自然语言处理在塞内加尔语言社会科学研究中的机遇与挑战
Opportunities and Challenges of Natural Language Processing for Low-Resource Senegalese Languages in Social Science Research
AI总结：
本文探讨了自然语言处理在塞内加尔六种语言社会科学研究中的机遇与挑战，提出构建可持续的NLP生态系统，强调伦理治理与跨学科合作。
摘要：
自然语言处理（NLP）正迅速改变各学科的研究方法，但非洲语言在这一技术变革中仍被边缘化。本文首次全面概述了NLP在塞内加尔宪法所承认的六种国家语言（沃尔夫语、普拉尔语、塞拉语、朱拉语、曼丁克语和索宁克语）上的进展与挑战。我们综合了语言学、社会技术以及基础设施因素，分析了这些语言的数字准备情况，并识别了数据、工具和基准方面的差距。基于现有倡议和研究成果，我们分析了文本标准化、机器翻译和语音处理等持续努力。我们还提供了一个集中化的GitHub仓库，汇总了这些语言在各种NLP任务上的公开资源，旨在促进协作和可重复性。特别关注NLP在社会科学中的应用，其中多语言转录、翻译和检索流程可以显著提高实地研究的效率和包容性。本文最后提出了一个可持续、以社区为中心的NLP生态系统路线图，强调了伦理数据治理、开放资源和跨学科合作。
英文摘要：
Natural Language Processing (NLP) is rapidly transforming research methodologies across disciplines, yet African languages remain largely underrepresented in this technological shift. This paper provides the first comprehensive overview of NLP progress and challenges for the six national languages officially recognized by the Senegalese Constitution: Wolof, Pulaar, Sérère, Diola, Mandingue, and Soninké. We synthesize linguistic, socio-technical, and infrastructural factors that shape their digital readiness and identify gaps in data, tools, and benchmarks. Building on existing initiatives and research works, we analyze ongoing efforts in various tasks, covering both text and speech modalities. We also provide a centralized GitHub repository that compiles publicly accessible resources for a range of NLP tasks across these languages, designed to facilitate collaboration and reproducibility. A special focus is devoted to the application of NLP to the social sciences, where multilingual transcription, translation, and retrieval pipelines can significantly enhance the efficiency and inclusiveness of field research. The paper concludes by outlining a roadmap toward sustainable, community-centered NLP ecosystems for Senegalese languages, emphasizing ethical data governance, open resources, and interdisciplinary collaboration.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
