Abstract
Various aspects of using language-level syntactic and semantic constraints to improve the performance of word recognition algorithms are discussed. Following a brief presentation of a hypothesis generation model for handwritten word recognition, various types of language-level constraints are reviewed. Methods that exploit these characteristics are discussed including intra-document word correlation, common vocabularies, part-of-speech tag cooccurrence, structural parsing with a chart data structure, and semantic biasing with a thesaurus.
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© 1994 Springer-Verlag Berlin Heidelberg
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Hull, J.J. (1994). Language-Level Syntactic and Semantic Constraints Applied to Visual Word Recognition. In: Impedovo, S. (eds) Fundamentals in Handwriting Recognition. NATO ASI Series, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-78646-4_16
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DOI: https://doi.org/10.1007/978-3-642-78646-4_16
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