# NLP Progress in Indigenous Latin American Languages

arXiv: https://arxiv.org/abs/2404.05365 · HTML: https://mlsanity.com/paper/2404.05365/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 112 references that are in the map.
- First posted on arXiv 8 Apr 2024.

## Builds on (most cited first, 23 of 23)

- [The State and Fate of Linguistic Diversity and Inclusion in the NLP World](https://mlsanity.com/paper/2004.09095/) (2020)
- [Systematic Inequalities in Language Technology Performance across the World's Languages](https://mlsanity.com/paper/2110.06733/) (2021)
- [AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages](https://mlsanity.com/paper/2104.08726/) (2021)
- [Challenges of language technologies for the indigenous languages of the Americas](https://mlsanity.com/paper/1806.04291/) (2018)
- [Ethical Considerations for Machine Translation of Indigenous Languages: Giving a Voice to the Speakers](https://mlsanity.com/paper/2305.19474/) (2023)
- [Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yolox'ochitl Mixtec](https://mlsanity.com/paper/2101.10877/) (2021)
- [BPE vs. Morphological Segmentation: A Case Study on Machine Translation of Four Polysynthetic Languages](https://mlsanity.com/paper/2203.08954/) (2022)
- [Fortification of Neural Morphological Segmentation Models for Polysynthetic Minimal-Resource Languages](https://mlsanity.com/paper/1804.06024/) (2018)
- [Tackling the Low-resource Challenge for Canonical Segmentation](https://mlsanity.com/paper/2010.02804/) (2020)
- [IndT5: A Text-to-Text Transformer for 10 Indigenous Languages](https://mlsanity.com/paper/2104.07483/) (2021)
- [Neural Machine Translation for the Indigenous Languages of the Americas: An Introduction](https://mlsanity.com/paper/2306.06804/) (2023)
- [A Resource for Computational Experiments on Mapudungun](https://mlsanity.com/paper/1912.01772/) (2019)
- [On the logistical difficulties and findings of Jopara Sentiment Analysis](https://mlsanity.com/paper/2105.02947/) (2021)
- [Improving Neural Machine Translation of Indigenous Languages with Multilingual Transfer Learning](https://mlsanity.com/paper/2205.06993/) (2022)
- [Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-Mixtec](https://mlsanity.com/paper/2305.17404/) (2023)
- [Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models](https://mlsanity.com/paper/2305.17406/) (2023)
- [Sheffield's Submission to the AmericasNLP Shared Task on Machine Translation into Indigenous Languages](https://mlsanity.com/paper/2306.09830/) (2023)
- [Robust Generalization Strategies for Morpheme Glossing in an Endangered Language Documentation Context](https://mlsanity.com/paper/2311.02777/) (2023)
- [Lost in Translation: Analysis of Information Loss During Machine Translation Between Polysynthetic and Fusional Languages](https://mlsanity.com/paper/1807.00286/) (2018)
- [Building an Endangered Language Resource in the Classroom: Universal Dependencies for Kakataibo](https://mlsanity.com/paper/2206.10343/) (2022)
- [Comparing morphological complexity of Spanish, Otomi and Nahuatl](https://mlsanity.com/paper/1808.04314/) (2018)
- [Apurin~a Universal Dependencies Treebank](https://mlsanity.com/paper/2106.03391/) (2021)
- [Multilingual unsupervised sequence segmentation transfers to extremely low-resource languages](https://mlsanity.com/paper/2110.08415/) (2021)

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

- [Shortcomings of LLMs for Low-Resource Translation: Retrieval and Understanding are Both the Problem](https://mlsanity.com/paper/2406.15625/) (2024)
- [Indigenous Languages Spoken in Argentina: A Survey of NLP and Speech Resources](https://mlsanity.com/paper/2501.09943/) (2025)
- [Redefining technology for indigenous languages](https://mlsanity.com/paper/2504.01522/) (2025)
- [Towards the Roof of the World: NLP Progress in Tibetan Languages](https://mlsanity.com/paper/2610.13398/) (2026)

## Abstract (arXiv)

The paper focuses on the marginalization of indigenous language communities in the face of rapid technological advancements. We highlight the cultural richness of these languages and the risk they face of being overlooked in the realm of Natural Language Processing (NLP). We aim to bridge the gap between these communities and researchers, emphasizing the need for inclusive technological advancements that respect indigenous community perspectives. We show the NLP progress of indigenous Latin American languages and the survey that covers the status of indigenous languages in Latin America, their representation in NLP, and the challenges and innovations required for their preservation and development. The paper contributes to the current literature in understanding the need and progress of NLP for indigenous communities of Latin America, specifically low-resource and indigenous communities in general.