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    <titleInfo>
        <title>Global Readiness of Language Technology for Healthcare: What Would It Take to Combat the Next Pandemic?</title>
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    <name type="personal">
        <namePart type="given">Ishani</namePart>
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    <name type="personal">
        <namePart type="given">Mohit</namePart>
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    <name type="personal">
        <namePart type="given">Jacki</namePart>
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    <name type="personal">
        <namePart type="given">Kalika</namePart>
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    <abstract>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 fighting against 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.</abstract>
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%0 Conference Proceedings
%T Global Readiness of Language Technology for Healthcare: What Would It Take to Combat the Next Pandemic?
%A Mondal, Ishani
%A Ahuja, Kabir
%A Jain, Mohit
%A O’Neill, Jacki
%A Bali, Kalika
%A Choudhury, Monojit
%S Proceedings of the 29th International Conference on Computational Linguistics
%D 2022
%8 October
%I International Committee on Computational Linguistics
%C Gyeongju, Republic of Korea
%F mondal-etal-2022-global
%X 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 fighting against 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.
%U https://aclanthology.org/2022.coling-1.381
%P 4320-4335

Markdown (Informal)

[Global Readiness of Language Technology for Healthcare: What Would It Take to Combat the Next Pandemic?](https://aclanthology.org/2022.coling-1.381) (Mondal et al., COLING 2022)

• Global Readiness of Language Technology for Healthcare: What Would It Take to Combat the Next Pandemic? (Mondal et al., COLING 2022)

ACL

• Ishani Mondal, Kabir Ahuja, Mohit Jain, Jacki O’Neill, Kalika Bali, and Monojit Choudhury. 2022. Global Readiness of Language Technology for Healthcare: What Would It Take to Combat the Next Pandemic?. In Proceedings of the 29th International Conference on Computational Linguistics, pages 4320–4335, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.