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LIMBA: An Open-Source Framework for the Preservation and Valorization of Low-Resource Languages using Generative Models

arXiv 2411.13453 ↗First posted 20 Nov 2024cs.CL cs.AIcited by 0

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Abstract (arXiv)

Minority languages are vital to preserving cultural heritage, yet they face growing risks of extinction due to limited digital resources and the dominance of artificial intelligence models trained on high-resource languages. This white paper proposes a framework to generate linguistic tools for low-resource languages, focusing on data creation to support the development of language models that can aid in preservation efforts. Sardinian, an endangered language, serves as the case study to demonstrate the framework's effectiveness. By addressing the data scarcity that hinders intelligent applications for such languages, we contribute to promoting linguistic diversity and support ongoing efforts in language standardization and revitalization through modern technologies.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 21 of its 64 references that are in the map. First posted on arXiv 20 Nov 2024.

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21 of 64 references.

References · 21

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
  2. 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,384
  3. 2023Data Selection for Language Models via Importance Resamplingcited by 329
  4. 2016Transfer Learning for Low-Resource Neural Machine Translationcited by 188
  5. 2020Metrics for Multi-Class Classification: an Overviewcited by 143
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  7. 2024LLMs Are Few-Shot In-Context Low-Resource Language Learnerscited by 68
  8. 2024Fine-tuning Large Language Models for Domain-specific Machine Translationcited by 43
  9. 2020Language Model Prior for Low-Resource Neural Machine Translationcited by 37
  10. 2019End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learningcited by 30
  11. 2019Analyzing ASR pretraining for low-resource speech-to-text translationcited by 27
  12. 2024adaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgroundscited by 14
9 more
  1. 2018Low-Resource Speech-to-Text Translationcited by 12
  2. 2017Model Transfer for Tagging Low-resource Languages using a Bilingual Dictionarycited by 10
  3. 2016Cross-Lingual Morphological Tagging for Low-Resource Languagescited by 9
  4. 2016Learning when to trust distant supervision: An application to low-resource POS tagging using cross-lingual projectioncited by 8
  5. 2019A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languagescited by 7
  6. 2024Introducing Syllable Tokenization for Low-resource Languages: A Case Study with Swahilicited by 4
  7. 2024Building pre-train LLM Dataset for the INDIC Languages: a case study on Hindicited by 4
  8. 2020Practical Comparable Data Collection for Low-Resource Languages via Imagescited by 3
  9. 2020An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translationcited by 3

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