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

arXiv: https://arxiv.org/abs/2109.14934 · HTML: https://mlsanity.com/paper/2109.14934/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 63 references that are in the map.
- First posted on arXiv 30 Sep 2021.

## Builds on (most cited first, 24 of 24)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [ALBERT: A Lite BERT for Self-supervised Learning of Language Representations](https://mlsanity.com/paper/1909.11942/) (2019)
- [Improving Neural Machine Translation Models with Monolingual Data](https://mlsanity.com/paper/1511.06709/) (2015)
- [Distributed Representations of Sentences and Documents](https://mlsanity.com/paper/1405.4053/) (2014)
- [Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation](https://mlsanity.com/paper/1611.04558/) (2016)
- [Transfer Learning for Low-Resource Neural Machine Translation](https://mlsanity.com/paper/1604.02201/) (2016)
- [On Using Monolingual Corpora in Neural Machine Translation](https://mlsanity.com/paper/1503.03535/) (2015)
- [ParsBERT: Transformer-based Model for Persian Language Understanding](https://mlsanity.com/paper/2005.12515/) (2020)
- [Cold Fusion: Training Seq2Seq Models Together with Language Models](https://mlsanity.com/paper/1708.06426/) (2017)
- [Toward Multilingual Neural Machine Translation with Universal Encoder and Decoder](https://mlsanity.com/paper/1611.04798/) (2016)
- [Transfer Learning across Low-Resource, Related Languages for Neural Machine Translation](https://mlsanity.com/paper/1708.09803/) (2017)
- [Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme](https://mlsanity.com/paper/1807.03491/) (2018)
- [Chinese Poetry Generation with Planning based Neural Network](https://mlsanity.com/paper/1610.09889/) (2016)
- [Beyond Narrative Description: Generating Poetry from Images by Multi-Adversarial Training](https://mlsanity.com/paper/1804.08473/) (2018)
- [Don't Go Far Off: An Empirical Study on Neural Poetry Translation](https://mlsanity.com/paper/2109.02972/) (2021)
- [Introducing Aspects of Creativity in Automatic Poetry Generation](https://mlsanity.com/paper/2002.02511/) (2020)
- [Improving Zero-Shot Translation of Low-Resource Languages](https://mlsanity.com/paper/1811.01389/) (2018)
- [Learning Rhyming Constraints using Structured Adversaries](https://mlsanity.com/paper/1909.06743/) (2019)
- [How Images Inspire Poems: Generating Classical Chinese Poetry from Images with Memory Networks](https://mlsanity.com/paper/1803.02994/) (2018)
- [Creating a New Persian Poet Based on Machine Learning](https://mlsanity.com/paper/1810.06898/) (2018)
- [PGST: a Polyglot Gender Style Transfer method](https://mlsanity.com/paper/2009.01040/) (2020)

## Built on by (most cited first, 7 of 7)

- [What is the Best Way for ChatGPT to Translate Poetry?](https://mlsanity.com/paper/2406.03450/) (2024)
- [Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad](https://mlsanity.com/paper/2405.06760/) (2024)
- [An Introduction to Natural Language Processing Techniques and Framework for Clinical Implementation in Radiation Oncology](https://mlsanity.com/paper/2311.02205/) (2023)
- [TPPoet: Transformer-Based Persian Poem Generation using Minimal Data and Advanced Decoding Techniques](https://mlsanity.com/paper/2312.02125/) (2023)
- [Automated Evaluation of Meter and Rhyme in Russian Generative and Human-Authored Poetry](https://mlsanity.com/paper/2502.20931/) (2025)
- [Echoes Across Centuries: Phonetic Signatures of Persian Poets](https://mlsanity.com/paper/2603.14443/) (2026)
- [Translating Classical Poetry into Modern Prose](https://mlsanity.com/paper/2606.02806/) (2026)

## Abstract (arXiv)

Persian Poetry has consistently expressed its philosophy, wisdom, speech, and rationale on the basis of its couplets, making it an enigmatic language on its own to both native and non-native speakers. Nevertheless, the notice able gap between Persian prose and poem has left the two pieces of literature medium-less. Having curated a parallel corpus of prose and their equivalent poems, we introduce a novel Neural Machine Translation (NMT) approach to translate prose to ancient Persian poetry using transformer-based Language Models in an extremely low-resource setting. More specifically, we trained a Transformer model from scratch to obtain initial translations and pretrained different variations of BERT to obtain final translations. To address the challenge of using masked language modelling under poeticness criteria, we heuristically joined the two models and generated valid poems in terms of automatic and human assessments. Final results demonstrate the eligibility and creativity of our novel heuristically aided approach among Literature professionals and non-professionals in generating novel Persian poems.