I recently received a t-shirt from Glyph Languages Services that I have to share:
The ampersand is composed of translations of the word “and” into 150 languages — from Afrakaans to Zulu. Very impressive.
Okay, now this is my last post of 2011. And I mean it this time.
Join me next week (February 24th at 9 am Eastern) for a free webinar hosted by Lionbridge.
I’ll be sharing what I’ve learned over the years as both a provider and buyer of language services.
If you’re new to the language industry, you may find yourself confused by the terminology and overwhelmed by the myriad choices in services. If so, you’re certainly not alone. I’ll demystify the terminology and will also cover:
And for more information on finding a language services vendor, check out my book The Savvy Client’s Guide to Translation Agencies.
UPDATE: The webinar has been recorded and is available at: http://bit.ly/gwxz42
Lior Libman of One Hour Translation has released a web tool that you can use to quickly determine if text was translated by one of the three major machine translation (MT) engines: Google Translate, Yahoo! Babel Fish, and Bing Translate.
It’s called the Translation Detector.
To use it, you input your source text and target text and then it tells you the probability of each of the three MT engines being the culprit.
How does it know this? Simple. Behind the scenes it takes the source text and runs it through the three MT engines and then compares the output to your target text. So the caveat here is that this tool only compares against those three MT engines.
Being the geek that I am, I couldn’t help but give it a test drive.
It correctly guessed between text translated by Google Translate vs. Bing Translate (I didn’t try Yahoo!). Below is a screen shot of what I found after inputing the Google Translate text:
Next, I input source and target text that I had copied from the Apple web site (US and Germany). I would be shocked if the folks at Apple were crunching their source text through Google Translate.
And, sure enough, here’s what the Translation Detector spit out:
So if you suspect your translator is taking shortcuts with Google Translate or another engine, this might be just the tool to test that theory.
Though in defense of translators everywhere, I’ve never heard of anyone resorting to an MT engine to cut corners.
I actually see this tool as part of something bigger — the emergence of third-party tools and vendors that evaluate, benchmark, and optimize machine translation engines. Right now, these three engines are black boxes. I wrote awhile back of one person’s efforts to compare the quality of these three engines. But there are lots of opportunities here. As more people use these engines there will be a greater need for more intelligence about which engine works best for what types of text. And hopefully we’ll see vendors arise that leverage these MT engines for industry-specific functions.
UPDATE: As the commenters noted below, there are limits to the quality of results you will get if you input more than roughly 130 words. The tool is limited by API word-length caps.
The TAUS Data Association (TDA) was founded about two years ago with the goal of creating a widely used and trusted platform for companies to share their translation memories. The idea was that companies could achieve greater cost savings and greater quality if they worked together and reciprocally shared their previous translated text strings. For companies within a given industry, the cost savings can quickly add up.
I received their update newsletter this week. After 18 months in operation, TDA reports:
Between the APIs and the more affordable membership fees, TAUS appears to be making the right moves to not only expand its membership but expand the reach of its platform. With the major translation vendors (and Google) offering proprietary platforms, it’s nice to see an independent alternative. But more important, it’s nice to see companies sharing. It wasn’t very long ago that the idea of sharing TMs was considered on par with divulging corporate secrets. But sharing of TMs and the building up of large-scale databases of translated strings will provide the foundation for some really innovative (and hopefully accessible) products and services, should TAUS wish to pursue them. It will be interesting to see what develops…
Link: TAUS Data Association
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