Language-Level Syntactic and Semantic Constraints Applied to Visual Word Recognition

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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