论文标题
全球医疗保健语言技术的准备:与下一个大流行作斗争需要什么?
Global Readiness of Language Technology for Healthcare: What would it Take to Combat the Next Pandemic?
论文作者
论文摘要
COVID-19的大流行既带来了最好的和最差的语言技术(LT)。一方面,信息传播和基本诊断的对话剂已经广泛使用,并且可以说,在打击大流行方面起着重要作用。另一方面,也很清楚,这些技术很容易用于少数语言,而全球南方的绝大多数人完全丧失了这些好处。在世界语言中,LT的医疗保健状态是什么?而且,要确保LT在下一个大流行之前的全球准备情况需要什么?在本文中,我们尝试通过对现有文献和资源的调查以及15种亚洲和非洲语言的快速聊天机器人建设练习来回答这些问题,并具有不同的资源可用性。这项研究证实了LT的可怜状态,即使对于具有诸如Sinhala和Hausa之类的大型说话者基础的语言,也可以确定可以帮助我们优先考虑LT的Healthcare研究和投资策略的差距。
The COVID-19 pandemic has brought out both the best and worst of language technology (LT). On one hand, conversational agents for information dissemination and basic diagnosis have seen widespread use, and arguably, had an important role in combating the pandemic. On the other hand, it has also become clear that such technologies are readily available for a handful of languages, and the vast majority of the global south is completely bereft of these benefits. What is the state of LT, especially conversational agents, for healthcare across the world's languages? And, what would it take to ensure global readiness of LT before the next pandemic? In this paper, we try to answer these questions through survey of existing literature and resources, as well as through a rapid chatbot building exercise for 15 Asian and African languages with varying amount of resource-availability. The study confirms the pitiful state of LT even for languages with large speaker bases, such as Sinhala and Hausa, and identifies the gaps that could help us prioritize research and investment strategies in LT for healthcare.