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Challenges of language technologies for the indigenous languages of the Americas

arXiv 1806.04291 ↗First posted 12 Jun 2018cs.CLcited by 29

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Abstract (arXiv)

Indigenous languages of the American continent are highly diverse. However, they have received little attention from the technological perspective. In this paper, we review the research, the digital resources and the available NLP systems that focus on these languages. We present the main challenges and research questions that arise when distant languages and low-resource scenarios are faced. We would like to encourage NLP research in linguistically rich and diverse areas like the Americas.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jun 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 5; 2023: 7; 2024: 4; 2025: 4; 2026: 3.

29 papers.

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  1. 2023NLPositionality: Characterizing Design Biases of Datasets and Modelscited by 91
  2. 2021Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Developmentcited by 85
  3. 2021AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languagescited by 50
  4. 2023Ethical Considerations for Machine Translation of Indigenous Languages: Giving a Voice to the Speakerscited by 26
  5. 2023A Material Lens on Coloniality in NLPcited by 19
  6. 2023A Survey of Corpora for Germanic Low-Resource Languages and Dialectscited by 16
  7. 2022BPE vs. Morphological Segmentation: A Case Study on Machine Translation of Four Polysynthetic Languagescited by 14
  8. 2021IndT5: A Text-to-Text Transformer for 10 Indigenous Languagescited by 10
  9. 2021A Massively Multilingual Analysis of Cross-linguality in Shared Embedding Spacecited by 8
  10. 2023Neural Machine Translation for the Indigenous Languages of the Americas: An Introductioncited by 7
  11. 2023Who Are All The Stochastic Parrots Imitating? They Should Tell Us!cited by 5
  12. 2021On the logistical difficulties and findings of Jopara Sentiment Analysiscited by 4
17 more
  1. 2022Improving Neural Machine Translation of Indigenous Languages with Multilingual Transfer Learningcited by 4
  2. 2023Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-Mixteccited by 4
  3. 2024NLP Progress in Indigenous Latin American Languagescited by 3
  4. 2021Adapting the Tesseract Open-Source OCR Engine for Tamil and Sinhala Legacy Fonts and Creating a Parallel Corpus for Tamil-Sinhala-Englishcited by 2
  5. 2022Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languagescited by 2
  6. 2024The #Somos600M Project: Generating NLP resources that represent the diversity of the languages from LATAM, the Caribbean, and Spaincited by 2
  7. 2025La Leaderboard: A Large Language Model Leaderboard for Spanish Varieties and Languages of Spain and Latin Americacited by 2
  8. 2024Automatic Speech Recognition Advancements for Indigenous Languages of the Americascited by 1
  9. 2024Harnessing the Power of Artificial Intelligence to Vitalize Endangered Indigenous Languages: Technologies and Experiencescited by 1
  10. 2025Comparative Study of Zero-Shot Cross-Lingual Transfer for Bodo POS and NER Tagging Using Gemini 2.0 Flash Thinking Experimental Modelcited by 1
  11. 2022Educational Tools for Mapuzuguncited by 0
  12. 2022Revisiting Syllables in Language Modelling and their Application on Low-Resource Machine Translationcited by 0
  13. 2025Indigenous Languages Spoken in Argentina: A Survey of NLP and Speech Resourcescited by 0
  14. 2025Redefining technology for indigenous languagescited by 0
  15. 2026Meenz bleibt Meenz, but Large Language Models Do Not Speak Its Dialectcited by 0
  16. 2026The Annotation Scarcity Paradox in Low-Resource NLP Evaluation: A Decade of Acceleration and Emerging Constraintscited by 0
  17. 2026Plurification in/of language technology -- The integration of culture in next-generation AIcited by 0