  Speech synthesis for poetry is challenging due to specific intonation
patterns inherent to poetic speech. In this work, we propose an approach to
synthesise poems with almost human like naturalness in order to enable literary
scholars to systematically examine hypotheses on the interplay between text,
spoken realisation, and the listener's perception of poems. To meet these
special requirements for literary studies, we resynthesise poems by cloning
prosodic values from a human reference recitation, and afterwards make use of
fine-grained prosody control to manipulate the synthetic speech in a
human-in-the-loop setting to alter the recitation w.r.t. specific phenomena. We
find that finetuning our TTS model on poetry captures poetic intonation
patterns to a large extent which is beneficial for prosody cloning and
manipulation and verify the success of our approach both in an objective
evaluation as well as in human studies.
