Abstract
The paper describes a new method that permits a computer
to listen to, and follow, live music in real-time, by analysing
the incoming audio stream and aligning it to a symbolic representation
(e.g, score) of the piece(s) being played. In particular, we
present a multi-level music matching and tracking algorithm that,
by continually updating and evaluating multiple high-level hypotheses,
effectively deals with almost arbitrary deviations of the live performer
from the score omissions, forward and backward jumps,
unexpected repetitions, or (re-)starts in the middle of the piece. Also,
we show that additional knowledge about the structure of the piece
(which can be automatically computed by the system) can be used
to further improve the robustness of the tracking process. The resulting
system is discussed in the context of an automatic page-turning
device for musicians, but it will be of use in a much wider class of
scenarios that require reactive and adaptive musical companions.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Starting AI Reserachrs´ Symposium (STAIRS 2010) |
| Number of pages | 6 |
| Publication status | Published - 2010 |
Fields of science
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
- 202002 Audiovisual media