  We provide a syllabification algorithm for the Divine Comedy using techniques
from probabilistic and constraint programming. We particularly focus on the
synalephe, addressed in terms of the "propensity" of a word to take part in a
synalephe with adjacent words. We jointly provide an online vocabulary
containing, for each word, information about its syllabification, the location
of the tonic accent, and the aforementioned synalephe propensity, on the left
and right sides. The algorithm is intrinsically nondeterministic, producing
different possible syllabifications for each verse, with different likelihoods;
metric constraints relative to accents on the 10th, 4th and 6th syllables are
used to further reduce the solution space. The most likely syllabification is
hence returned as output. We believe that this work could be a major milestone
for a lot of different investigations. From the point of view of digital
humanities it opens new perspectives on computer assisted analysis of digital
sources, comprising automated detection of anomalous and problematic cases,
metric clustering of verses and their categorization, or more foundational
investigations addressing e.g. the phonetic roles of consonants and vowels.
From the point of view of text processing and deep learning, information about
syllabification and the location of accents opens a wide range of exciting
perspectives, from the possibility of automatic learning syllabification of
words and verses, to the improvement of generative models, aware of metric
issues, and more respectful of the expected musicality.
