Instrument Identification in Optical Music Recognition

We present a method for recognizing and interpreting the text labels for the instruments in an orchestra score, thereby associating staves with instruments. This task is one of many necessary in optical music recognition. Our approach treats the score system as the basic unit of processing. A graph structure describes the possible orderings of instruments in the system. Each instrument may apply to several staves, may be represented with several possible text strings, and may appear at several possible positions relative to the staves. We find the optimal labeling of staves using a globally optimal dynamic programming approach that embeds simple template-based optical character recognition within the overall recognition scheme. When given an entire score, we simultaneously optimize on the text labeling for each system, as well as the character template models, thus adapting to the font at hand. Our implementation alternately optimizes over the text label identification and re-estimates the character templates. Experiments are presented on 10 different scores showing a significant improvement due to adaptation.