Abstract
In this paper we consider a category of classification tasks, where the classification results are sentences of words subject to a given grammar. The particular nature of grammar-guided sentence recognition makes classifier combination rules known from the literature not applicable any longer. We propose a conceptually new approach to classifier combination that consists of three main components: class set reduction, inconsistency localization, and resolution. The proposed algorithm represents a framework for classifier combination in grammar-guided sentence recognition that is applicable to a variety of different tasks. Experimental results will be shown for the task of spoken email command recognition, where an acoustic and a visual classifier are combined.
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K. Yu, X. Jiang, and H. Bunke, Combining acoustic and visual classifiers for the recognition of spoken sentences, 2000. (submitted for publication)
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© 2000 Springer-Verlag Berlin Heidelberg
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Jiang, X., Yu, K., Bunke, H. (2000). Classifier Combination for Grammar-Guided Sentence Recognition. In: Multiple Classifier Systems. MCS 2000. Lecture Notes in Computer Science, vol 1857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45014-9_37
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DOI: https://doi.org/10.1007/3-540-45014-9_37
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67704-8
Online ISBN: 978-3-540-45014-6
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