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The paper pairs a nationwide survey of emergency managers with an evaluation of commercial machine translation tools for crisis alerts. Its main value for AI readers is the operational view: where these tools are useful, where their quality is unknown, and the conditions under which they can be used safely. Readers building or deploying translation systems in high-stakes settings should find its guidance on evaluation and limits most relevant.
Communicating with the Entire Population: Machine Translation of Emergency Alerts and Warnings
arXiv:2610.32842v1 Announce Type: new Abstract: It is essential that we communicate with the entirety of an affected population during a crisis, including those who do not speak a region's dominant language(s). Commercial Translation tools offer a tempting solution to broaden access and can provide a lifeline when no other resources are available. However, Emergency response managers often operate in the dark regarding the quality and adequacy of these automated outputs. In this paper, we conduct a nationwide survey of emergency managers to understand their current workflows, perspectives, and operational challenges. We then evaluate commercial translation tools against these needs, shedding light on their utility and offering practical guidance on how and when these tools can be safely used in emergency response.
Abstract:It is essential that we communicate with the entirety of an affected population during a crisis, including those who do not speak a region's dominant language(s). Commercial Translation tools offer a tempting solution to broaden access and can provide a lifeline when no other resources are available. However, Emergency response managers often operate in the dark regarding the quality and adequacy of these automated outputs. In this paper, we conduct a nationwide survey of emergency managers to understand their current workflows, perspectives, and operational challenges. We then evaluate commercial translation tools against these needs, shedding light on their utility and offering practical guidance on how and when these tools can be safely used in emergency response.
In Proceedings of the Language Technologies for Crisis Preparedness and Response (LT4CPR Workshop), Hengqin, Zhuhai, China. Association for Computational Linguistics. Nov 2026
Computation and Language (cs.CL)
arXiv:2610.32842 [cs.CL]
(or arXiv:2610.32842v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2610.32842 arXiv-issued DOI via DataCite (pending registration)
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