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Proceedings Paper

How I handled ambiguity in a system to read music scores
Author(s): Alan Ruttenberg
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Paper 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.

Paper Details

Date Published: 1 November 1992
PDF: 6 pages
Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); doi: 10.1117/12.131527
Show Author Affiliations
Alan Ruttenberg, Media Lab./MIT (United States)


Published in SPIE Proceedings Vol. 1825:
Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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