Let’s face it, we’ve all at one time or another needed a little guidance through Google’s search engine. First, you may ask a question. Maybe the question is answered, maybe not. In reality, there is a list of cheats to make Google search engine easier, cutting down on more than half of the results you find. Continue reading Cheat Sheet on Google’s Search Engine
Did you know that Google has a blog dedicated to Google Translate?
In a recent post this month on the Google Translate Blog it was announced that a Google online community had been created. The online community is meant for translators and interpreters, if they so choose, by volunteering to refine the Google Translate Services.
Free Translation Software has become somewhat of a joke for anyone who needs something translated, but with an active step in improving the software Google’s Translating Services could have no limit.
The volunteers will add their language knowledge in the online community by creating new translations for words and phrases, any existing translations can be corrected, and the volunteers can rate the existing translations for accuracy. Google Translate was launched in 2006, offering translations between Arabic and English, according to Google.
By giving volunteers the opportunity to offer their two cents, Google gains the knowledge and experience of seasoned translators around the world. This will not only help improve the quality of the 80 current languages offered, but also provide Google the opportunity to expand its offerings to many other languages in the future.
The volunteer’s input will be used in the latest version of Google Translate, which includes more language support for the built-in handwriting feature, giving users the ability to write words directly into Hebrew, Javanese and Esperanto on their devices for quick, easy access.
According to eweek.com, Google also has added a Camera Translation feature, which allows the user to simply snap a photo of written text with their android device and highlight the words that need to be translated. Source:
I recently ran across an article extolling the virtues of Google MT – http://www.independent.co.uk/life-style/gadgets-and-tech/features/how-google-translate-works-2353594.html. While I agree with many of the ideas in the article, a few of the points and the whole tone of the article seemed out of line with reality. First, the idea that MT should focus on statistics more than extracting meaning I agree with…at least for now. But lets at least concede that that is fundamentally different than what we do as humans. I do believe in statistical theory, and have in my linguistic background studied the role that statistics plays in human language but I do NOT believe that word sequences and alignment statistics are the only determining characteristics of acceptability for a sentence. I DO look at meaning. So given this fundamental difference in processing, we have to assume the introduction of errors. So while the article praises the virtues of statistical based processing, let’s temper our enthusiasm as that is only part of the puzzle, and probably not the most important one for real fully automated high-quality machine translation.
Which brings me to my next point. The most inexplicable part of the article is where the author, David Bellos, discusses how human translation errors are usually more dangerous than MT errors. I’m completely lost on the reasoning here. He says when Google MT makes an error, it’s obvious, but the human translators make an error, it’s not, so human translation errors are more dangerous. Analogously then, as a business owner, the data entry guy that 10 to 20% of the time spews junk is preferable because I know I can ignore his garbage vs. the guy that makes an error once every 100 or 200 entries. What? Isn’t the reason I’m getting data entry (analogously translation) because I WANT to understand, not disregard, the output? I’m baffled. The only reason that human errors would be more dangerous, is because the output is actually useful – and that’s kinda the idea.
Finally, the name of the article is “How Google Translate Works”. While I understand that he’s probably trying to write for a broader crowd, it doesn’t really go into any technical detail beyond “it uses human translations” and “it uses statistics”. No equations, no specifics. And then he makes the assumption that because our desires and needs are the same, the premise of everything-has-been-said-before MT should work. Once again, while I don’t outright disagree, linguistic nuances go a little deeper than that.