|
|
|
This paper
addresses the issue of source detection when more sources than mixtures
overlap in time and frequency. We show
that repetitive structure in the form of time-time correlation matrices can
reveal when each source is active. |
|
Related publication: |
|
|
|
|
|
This paper proposes the use of feature weights to reveal
the hierarchical nature of music audio. Feature weighting has been exploited in
machine learning, but has not been applied to music audio segmentation. We
describe both a global and a local approach to automatic feature weighting.
The global approach assigns a single weighting to all features in a song. The
local approach uses the local separability
directly. Both approaches reveal
structure that is obscured by standard features, and emphasize segments of a
particular size. |
|
Related publication: |
|
|
|
|
|
Rhythmic similarity techniques
for audio tend to evaluate how close to identical two rhythms are. This paper
proposes a similarity metric based on rhythmic elaboration that matches rhythms
that share the same beats regardless of tempo or identicalness. Elaborations
can help an application decide where to transition between songs. Potential
applications include automatically generating a non-stop music mix or
sonically browsing a music library. |
|
Related publication: |
