mlsanityData to 14 Oct 2026

Connecting the Persian-speaking World through Transliteration

arXiv 2502.20047 ↗First posted 27 Feb 2025cs.CLcited by 4

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Abstract (arXiv)

Despite speaking mutually intelligible varieties of the same language, speakers of Tajik Persian, written in a modified Cyrillic alphabet, cannot read Iranian and Afghan texts written in the Perso-Arabic script. As the vast majority of Persian text on the Internet is written in Perso-Arabic, monolingual Tajik speakers are unable to interface with the Internet in any meaningful way. Due to overwhelming similarity between the formal registers of these dialects and the scarcity of Tajik-Farsi parallel data, machine transliteration has been proposed as more a practical and appropriate solution than machine translation. This paper presents a transformer-based G2P approach to Tajik-Farsi transliteration, achieving chrF++ scores of 58.70 (Farsi to Tajik) and 74.20 (Tajik to Farsi) on novel digraphic datasets, setting a comparable baseline metric for future work. Our results also demonstrate the non-trivial difficulty of this task in both directions. We also provide an overview of the differences between the two scripts and the challenges they present, so as to aid future efforts in Tajik-Farsi transliteration.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 5 of its 24 references that are in the map. First posted on arXiv 27 Feb 2025.

Builds on

5 of 24 references.

References · 5

  1. 2021Survey of Low-Resource Machine Translationcited by 92
  2. 2020Applying the Transformer to Character-level Transductioncited by 43
  3. 2020Transformer based Grapheme-to-Phoneme Conversioncited by 32
  4. 2018A Rule-based Kurdish Text Transliteration Systemcited by 13
  5. 2020Persian Ezafe Recognition Using Transformers and Its Role in Part-Of-Speech Taggingcited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.