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.

本研究针对低资源语言面临的数据匮乏问题，提出了一个生成语言工具的框架，以支持语言模型的开发，帮助保存这些语言。通过以撒丁语为案例，该框架的有效性得以验证，推动了语言多样性和现代技术在语言标准化与复兴中的应用。

LIMBA：一个开源框架用于低资源语言的保存和增值，采用生成模型