  Although abbreviations are fairly common in handwritten sources, particularly
in medieval and modern Western manuscripts, previous research dealing with
computational approaches to their expansion is scarce. Yet abbreviations
present particular challenges to computational approaches such as handwritten
text recognition and natural language processing tasks. Often, pre-processing
ultimately aims to lead from a digitised image of the source to a normalised
text, which includes expansion of the abbreviations. We explore different
setups to obtain such a normalised text, either directly, by training HTR
engines on normalised (i.e., expanded, disabbreviated) text, or by decomposing
the process into discrete steps, each making use of specialist models for
recognition, word segmentation and normalisation. The case studies considered
here are drawn from the medieval Latin tradition.
