2006:Score Following Proposal
Contents
Proposers
- Arshia Cont (University of California in San Diego (UCSD) and Ircam - Realtime Applications Team, France) - cont@ircam.fr
- Diemo Schwarz (Ircam - Realtime Applications Team, France) - schwarz@ircam.fr
Title
Score Following
Description
Score Following is the real-time alignment of incoming music signal to the music score. The music signal can be symbolic (Midi Score Following) or Audio.
This page describes a proposal for evaluation of score following systems. Discussion of the evaluation procedures on the MIREX 06 "ScoreFollowing06" contest planning list will be documented on the Score Following page. A full digest of the discussions is available to subscribers from the MIREX 06 "ScoreFollowing06" contest planning list archives.
Submissions will be required to estimate alignment precision according to the indexed times, type of alignment (monophonic, polyphonic), type of training and realtime performance, also separated into two domains (upon enough submissions) for symbolic and audio systems.
Status
Evaluation procedures
Input data
Each system will need an Audio input as well as a Score to follow (or align).
File formats
Score used for this year's MIREX would be MIDI files. Audio format would be standard WAV or AIFF, as performances of the given MIDI score.
Output data
File formats
ASCII output for each score following system as described below.
Content
The result files represent the alignment found by a score following system between a MIDI score and a recording of a performance of it. They have one line per detected note with the columns:
- estimated note onset time in performance audio file (ms)
- detection time relative to performance audio file (ms)
- note start time in score (ms)
- MIDI note number in score (int)
Suggested calling formats for submitted algorithms
Evaluation metrics
Evaluator pseudo-code
Test collections
Potential Participants
- Arshia Cont (UCSD / Ircam)
- Roger Dannenberg (Carnegie Mellon University)
- Christopher Raphael (Indiana university)
- Diemo Schwarz (Ircam)
- Miller Puckette (UCSD)
- Ozgur Izmirli (Connolle)
- Cort Lippe (University of Buffalo)
- Frank Weinstock (TimeWarp Technologies)
