Ethan Shen, a Chinese translator, used for years, while studying in high school and college, a variety of free MT translation engines. A question remained unsolved for him, however: which MT translation system is best?
To finally settle the question, Shen has devised a comparative study, and is looking for volunteers. Shen has set up a web site in which you can paste or input text to translate. The survey site feeds the source text to three diferent free MT systems (Google Translate, Yahoo/Babelfish and Microsoft Bing's). You are then asked to review the resulting translations, rate them, and add your comments.
Shen is looking for 10,000 testers between now and the end of March, for any of the language pairs supported by these machine translations systems.He will then analyze the results, and I believe he plans to publish the results of his research, or write about them.
If you would like to participate, you can do so by following the link to Which Engine Translates Best? March Madness Edition.
As an enticement to participate in the survey, Shen's company will award a new Apple iPad to a participant in the March Madness contest (you can find the details on Shen's survey site).
Ha, I can answer that straight away, it's Google, without a shadow of a doubt, at least in my pair and in most fields. But I'd be interested to see how this experiment is approached - how you quantify a "good" translation, how you take into account the infinite range of registers and subject areas etc...
ReplyDeleteHi Mark,
ReplyDeleteAs far as I understand Shen's survey relies exclusively on the subjective evaluations of the responders: each responder inputs some text, ranks the resulting translations and may add comments about the results.
I haven't tried the test myself yet; I may blog about the results I get, once i do.