.4% to 80.7%.
Poster (first pase)
Poster (second page)
Kazuyoshi Yoshii, Masataka Goto, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno,
"An Error Correction Framework based on Drum Pattern Periodicity for Improving Drum Sound Detection,"
In Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2006), 5/14-5/19, 2006.
This research was achieved by using
RWC Music Database.
We thank everyone who has made this database.
Author : Kazuyoshi Yoshii (AIST)
mail to k.yoshii(at)aist.go.jp