# Lost in Translation: Analysis of Information Loss During Machine Translation Between Polysynthetic and Fusional Languages

arXiv: https://arxiv.org/abs/1807.00286 · HTML: https://mlsanity.com/paper/1807.00286/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jul 2018.

## Built on by (most cited first, 3 of 3)

- [Neural Machine Translation for the Indigenous Languages of the Americas: An Introduction](https://mlsanity.com/paper/2306.06804/) (2023)
- [Improving Neural Machine Translation of Indigenous Languages with Multilingual Transfer Learning](https://mlsanity.com/paper/2205.06993/) (2022)
- [NLP Progress in Indigenous Latin American Languages](https://mlsanity.com/paper/2404.05365/) (2024)

## Abstract (arXiv)

Machine translation from polysynthetic to fusional languages is a challenging task, which gets further complicated by the limited amount of parallel text available. Thus, translation performance is far from the state of the art for high-resource and more intensively studied language pairs. To shed light on the phenomena which hamper automatic translation to and from polysynthetic languages, we study translations from three low-resource, polysynthetic languages (Nahuatl, Wixarika and Yorem Nokki) into Spanish and vice versa. Doing so, we find that in a morpheme-to-morpheme alignment an important amount of information contained in polysynthetic morphemes has no Spanish counterpart, and its translation is often omitted. We further conduct a qualitative analysis and, thus, identify morpheme types that are commonly hard to align or ignored in the translation process.