# Orthographic Syllable as basic unit for SMT between Related Languages

arXiv: https://arxiv.org/abs/1610.00634 · HTML: https://mlsanity.com/paper/1610.00634/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Oct 2016.

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

- [Evaluating Various Tokenizers for Arabic Text Classification](https://mlsanity.com/paper/2106.07540/) (2021)
- [Alternative Input Signals Ease Transfer in Multilingual Machine Translation](https://mlsanity.com/paper/2110.07804/) (2021)
- [Unicode Normalization and Grapheme Parsing of Indic Languages](https://mlsanity.com/paper/2306.01743/) (2023)
- [LCP-dropout: Compression-based Multiple Subword Segmentation for Neural Machine Translation](https://mlsanity.com/paper/2202.13590/) (2022)
- [Revisiting Syllables in Language Modelling and their Application on Low-Resource Machine Translation](https://mlsanity.com/paper/2210.02509/) (2022)
- [IndicQE-APE: A Consolidated Benchmark for Quality Estimation and Automatic Post-Editing for Indic Languages](https://mlsanity.com/paper/2608.16344/) (2026)
- [Type-Driven Tokenization for Brahmic Scripts](https://mlsanity.com/paper/2609.22125/) (2026)

## Abstract (arXiv)

We explore the use of the orthographic syllable, a variable-length consonant-vowel sequence, as a basic unit of translation between related languages which use abugida or alphabetic scripts. We show that orthographic syllable level translation significantly outperforms models trained over other basic units (word, morpheme and character) when training over small parallel corpora.