大陆之声：绘制非洲语音技术前沿地图
Voice of a Continent: Mapping Africa's Speech Technology Frontier
AI总结：
本文系统绘制非洲语音数据集与技术空间地图，提出综合基准 SimbaBench 和 Simba 模型家族，在多种非洲语言任务上取得最先进性能，并揭示资源、数据质量与语系关系对性能的影响。
摘要：
非洲丰富的语言多样性在语音技术中仍然显著代表性不足，造成了数字包容的障碍。为缓解这一挑战，我们系统地绘制了该大陆语音数据集与技术空间的地图，从而形成一个新的综合基准 SimbaBench，用于下游非洲语音任务。利用 SimbaBench，我们引入了 Simba 模型家族，在多种非洲语言和语音任务上取得了最先进的性能。我们的基准分析揭示了资源可用性方面的关键模式，而我们的模型评估则展示了数据集质量、领域多样性和语系关系如何影响跨语言性能。我们的工作凸显了扩展语音技术资源以更好地反映非洲语言多样性的必要性，并为未来朝着更具包容性的语音技术开展研究与开发工作提供了坚实基础。
英文摘要：
Africa's rich linguistic diversity remains significantly underrepresented in speech technologies, creating barriers to digital inclusion. To alleviate this challenge, we systematically map the continent's speech space of datasets and technologies, leading to a new comprehensive benchmark SimbaBench for downstream African speech tasks. Using SimbaBench, we introduce the Simba family of models, achieving state-of-the-art performance across multiple African languages and speech tasks. Our benchmark analysis reveals critical patterns in resource availability, while our model evaluation demonstrates how dataset quality, domain diversity, and language family relationships influence performance across languages. Our work highlights the need for expanded speech technology resources that better reflect Africa's linguistic diversity and provides a solid foundation for future research and development efforts toward more inclusive speech technologies.
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。
