Billions of people are still unable to easily access most of the information on the internet or connect with most of the online world in their native language. Today’s machine translation (MT) systems are improving rapidly, but they still rely heavily on learning from large amounts of textual data, so they do not generally work well for low-resource languages.
Meta – the parent organization of Facebook, Instagram, and WhatsApp, among other subsidiaries – now wants to break language barriers across the globe using artificial intelligence (AI), making it possible for billions of people to access information online in their native or preferred languages. It has announced an ambitious new AI research project to create translation software that works for “everyone in the world.”
This includes two new projects. The first is No Language Left Behind, where the company is building a new advanced AI model that can learn from languages with fewer examples to train from. The second is Universal Speech Translator, where Meta is designing novel approaches to translating from a speech in one language to another in real-time so we can support languages without a standard writing system as well as those that are both written and spoken.
“The ability to communicate with anyone in any language – that’s a superpower people have dreamed of forever, and AI is going to deliver that within our lifetimes,” CEO of Meta Mark Zuckerberg said in an online presentation.
Meta researchers did not offer a timeframe for completing these projects or even a roadmap for major milestones in reaching their lofty goal. Instead, the company stressed its new innovation would have a significant impact around the world.
“Eliminating language barriers would be profound, making it possible for billions of people to access information online in their native or preferred languages,” said Meta in its blog. “Advances in MT won’t just help those people who don’t speak one of the languages that dominate the internet today; they’ll also fundamentally change the way people in the world connect and share ideas.”
The company is working with linguists to help it understand the challenges of producing accurate data set collections and networks of evaluators to help us make sure that translations are accurate. They are also conducting case studies with speakers of more than 20 languages to understand what translation features are important to people from different backgrounds and how they will be using the translations their AI models produce.