Is MT Ready for the Next Crisis or Pandemic?
This work addresses the problem of communication barriers in crises for affected communities, but it is incremental as it assesses existing tools without proposing new solutions.
The study evaluated four commercial machine translation systems on the TICO-19 dataset of pandemic-related sentences in high-priority languages, finding that their effectiveness for low-resource languages in crisis or medical domains is limited, with usability issues in output translations.
Communication in times of crisis is essential. However, there is often a mismatch between the language of governments, aid providers, doctors, and those to whom they are providing aid. Commercial MT systems are reasonable tools to turn to in these scenarios. But how effective are these tools for translating to and from low resource languages, particularly in the crisis or medical domain? In this study, we evaluate four commercial MT systems using the TICO-19 dataset, which is composed of pandemic-related sentences from a large set of high priority languages spoken by communities most likely to be affected adversely in the next pandemic. We then assess the current degree of ``readiness'' for another pandemic (or epidemic) based on the usability of the output translations.