Abstract
Comparing pitch class distributions with predefined key
profiles has become the preferred method for key-finding
in tonal music, since it was first proposed by Krumhansl
and Schmuckler in 1990 [6].
When determining keys using this strategy, information
about the temporal order of the notes is not taken into
account, although this might contribute additional information
useful for key-finding.
An obvious extension of the pitch class profiles is to
look at distributions of intervals calculate scale degree
transition profiles. This idea has not been given much attention
in previous research. We conduct a data driven
experiment where pitch class profiles and interval profiles
are learned from key-annotated music and evaluated on a
key-finding task.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the International Computer Music Conference (ICMC 2007) , Copenhagen, Denmark. |
| Number of pages | 4 |
| Publication status | Published - 2007 |
Fields of science
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
- 202002 Audiovisual media