Do I need to download and install Lilt?
No. Lilt is cloud-based software, so you need only login with your browser. Because it runs remotely, you probably want to know....
Is my data secure?
Yes. Communication between your computer and our database is encrypted. The data itself (e.g., source documents, translations, translation memories) are encrypted in our database.
Is my data shared with other users or third parties?
No. Your data is used to train personalized machine translation systems. Neither your data nor the trained systems are shared with or accessible by anyone other than you. We do not send your data to Google Translate, Microsoft Translator, or any other third-party service.
Do I need training to use Lilt?
No. When you register, a quick interactive tutorial will teach you the basics. The User Guide contains more advanced instructions. But it's short. Our design goal is for you to learn the system in five minutes or less.
I forgot my password!
You can request a password reset link on the login page. Click the "Forgot your password?" link on the bottom, enter your email address, and click on "Request password reset". An email with instructions including a password reset link for your account will be sent to you. If you don't receive the email within the next minutes, please check your spam folder.
Can I import my data to and from SDL Trados?
Yes. The User Guide shows you how to export and import via SDLXLIFF, SDLTM, and SDLPPX (i.e., SDL packages). Standard interchange formats such as XLIFF 1.2 and TMX are also supported.
Can I download my trained Memories / MT systems?
No. But you can always download the data (as TMX) from your Memories.
Do you use Google Translate or Microsoft Translator?
No. We develop and train our own machine translation systems. The open-source decoder we use is called Phrasal, which is distributed by the Stanford University NLP Group. We actively contribute to Phrasal. Our Lexicon/concordance service is also open source and is developed in conjunction with the UC Berkeley Oscii Lab. You can find it on Github.