During a health crisis such as the ongoing pandemic, authorities need to reach as many people as possible with vital news, and communities want information in their own language. Translation is an important part of this global communication; however, there may be a lack of human resources or time to handle rapidly changing information. Machine translations can help.
In a recent article in Wired, Gretchen McCulloch argued that linguistic competence is important in times of Covid-19, which she referred to as history’s biggest translation challenge. She highlighted the massive task at hand, when immediate translations are needed on a global scale. “But in a pandemic, the challenge isn’t just translating one or a handful of primary languages in a single region — it’s on a scale of perhaps thousands of languages, at least 1,000 to 2,000 of the 7,000-plus languages that exist in the world today.”
They’re unlikely to replace translations by humans, but machine translations certainly can handle high volumes of data and provide translations into a large number of languages in a short space of time. For instance, in the US, some 350 languages are spoken and a fast response is crucial for public service announcements and other urgent communications. However, as stated by Gretchen, “both human and machine language expertise needs to be invested in during calmer times so that it can be used effectively in a crisis.”
New developments for Covid-19
No doubt, machine translations can be invaluable, and there are a number of new developments. Translators Without Borders (TWB) is taking part in a project known as the Translation Initiative for Covid-19 (TICO-19), providing machine-readable translation data related to the pandemic in as many languages as possible, including low-resource languages. Together with academic, language service, and industry partners such as Google, Facebook and Microsoft, TWB is preparing materials to be used by professional translators and for training machine translation models, which can be deployed quickly for future crises.
Last year, with the support from Cisco, TWB kicked off another machine translation project, called Gamayun, aimed to help people who speak minority languages. The initiative uses advanced technology to improve two-way communication in marginalised languages. The Cisco Foundation’s Erin Connor said in a press release: “We believe that TWB’s Gamayun initiative presents an exciting opportunity to apply machine learning translation technology to marginalized languages, ultimately enabling better communication and humanitarian services to crisis-affected communities.”
Catching up with the new reality
Google’s machine translation is also helping to disseminate Covid-19 information. In an article published in July, Michal Lahav, User Experience Researcher at Google Research, stressed the importance of available tools for language access during the health crisis. “In the context of a global pandemic, government and health officials urgently need to deliver vital information to their communities, and every member of the community needs access to information in a language they understand.”
To aid an effective Covid-19 response, Google Translator’s widget Website Translator has now been reopened with free access for governments, non-profit and non-commercial institutions to reach more users around the world. It translates web content into more than 100 languages, using the latest machine translation technology. Users can also enable the translation functionality in their browser or use an online tool such as Google Translate, which now supports a number of file formats including .doc and .pdf so that users can upload a document and get a translated version in their preferred language.
In addition to providing support through the TICO-19 project, Facebook has launched a global version of its Community Help hub for people to request or offer help during the pandemic, now available in a dozen languages with more to be added. Streaming platforms such as Amazon Prime Video are pulling their weight too, localising content and taking part in machine translation research, and a team at Netflix is exploring how to improve machine translation quality for low-resource languages.