Ning-Ning Mahlmann


Utilizing Automated Translation with Quality Scores to Increase Productivity
Daniel Marcu | Kathleen Egan | Chuck Simmons | Ning-Ning Mahlmann
Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Government MT User Program

Automated translation can assist with a variety of translation needs in government, from speeding up access to information for intelligence work to helping human translators increase their productivity. However, government entities need to have a mechanism in place so that they know whether or not they can trust the output from automated translation solutions. In this presentation, Language Weaver will present a new capability "TrustScore": an automated scoring algorithm that communicates how good the automated translation is, using a meaningful metric. With this capability, each translation is automatically assigned a score from 1 to 5 in the TrustScore. A score of 1 would indicate that the translation is unintelligible; a score of 3 would indicate that meaning has been conveyed and that the translated content is actionable. A score approaching 4 or higher would indicate that meaning and nuance have been carried through. This automatic prediction of quality has been validated by testing done across significant numbers of data points in different companies and on different types of content. After outlining TrustScore, and how it works, Language Weaver will discuss how a scoring mechanism like TrustScore could be used in a translation productivity workflow in government to assist linguists with day to day translation work. This would enable them to further benefit from their investments in automated translation software. Language Weaver would also share how TrustScore is used in commercial deployments to cost effectively publish information in near real time.