构建首个阿萨姆语开源数据集仓库，助力低资源语言NLP发展
Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset Repository
- 整合多任务数据集，支持情感分析、命名实体识别等下游任务
- 提供预训练与微调语料，推动阿萨姆语机器翻译与大模型研究
- 面向研究者与开发者，尤其适合低资源语言技术探索者
本文提出一个集中式开源数据集仓库，旨在推动阿萨姆语自然语言处理与神经机器翻译的发展。该仓库托管于GitHub，涵盖情感分析、命名实体识别、机器翻译等多种任务的语料，既支持预训练也支持微调。文章综述了现有阿萨姆语数据集，强调标准化资源的迫切需求，并探讨其在大语言模型、光学字符识别和聊天机器人等人工智能应用中的潜力。尽管前景广阔，仍面临数据稀缺与语言多样性等挑战。该仓库致力于促进学术协作与技术创新，推动阿萨姆语在数字时代的学术研究。
原文摘要 · Abstract (English)
This paper introduces a centralized, open-source dataset repository designed to advance NLP and NMT for Assamese, a low-resource language. The repository, available at GitHub, supports various tasks like sentiment analysis, named entity recognition, and machine translation by providing both pre-training and fine-tuning corpora. We review existing datasets, highlighting the need for standardized resources in Assamese NLP, and discuss potential applications in AI-driven research, such as LLMs, OCR, and chatbots. While promising, challenges like data scarcity and linguistic diversity remain. The repository aims to foster collaboration and innovation, promoting Assamese language research in the digital age.
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