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ABSTRACT
This paper proposes a sequential coupling of a Hidden Markov Model (HMM) recognizer for offline handwritten English sentences with a probabilistic bottom-up chart parser using Stochastic Context-Free Grammars (SCFG) extracted from a text corpus. Based on extensive experiments, we conclude that syntax analysis helps to improve recognition rates significantly.
INDEX TERMS
Optical character recognition, handwriting analysis, natural language parsing and understanding.
CITATION
Matthias Zimmermann, Horst Bunke, Jean-C?dric Chappelier, "Offline Grammar-Based Recognition of Handwritten Sentences", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 28, no. , pp. 818-821, May 2006, doi:10.1109/TPAMI.2006.103
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