Google Translate App for iPhone: Will it hit number 1? (Answer: Yes!)

I’m a little amazed by all the press that the Google Translate app for iPhone is getting today.

From The Wall Street Journal to the LA Times, this app is getting noticed.

And this app doesn’t even include the “Conversation Mode” feature that is currently included in Google Translate for Android app. It will be interesting to see how quickly Conversation Mode makes it into the iPhone given Google’s escalating mobile battle with Apple.

I checked the iTunes store a moment ago to see that the app is ranked at #16 in the Free category. Not bad!

Now, can it beat the mighty Sky Burger app for the number one spot?

I think it can.

PS: The Google Translate app supports 30 or so languages, which means its one of the most-localized apps on the iPhone (if not THE most localized).

UPDATE: One day later and, yes, the Sky Burger app has been unseated by Google Translate!

Think your translator is cutting corners? Try the machine translation detector…

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.

Previewing the 2011 Web Globalization Report Card

I’ve begun work on the 7th edition of the Report Card. To produce this report I individually review more than 200 global web sites across more than 20 industries. Needless to say, I’ve got a busy month ahead!

I’ve already done a first pass on a number of web sites and have some initial thoughts to share:

  • As regular readers know, Google and Facebook finished in a dead heat for first place last year, with Google having a slight advantage. Both companies made significant changes over the past twelve months, changes that promise to make this another photo finish.
  • I’ve noticed an increase in the number of sites using geolocation for navigation. Unfortunately, some of these sites are not using geolocation as well as they should. As I’ve noted in my book, geolocation should never be used without a visual global gateway in place. Geolocation is an excellent tool, but it presents a number of edge cases that only a global gateway can solve.
  • I’ve seen some amazing global gateways so far, and, in some cases, demonstrating vast improvements over previous global gateways. I’ll be documenting a number of these gateways in the report.
  • Companies continue to add languages. After initial analysis, Indonesian is hot, as is Russian and Turkish. Last year, the average number of languages was 20. I suspect we’ll see increase again this year. Keep in mind that this is just the average. Companies like Cisco, Apple, and DHL are well above 20 languages.
  • For last year’s report, I began measuring “community localization” — the integration of social networking platforms into local web sites. I wasn’t just looking at Twitter and Facebook use around the world, but at how companies are fostering communities. I’ve noticed quite a lot of Facebook integration around the world. Below is a home page visual from Samsung Italy:
  • Samsung also promotes its Twitter feed on the home page of its Brazil site. And Samsung is far from alone.
  • Finally, I’m noticing lots and lots of web site surveys.They’re popping up everywhere and in many languages. Somebody please make them stop!

Here is the link to the 2010 Report Card. All companies included in this report will be included in 2011. We’ll have a page for the 2011 report up shortly.