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Alignment between Text Images and their Transcripts for Handwritten Documents.. Language Technology for Cultural Heritage. Springer,. 2011. Theory and Applications of Natural Language Processing, pp. 23-37. Caroline Sporleder, Antal van den Bosch y Kalliopi Zervanou (Eds.)An alignment method based on the Viterbi algorithm is proposed to find mappings between word images of a given handwritten document and their respec- tive (ASCII) words on its transcription. The approach takes advantage of the un- derlying segmentation made by Viterbi decoding in handwritten text recognition based on Hidden Markov Models (HMMs). Two levels of alignments are consid- ered: the traditional one at word level and the one at text-line level where pages are transcribed without line break synchronization. According to various metrics used to measure the quality of the alignments, satisfactory results are obtained. Further- more, the presented alignment approach is tested on two HMMs modelling schemes: one using 78 HMMs (one HMM per character class) and other using two HMMs (for blank space and no-blank characters respectively).