# Are Mutually Intelligible Languages Easier to Translate?

arXiv: https://arxiv.org/abs/2201.13072 · HTML: https://mlsanity.com/paper/2201.13072/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 7 references that are in the map.
- First posted on arXiv 31 Jan 2022.

## Builds on (most cited first, 3 of 3)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://mlsanity.com/paper/1904.01038/) (2019)

## Abstract (arXiv)

Two languages are considered mutually intelligible if their native speakers can communicate with each other, while using their own mother tongue. How does the fact that humans perceive a language pair as mutually intelligible affect the ability to learn a translation model between them? We hypothesize that the amount of data needed to train a neural ma-chine translation model is anti-proportional to the languages' mutual intelligibility. Experiments on the Romance language group reveal that there is indeed strong correlation between the area under a model's learning curve and mutual intelligibility scores obtained by studying human speakers.