e2f, Lilt & GetYourGuide to speak at LocWorld32
The staff here at e2f are looking forward to meeting you at LocWorld32, which will be held this 26-28 October 2016, in Montreal, Quebec. We’ll be at Stand 22 in the exhibit hall.
As well, e2f’s CEO, Michel Lopez, will be speaking along with Lilt’s CEO, Spence Green, and GetYourGuide’s Anne-Cécile Tomlinson, about our case study for the use of autoadaptive translation technology for large-scale localization projects. Here’s the abstract:
Using Auto-adaptive Machine Learning for GetYourGuide — a Case Study
Machine Translation (MT) systems are traditionally criticized for poor quality output. Yet combining Machine Translation with auto-adaptive Machine Learning (ML) enables a new paradigm of “machine assistance.” Such systems learn from the experience, intelligence and insights of human users, improving productivity by working in partnership, making suggestions and improving accuracy over time.
e2f CEO Michel Lopez, Lilt CEO Spence Green, and GetYourGuide head of Content Operations Anne-Cécile Tomlinson will share their experience empowering e2f’s human translators using Lilt’s technology in an application of machine assistance for a project requiring translation of over one million words in less than two weeks, resulting in a critical customer success.
Date & Time: Friday, October 28, 2016, 2:15pm – 3:15pm
Location: Room 4
Read the Case Study
The discussion will drill down into the technical and operational details on how to successfully deliver such a technically-advanced large-scale project in such a short time. In preparation for attending the talk, you can read the case study we released in June which gives an overview of the methods and results.
Of course, if you really want to learn how these new methods in machine learning, machine translation, and machine assistance are changing the world of translation, feel free to drop us a line! Email us at projects@e2f.com, and we can share with you how these exciting new techniques and advances can help you translate your own content.