From the user’s perspective, that kind of advice could be very useful. Do you know if anyone has done any research on mixing machine translation with human translation?

Again another fascinating blog. I was particularly interested in this comment of yours: “Nevertheless, in the minds of many people, these new translation tools and advances allow them to ‘translate’ their texts quickly and for free. It’s a strong enough offer to demand our professional attention.”;

True! In fact the whole idebate about free translator engines has led to some research at the Universitat Autonoma of Barcelona (where I work) to start a ranking. Universities are ranked so why not FTEs? Below are the top ten according to ourselves at the Faculty of Translation and Interpreting at UAB. The ranking is based on a score for a text which is machine translated by each of the FTEs four categories fidelity (4 points), accuracy (4 points), style (2 points) and ease of use (+,-), making a total of 10 points. However, these categories have been hotly debated – I wonder whether other readers, bloggers would agree with the way of marking a text. It is the one that three or four of us have agreed on at the FTI but it is not necessarily the best way of doing it?!
Our article in the making starts like this:

Despite the fact that there are many free translation engines on the market, there are no league tables or ´ranking `systems as far as we know. There is increasing user acceptance by the general public of machine translation (MT) for ´gist`. For example Smith ([1] 2001) cites evidence of Transparent Language, which runs a on-line free translation service of receiving 2,000 translation requests in typical one-hour period. Eight years later, the website (www.freetranslation.com) is still going strong with two million visits a week. There is also a huge range of free translator engines such as: Babelfish, Translator Online, Foreign Word, Web Trance, Prompt, Verbalis, Google, Systran and Intertran.
As the interest in and demand for free translations, from translator engines such as Google, increases, we believe a league table or ranking system of this multitude of engines will be useful to the user to decide which one suits him or her. We provides a clear description of the criteria used to judge the quality Although rankings provoke fierce criticism ([2] Dill and Soo, 2005), they are completely credible at mainstream public opinion and higher education policy levels ([3] Marginson, 2007).

RANKING OF WORLD FREE TRANSLATOR ENGINES
(SPANISH TO ENGLISH)

WORLD RANK ENGINE NTIs Logo Ease of Use
1 Google 8.0 *****
2 Dictionary.Com 8.0 ****
3 Babylon5.0
4 BabelFish4.0 *****
5 Systrans4.0 ****
6 Bing4.0 ***
7 Worldlingo4.0 **
8 SDL3.0 *****
9 PROMT3.0 ****
10 Reverso2.5
11 Foreign Word0.0

Cheers Matthew!

(Dr) Steve Hampshire