Parsing N-Best Lists of Handwritten Sentences

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Parsing N-Best Lists of Handwritten Sentences
This paper investigates the application of a probabilistic parser for natural language on the list of the Nbest sentences produced by an off-line recognition system for cursive handwritten sentences. For the generation of the N-best sentence list an HMM-based recognizer including a bigram language model is used. The parsing of the sentences is achieved by a bottom-up chart parser for stochastic context-free grammars which produces the parse tree of the input sentence as well as the word tags. From a collection of corpora we extract the linguistic resources to build the lexicon, a word bigram model and the stochastic context-free grammar. Results from experiments indicate an increase of the word and sentence recognition rate when using the proposed combination scheme.
Matthias Zimmermann, Jean-Cédric Chappelier
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Authors Matthias Zimmermann, Jean-Cédric Chappelier, Horst Bunke
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