OpenKiwi: An Open Source Framework for Quality Estimation

A year ago we told you why Quality Estimation is the missing piece in Machine Translation. Today, we have some exciting news to share about a new project from our AI Research team, with my colleagues Fábio Kepler, Sony Trénous, and Miguel Vera. Since 2016, Unbabel's AI team has been focused on advancing the state of the art in Quality Estimation (QE). Our models are running in production systems for 14 language pairs, with coverage and performance improving over time, thanks to the increasing amount of data produced by our human post-editors on a daily basis. This combination of AI and humans is what makes our translation pipeline fast and accurate, at scale.