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Digital Objez Ide tifie (DOI) 10.1007/s10032-003-0113-0 IJDAR (2003) 6:126--144 Lexicon-dr en HMM decodingfor lar vocabular handwr- randwrwith multiple char
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In: http://www.ppgia.pucpr.br/~alekoe/pt/./Papers/Koerich-IJDAR2003.pdf (2003)
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Lexicon-Driven HMM Decoding for Large Vocabulary Handwriting Recognition with Multiple Character Models
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In: http://www.ppgia.pucpr.br/~alekoe/Port/./Papers/Koerich_IJDAR_2003.pdf (2003)
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Abstract:
This paper present a handwriting recognition system that deals with unconstrained handwriting and large vocabularies. The system is based on the segmentation-recognition paradigm where words are first loosely segmented into characters or pseudocharacters and the final segmentation is obtained during the recognition process, which is carried out with a lexicon. Characters are modeled by multiple hidden Markov models (HMMs), which are concatenated to build up word models. The lexicon is organized as a tree structure, and during the decoding words with similar prefixes share the same computation steps. To avoid an explosion of the search space due to the presence of multiple character models, a lexicon-driven level building algoritm (LDLBA) is used to decode the lexical tree and to choose at each level the more likely models. Bigram probabilities related to the variation of writing styles witin the words are inserted between the levels of the LDLBA to improve the recognition accuracy. To further speed up the recognition process, some constraints are added to limit the search efforts to the more likely part of the search space. Experimental result on a dataset of 4674 unconstrained words show that the proposed recognition system achieves recognition rates from 98% for a 10-word vocabulary to 71% for a 30,000-word vocabulary and recognition times from 9 ms to 18.4 s, respectively.
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Keyword:
Handwriting recognition – Large vocabulary – Level building algorithm – Hidden Markov models – Searc
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.9150
http://www.ppgia.pucpr.br/~alekoe/Port/./Papers/Koerich_IJDAR_2003.pdf
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Lexicon-Driven HMM Decoding for Large Vocabulary Handwriting Recognition with Multiple Character Models
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In: http://www.livia.etsmtl.ca/publications/2003/ijdar_Koerich2003.pdf (2003)
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