# Joint Persian Word Segmentation Correction and Zero-Width Non-Joiner Recognition Using BERT

arXiv: https://arxiv.org/abs/2010.00287 · HTML: https://mlsanity.com/paper/2010.00287/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2020.

## Built on by (most cited first, 4 of 4)

- [Evaluating Persian Tokenizers](https://mlsanity.com/paper/2202.10879/) (2022)
- [Script Normalization for Unconventional Writing of Under-Resourced Languages in Bilingual Communities](https://mlsanity.com/paper/2305.16407/) (2023)
- [ViraPart: A Text Refinement Framework for Automatic Speech Recognition and Natural Language Processing Tasks in Persian](https://mlsanity.com/paper/2110.09086/) (2021)
- [Filling the Gap for Uzbek: Creating Translation Resources for Southern Uzbek](https://mlsanity.com/paper/2508.14586/) (2025)

## Abstract (arXiv)

Words are properly segmented in the Persian writing system; in practice, however, these writing rules are often neglected, resulting in single words being written disjointedly and multiple words written without any white spaces between them. This paper addresses the problems of word segmentation and zero-width non-joiner (ZWNJ) recognition in Persian, which we approach jointly as a sequence labeling problem. We achieved a macro-averaged F1-score of 92.40% on a carefully collected corpus of 500 sentences with a high level of difficulty.