Abstract
This paper shows how the nowadays prevalent technology used in HTR borrows concepts and methods from the field of ASR; i.e. those based on Hidden Markov Models (HMMs). Additionally, it will be described a HTR approach based on employing Bernoulli distributions rather than Gaussian-Mixture distributions for the HMM-state emission probability of observations. Finally, handwritten text recognition evaluation results are reported for several corpora involving different characteristics and languages.
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Toselli, A.H., Serrano, N., Giménez-Pastor, A., Khoury, I., Juan, A., Vidal, E. (2012). Language Technology for Handwritten Text Recognition. In: Torre Toledano, D., et al. Advances in Speech and Language Technologies for Iberian Languages. Communications in Computer and Information Science, vol 328. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35292-8_19
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DOI: https://doi.org/10.1007/978-3-642-35292-8_19
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