On musical score recognition using probabilistic reasoning

TitleOn musical score recognition using probabilistic reasoning
Publication TypeConference Papers
Year of Publication1999
AuthorsStuckelberg MV, Doermann D
Conference NameDocument Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on
Date Published1999/09//
Keywordsanalysis;document, attribute, class;document, descriptive, document, engine;local, estimation;musical, grammar;attribute, grammars;character, handling;, image, interpretation;stochastic, Markov, mechanisms;music;uncertainty, model;global, modeling, models;inference, parameter, processing;image, propagation;explicit, reasoning;scanned, recognition;document, recognition;end-to-end, recognition;inference, recognition;probabilistic, score, structure;hidden, Uncertainty

We present a probabilistic framework for document analysis and recognition and illustrate it on the problem of musical score recognition. Our system uses an explicit descriptive model of the document class to find the most likely interpretation of a scanned document image. In contrast to the traditional pipeline architecture, we carry out all stages of the analysis with a single inference engine, allowing for an end-to-end propagation of the uncertainty. The global modeling structure is similar to a stochastic attribute grammar, and local parameters are estimated using hidden Markov models