No Language Left Behind: Scaling Human-Centered Machine Translation

Understand

Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today.

• However, such efforts have coalesced around a small subset of languages, leaving behind the vast majority of mostly low-resource languages.
• What does it take to break the 200 language barrier while ensuring safe, high quality results, all while keeping ethical considerations in mind? In No Language Left Behind, we took on this challenge by first contextualizing the need for low-resource language translation support through exploratory interviews with native speakers.
• Then, we created datasets and models aimed at narrowing the performance gap between low and high-resource languages.