It’s not an everyday occurrence that translators and technology professionals come together and discuss the state of the language industry, but that’s exactly what happened last month in Santa Clara, CA. The event, The Future of Language Work: Enterprise, Technology, and Translation Professional Perspectives, was hosted by translation startup, Lilt, and featured two panelist discussions on topics ranging from language technology advancements to the effect of globalization on translation demand. While the first panelist discussion focused on the past, present and future of translation technology, the second panelist discussion turned to look at how technology is affecting language work. The panel, moderated by Katie Botkin, Managing Editor of Multilingual Magazine, included panelists David Snider, Globalization Architect at LinkedIn, Anna Schlegel, Sr. Director of Globalization Programs and Information Strategy at NetApp, Jost Zetzsche, Localization Consultant and Writer at the International Writers’ Group and Max Troyer, Assistant Professor and Program Coordinator, Translation & Localization Management at the Monterey Institute of International Studies.
This article describes the technology behind Lilt’s interactive translation suggestions. The details were first published in an academic conference paper, Models and Inference for Prefix-Constrained Machine Translation. Machine translation systems can translate whole sentences or documents, but they can also be used to finish translations that were started by a person — a form of autocomplete at the sentence level. In the computational linguistics literature, predicting the rest of a sentence is called prefix-constrainedmachine translation. The prefix of a sentence is the portion authored by a translator. A suffix is suggested by the machine to complete the translation. These suggestions are proposed interactively to translators after each word they type. Translators can accept all or part of the proposed suffix with a single keystroke, saving time by automating the most predictable parts of the translation process.