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Persian Poetry has consistently expressed its philosophy, wisdom, speech, andrationale on the basis of its couplets, making it an enigmatic language on itsown to both native and non-native speakers. Nevertheless, the notice able gapbetween Persian prose and poem has left the two pieces of literaturemedium-less. Having curated a parallel corpus of prose and their equivalentpoems, we introduce a novel Neural Machine Translation (NMT) approach totranslate prose to ancient Persian poetry using transformer-based LanguageModels in an extremely low-resource setting. More specifically, we trained aTransformer model from scratch to obtain initial translations and pretraineddifferent variations of BERT to obtain final translations. To address thechallenge of using masked language modelling under poeticness criteria, weheuristically joined the two models and generated valid poems in terms ofautomatic and human assessments. Final results demonstrate the eligibility andcreativity of our novel heuristically aided approach among Literatureprofessionals and non-professionals in generating novel Persian poems.

Prose2Poem: The Blessing of Transformers in Translating Prose to Persian Poetry