- Google (with 0.5131), ISI, IBM, UMD, JHU, and Edinburgh in the Arabic-to-English Large Data Track
- Google (with 0.5137), SAKHR, and ARL in the Arabic-to-English Unlimited Data Track
- Google (with 0.3531), ISI, UMD, RWTH, JHU and IBM in the Chinese-to-English Large Data Track
- Google (with 0.3516), ICT, and HIT in the Chinese-to-English Unlimited Data Track
Two of my grad students, Tejaswi Pydimarri (pnvtejaswi) and Waleed Al-Jandal, are at the NIST annual Machine Translation evaluation workshop. This is our first attendance at an MT or computational linguistics meeting, so we're mainly there to learn. Teja has a short presentation on our first (nominally) functioning end-to-end translation system, but we did it primarily to get our feet wet. This being our first BLEU score ever, I have strong hopes for the coming year. My goal is to "make the scoreboard" in earnest by October (with a 0.1 on the Chinese track) and get as close as we can to 0.2 by year's end. If you're interested in keeping tabs on our progress, look for my posts in comptranslation.
I can't believe they've been at the workshop a day now and are almost coming home! Time zips by.