How I handled ambiguity in a system to read music scores

Alan Ruttenberg

doi:10.1117/12.131527

1 November 1992 How I handled ambiguity in a system to read music scores

Alan Ruttenberg

Proceedings Volume 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision; (1992) https://doi.org/10.1117/12.131527
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

In a program for reading printed music, a variety of low level feature detectors were used to extract sufficient information to reconstruct the score. All feature detectors were unreliable to some extent, and were biased towards yielding false positives rather than missing features. In order to reconstruct the score, conflicting information from the feature detectors needed to be recognized and eliminated. All objects as well as their geometric and semantic relations were represented in an object oriented framework. Ambiguity (implemented as a generic predicate) was defined -- and explicitly represented -- in terms of these relationships. Examples of ambiguous relationships include: An accidental and a note head having an on-top-of geometric relationship, or the total duration of notes in a measure not being equal to the notated time signature. A method inspired by Waltz filtering was used to produce a consistent, unambiguous interpretation. Waltz filtering is a symbolic constraint propagation technique which has been applied to line drawings. During interpretation attention was focused on objects which had ambiguous relations. Ambiguity was iteratively reduced or removed by using a variety of methods employing information gathered from local unambiguous relations.

Citation Download Citation

Alan Ruttenberg "How I handled ambiguity in a system to read music scores", Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); https://doi.org/10.1117/12.131527

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