弥合自然语言处理在约鲁巴语中的差距：对十年进展与前景的系统综述
Bridging Gaps in Natural Language Processing for Yorùbá: A Systematic Review of a Decade of Progress and Prospects
AI总结：
本文通过系统综述分析了近十年约鲁巴语NLP的发展，揭示了资源匮乏、声调复杂性等挑战，并总结了基于规则等主要技术，旨在推动该语言在NLP中的应用进展。
摘要：
自然语言处理（NLP）正成为人工智能的一个主导子领域，因为帮助机器理解人类语言的需求显得必不可少。几种NLP应用无处不在，部分原因在于通过社交媒体等媒介每天都会产生大量的数据集。然而，发展速度在大多数非洲语言中并未显现，这主要是由于持续存在的资源限制等其他问题。约鲁巴语，一种具有声调和形态丰富的非洲语言，也面临同样的命运，导致NLP应用有限。为了鼓励进一步的研究以改善这一状况，本系统文献综述旨在全面分析针对约鲁巴语NLP发展的研究，识别挑战、资源、技术和应用。从一个结构化的协议中制定的明确搜索字符串被用来在可靠的数据库中搜索、选择和分析2014年至2024年间105项主要研究。综述突显了标注语料库的稀缺性、预训练语言模型的有限可用性以及语言学挑战如声调复杂性和声调依赖性作为重要障碍。它还揭示了主要技术，包括基于规则的方法等。研究结果表明，尽管该领域受到社会文化因素如代码切换和语言数字化弃用的限制，但多语言和单语言资源的总量正在增长。本综述整合了现有研究，为推进约鲁巴语及其他非洲语言的NLP发展奠定了基础。它旨在通过识别差距和机会来指导未来研究，从而促进约鲁巴语和其他资源匮乏的非洲语言在NLP进步中的更大包容性。
英文摘要：
Natural Language Processing (NLP) is becoming a dominant subset of artificial intelligence as the need to help machines understand human language looks indispensable. Several NLP applications are ubiquitous, partly due to the myriad of datasets being churned out daily through mediums like social networking sites. However, the growing development has not been evident in most African languages due to the persisting resource limitations, among other issues. Yorùbá language, a tonal and morphologically rich African language, suffers a similar fate, resulting in limited NLP usage. To encourage further research towards improving this situation, this systematic literature review aims to comprehensively analyse studies addressing NLP development for Yorùbá, identifying challenges, resources, techniques, and applications. A well-defined search string from a structured protocol was employed to search, select, and analyse 105 primary studies between 2014 and 2024 from reputable databases. The review highlights the scarcity of annotated corpora, the limited availability of pre-trained language models, and linguistic challenges like tonal complexity and diacritic dependency as significant obstacles. It also revealed the prominent techniques, including rule-based methods, among others. The findings reveal a growing body of multilingual and monolingual resources, even though the field is constrained by socio-cultural factors such as code-switching and the desertion of language for digital usage. This review synthesises existing research, providing a foundation for advancing NLP for Yorùbá and in African languages generally. It aims to guide future research by identifying gaps and opportunities, thereby contributing to the broader inclusion of Yorùbá and other under-resourced African languages in global NLP advancements.
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。
