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.
