And as Google noted in its blog, Poland’s Ministry of Economy is taking advantage of this translation engine to provide web users with real-time translated content. The Google Translate engine is built right into the header.

Here’s a screen grab from their site (translated from Polish into English):

However, you’ll notice that the main header is still in Polish.

Why is that?

Blame embedded text.

Embedding text within visuals is a great way to ensure that the text appears exactly how you wish it to appear. But it’s a lousy way to make that text translateable, indexable, etc.

So don’t do it.

You can achieve a similar effect using style sheets and background images. Fonts may vary based on operating system, but even this too can be managed via hosted fonts.

Making your web site “translation friendly” is a great way to make the most of the free translation tools already out there. Eventually you’ll want to get your site professionally translated, but until then, unlock the text so users can translate it for themselves.

Link: Polish Ministry of Economy

But translation memory requires using translation memory software, which has for years largely meant using SDL Trados software.

When a company hires a translation agency and requires that they use translation memory — not only must that agency have Trados software, but so too must the freelance translators — who are often located all around the world. This is a nice business model for SDL, but it has been a pain point for translators and agencies for years.

For agencies, the more acute pain point has been that SDL not only sells TM software but also sells translation services. Nearly every translation exec I have spoken to has openly asked for an open-source alternative to Trados.

Well, now we have one.

IBM has partnered with LISA (Localization Industry Standards Association), Welocalize, Cisco, and Linux Solution Group e.V. (LiSoG) to launch an open source project that provides a “full-featured, enterprise-level translation workbench environment for professional translators.”

It’s called Open TM2 — and it’s basically a scaled-down version of what IBM has developed and used internally for years. I haven’t used the product yet and there’s understandably quite a bit of work involved to get this software to a point where it’s easy for translators, agencies, etc. to consume.

I’m not prepared to say Open TM2 is going to put an end to Trados. After all, Linux didn’t exactly put Windows or OSX out of business. But I am excited to see it out there in the world. Open source keeps software vendors on their toes. I’ll be very curious to see if developers embrace the code,  and what they come up with.

To learn more, I interviewed one of the partners behind Open TM2, Smith Yewell, CEO of Welocalize.

Here is what he had to say:

Q: Why did IBM decide to open source its software in this fashion? What does it hope to gain?

Bill Sullivan can answer this question better than I, but as he stated, “Freelance translators are the backbone of the localization industry. These translators have longed for free and open translation tools to increase their productivity. There is a recognized and growing need for standards in the localization industry. Despite our best intentions, however, standards themselves can often be vague and open to multiple interpretations. What is needed are reference implementations and reference platforms that serve as concrete and unambiguous models in support of the standard.”

In my opinion, productivity and standardization go hand-in-hand. By releasing Open TM2 as an open source product with a standards-based, data-exchange goal, not only is there potential for increased productivity – flexibility and freedom of choice also increase.

Q: And what do you hope to gain from this effort?

I like to use the mobile phone analogy. I can travel just about anywhere in the world, turn my phone on, and it works. This is possible, because competing carriers and hardware manufacturers collaborated to be able to offer that seamless user experience across global networks and handset protocols. Consider the user experience in our industry. There is really no ability for a client to turn on a translation supply chain and have it work out of the box across various content types, tools and translation vendors. The clients I speak with are demanding that this change.

GlobalSight, Joomla and Open TM2 are being used to demonstrate an example of a seamless data exchange based upon a set of standards. LISA will play an important role in documenting and sharing these standards so that they can be applied uniformly to other integrations. To put it simply, we need a variety of tools to be able to talk to each other in an automated way. This is where I think we can improve time, cost and quality results and greatly improve the user experience. Ultimately, I expect Welocalize to gain an increase in productivity, interoperability and freedom of choice in configuring the best set of tools for each client’s unique translation supply chain needs. If we can get under the hood, we can tune the engine; otherwise, it is becoming increasingly difficult to gain time, cost and quality advantages from the old way of doing business.

Q: Who is going to use this software? And what software will it replace?

Many translators are already using TM2 in delivering work to IBM. I expect Open TM2, as its features grow, will appeal to more translators as a desktop workbench. This is only an initial release of the open source product, and there is much work to be done. But the potential is there to collaborate and improve. Ultimately, I think Open TM2 has the potential to replace the Trados desktop workbench.

Q: When you talk open source, stability and support are common pain points. Who will be actively supporting this effort?

The members of the Steering Committee are currently supporting the effort, and the goal is to build a community which can support itself. This open source initiative is not unlike others, what one puts into it will determine the benefits one can pull from it. I wouldn’t be surprised to see a company create a business model to offer Open TM2 support. Support, training and customization are typical services that bloom around open source initiatives.

Q: What would stop a technology company from taking the source code and creating a competitive ™ product?

It is an open source product, so there is potential for companies to build a business model around the product. However, I doubt that will be a proprietary fork of the code. The appeal is an open source product with growing standards compliance, not yet another proprietary product. What is more likely are support, training and integration services. Anyone investing in the product naturally expects a return, and the better the return, the more healthy and diverse will be the community. I think that is a good thing. Competition drives innovation. However, if we can’t get the standard data-exchange protocols right, productivity across the supply chain will continue to lag the increasing velocity of change in the marketplace. Rapidly evolving time, cost and quality demands already exceed what the traditional translation supply chain can deliver.

Q: The source code is available now but documentation is lacking. What is your timetable for launching a more translator and agency friendly product.

I think the first step for the Steering Committee is to take the feedback that is already coming in about the product, good and bad, and use that to set priorities, responsibilities and a timeline. The idea is sound, but it must be tested in practical use and refined according to what the market really needs. Translators have the answers to many challenges in our supply chain, they are just not asked very often.

Q: How will this software be integrated? Is there is a goal of integrating it with the open source GlobalSight CMS?

Content creation, translation, workflow and performance metrics reporting – there are many systems and tools for accomplishing each of these requirements. However, very few of them can pass necessary data in an automated way. A lot can be accomplished with web services and open APIs, but widespread integration possibilities can only be realized with a critical mass actively using an industry-supported data-exchange standard.

In order to demonstrate this possibility in a live use case scenario, Joomla, GlobalSight and Open TM2 will be integrated with the resultant standards published by LISA. I think additional standards organizations will also need to participate to gain wider understanding, agreement and adoption. If enough of the industry’s thought leaders and leading practitioners get behind this standard data-exchange and tools integration challenge, I think all boats will rise. Without it, the industry will never be able to approach the growing volume of content which current production and cost models can’t support.

Link: Open TM2

That is, I admire the organization’s goal of broadly sharing translation memories (TM).

But I’ve been less than enthusiastic about how this organization operates.

TAUS always felt a bit like a country club — in which only a few large players could afford to join and its inner workings kept top-secret. TAUS caught some flack awhile back from trying to prevent its attendees from tweeting its conference sessions. It’s this culture of secrecy that has always bothered me. For translation memory sharing to go mainstream, you need to raise awareness significantly. You need lots of evangelists embedded in companies large and small.

So I’m happy to see TAUS lowering admission fees for its Data Association. TAUS writes:

The annual associate level fee has come down from €625 to €250. Professional membership has been reduced from €75 to €50 and allows individuals to download 10 times the amount of data that is uploaded.

Many executives that I speak with still do not see the value of sharing previously translated text strings (if this is on their radar to begin with). And if you don’t see the value in sharing TM, you sure as heck aren’t going to throw money at it.

More important, you’re not going to throw money at membership fees for something you don’t understand.

By lowering the fees, not only do you expand your organization to smaller players, you lower the barrier for larger organization that may not yet see the value of participating.

It will be interesting to see how membership evolves based on this change. The last I checked, current membership stands at roughly 70 corporate members.

Note to translators: I’m not implying you’ll be out of business anytime soon. But I am saying that machine translation (MT) is going to find its niche and this niche will grow exponentially. There is simply not enough translators in the world to handle the content necessary in this increasingly global economy.

Enter Lionbridge and IBM.

In March, the two companies inked a multi-year partnership in which Lionbridge would have exclusive rights to market IBM’s Real Time Translation Service (RTTS) technology.

I recently asked Lionbridge COO Satish Maripuri about the deal.

Here is the interview:

Q: It appears that Lionbridge is trying to replace the legacy term “machine translation” with Real-Time Translation. Why do you think this new term is better?

Real-Time Translation is a more accurate term for the solution. We see machine translation as a technology that enables the solution.  Real time instantaneous translation is the solution. Also, within the localization industry, Machine Translation typically refers to using productivity tools to offset the cost and time associated with translation and usually ends with a heavy post edit (PE) to get the content to publication quality. That is different than instantaneous real time translation that delivers “good-enough” translation without post edit if a customer so desires.

Q: When you talk to companies about machine translation, what types of content are they most excited about leveraging through your MT engine?

The customer excitement is remarkable. This one announcement created more in-bound interest than any announcement in our history. Organizations are most excited about translating the enterprise content that they aren’t translating today due to cost and time associated with the traditional localization process. Examples include: user generated content, research  reports, eSupport, social media, knowledge bases, website content and real time instantaneous chat/email communication.

Q: We still live in a “cost per word” translation ecosystem. Do you see real-time translation as the beginning of the end of the per-word pricing model?

Details around the new pricing model will be forthcoming, but it will follow a SaaS model subscription fee and/or seat license for certain applications. This will be different than the traditional per-word pricing model.  Time will tell whether this will lead to a change in the way organizations view all translation pricing. But for real time translation technology, SaaS-based subscription pricing is clearly the right model.

Q: In my view, Google has done more than any language provider to demonstrate that machine translation has a valuable role to play in global communications. Is there any concern at Lionbridge, that Google might open up its MT engine to companies via its Apps platform?

Google’s automated translation tool is a highly visible application.  And you are right in that it creates awareness of the opportunity for automated translation. There are applications for Google’s technology, specifically in its ability to enhance search.  Our focus is on enterprise content – which is a different application for automated translation in that it requires higher levels of quality and utility within the enterprise.

For the last five years, Lionbridge has been using and continuously developing our translation management platform — Translation Workspace. This technology combined with IBM’s real-time translation technology will allow us to customize the engine to our customer-specific domains to provide levels of quality that far surpass any freeware translation technology. This customization combined with cloud availability through Translation Workspace differentiates our tool from freeware tools and creates a  highly valuable application for the enterprise.

Q: TAUS has been critical of the Lionbridge/IBM alliance as an attempt to “lock in” users via ownership of the translation resources. TAUS has called on Lionbridge to open up your data. What is Lionbridge’s response?

Customers who use Lionbridge’s real time translation technology are not locked in to Lionbridge for any service — post edit or other traditional managed service translation. We are only providing our customers with a technology application to support real-time multilingual communication.  As such, our customers would simply license the technology to support real time translation. If they choose to post edit the result, they can use any service provider they choose.

Q: What do you estimate will be the ratio of human translated content to machine translated content in a typical company — say from today to five years from now?

As machine translation improves over time we believe it will be used more frequently, especially on dynamic user-generated content. We also believe over the next ten years we are going to see a shift from “Just in Case Translation” — just in case someone happens to read to “Just in Time Translation” — translation after someone shows interest.

In addition, we believe that over the next five to ten years, there will be more acceptance in the market for “good-enough” translation. Therefore, it would not be unreasonable to see a larger percentages of enterprise content translated using machine translation or Real-Time Translation technology.

For more information:

• Lionbridge announcement
• TAUS comments on the deal
• SDL comments on the deal
• Lionbridge response to SDL

• Google Translate
• Bing (Microsoft) Translator
• Yahoo! Babelfish

Ethan Shen has wrapped up the project, soliciting input from more than 1,000 reviewers. He summed up his findings here.

Here are the findings that jumped out at me:

• Google wins, hands down, translating longer text passages. No big surprise here.
• Bing and Babelfish are competitive translating shorter texts (150 or fewer characters). Bing did quite well with Italian and German, while Babelfish did well with Chinese.
• Google’s brand trumps all. About halfway through his test, Ethan removed the brand names from the search engines, so the reviewers did not know which engine was doing which translation. The change in results was significant. Reviewers were 21% more likely to say Google was better than Microsoft when they knew the brand names. And reviewers were 136% more likely to say Google was better than Babelfish.

This last finding is what poses the greatest hurdle for Microsoft and Yahoo!

When it comes to machine translation — perception is (almost) everything. If people think you’re the best translation engine, then you are the best.

Integration is the other key element of success, and Google Translate is doing well here also — I absolutely love the Chrome browser integration.

Ethan is not done with his research. This is only stage one. To help him with stage two, click here.

So not only is Google automatically transcribing the text of its videos, it’s also providing translations — via machine translation. Now I just need a “machine reader” so I can process all of this new content — as I’m running out of hours in a day.

Google’s blog post notes:

In the next few months we expect over 150,000 Youtube channels to implement auto-captioning with translation. This is just the beginning and we hope that all Youtube content will soon be enjoyed by all Youtube users, regardless of what language they speak.

One of the examples cited is a TED talk by author Elizabeth Gilbert, show here:

Here’s how you enable the auto-translation — hover your mouse over the Closed Caption icon and click the Translate Captions link.

I found the language-selection overlay (shown below) challenging to scroll through. But I suspect this feature will be automated eventually, similar to how Google’s Chrome browser has automated translation based on your language setting.

What I find interesting about the Gilbert talk is that TED has recruited its own army of translators — human translators — to do the same thing but in higher quality.

Here is the TED-translated version of the same talk:

I think it’s safe to assume that the volunteers are going to offer a much higher-quality translation of the video. But TED does not (yet) support the breadth of languages that Google supports. So while TED has the advantage in quality, Google has the advantage in languages.

But the larger is to what extent Google will make the TED-translated video as easy to find as its own YouTube version.

I did a Google search today and both videos emerged at the top of the results:

I believe this scenario raises a few interesting issues that will need to be addressed in the years ahead:

• How to easily differentiate between content that has been machine translated vs. human translated
• How to quickly discover which content is available in which languages
• Will the crowd continue to be as enthused about translating content by hand when Google  provides the same service, albeit in lower quality, for free?
  

Ethan has provided me with a mid-point summary of results, which I’ve included below. I was surprised to find that Microsoft and Babelfish are beating Google on some languages pairs, as well as on shorter text strings. Although Google is emerging the overall winner — and receiving some much-deserved attention from the media — it’s nice to see some healthy competition.

That said, quality is only one piece of the puzzle. The other piece — perhaps much more important — is usability. Now that Google has embedded its MT engine into Gmail and Reader — and now its Chrome client –I find I’m using Google exclusively as my MT engine.

Here are Ethan’s findings so far (emphasis mine):

At the highest level, it appears that survey participants prefer Google Translate’s results across the board.

In a few languages (Arabic, Polish, Dutch) the preference is overwhelming with votes for Google doubling its nearest competitor

However, once you remove voters that have self defined their fluency in the source or target language as “limited,” the contest becomes closer along some of the heavily trafficked languages. For example:

• Microsoft Bing Translator leads in German
• Yahoo! Babelfish leads in Chinese
• Google maintains its lead in Spanish, Japanese, and French

Observing only the self-defined “limited fluency” voter reveals a strong brand bias. If your fluency in the target translation language is limited, it would stand to reason your ability to assess the quality of the translation is very limited. And yet…

• Limited-fluency voters chose Google over Bing by 2 to 1
• They also chose Google over Yahoo! Babelfish by 5 to 1

As I had guessed, Yahoo! and Microsoft’s hybrid rules-based MT model performed better on shorter text passages

For phrases below 50 characters, Google’s lead in Spanish, Japanese, and French disappear. And Microsoft’s lead in German widens.

Beyond 50 characters, Google’s relative performance seems to improve across the board.

For passages that are only one sentence, the same effect is seen, though to a lesser extent than under 50 characters.

On March 4th, we made a few changes to our survey – hiding the brands and randomizing the positions of the text results before voting.  Since then, we have not yet collected enough data to draw conclusions, but Babelfish seems to be receiving the biggest boost, perhaps showing the effects of the recent neglect of that tool.

Clearly, Ethan needs more data to arrive at more concrete conclusions. If you’re a translator and you want to lend a hand, here is the voting site.

PS: Here’s an interview with Google’s MT guru Franz Josef Och.

But which engine offers the highest quality translations? I’m assuming Google, but this is only based on anecdotal feedback and personal experience.

Years ago, IBM developed an algorithmic method of measuring MT quality known as the BLEU score. Google scored well here, but the BLEU score is not without its critics.

Translation, like writing itself, is as much an art as it is a science.

Which is why translators are best positioned to judge the quality of machine translation engines. And although even translators are going to disagree as well, if you get enough of them together, perhaps you can begin to draw statistically significant conclusions.

Enter Ethan Shen and his start-up venture Gabble On.

Ethan has set out to recruit a few thousand volunteer translators to compare the three free translation engines. He asked me to help get out the word. He promises that he will publish the results for all to see. He’s also offering a free Apple iPad to one lucky volunteer. I have no financial interest in the project. I’m just curious to see what engine comes out on top.

Here are the details from Ethan:

We are seeking functional to fluent speakers of any two languages to take 5 minutes to judge and submit their opinion in our dynamic comparison engine (until March 29, 2010). At the end of the 6 week voting period, we will be publishing our results publicly in hopes that our research can to contribute meaningfully to the body of knowledge in this field.

In gratitude for your participation, we are awarding one new Apple iPad to a lucky participant. The survey can be found at: www.gabble-on.com/SurveySelector.aspx.

Which engine do you think is best?

In response to the earthquake in Haiti, Microsoft quickly expanded its machine translation engine to include Haitian Creole.

Today I noticed that Google has an alpha version of its Haitian Creole engine as well.

Though it’s sad that it took a natural disaster to spur attention to a particular language, I’m glad to see the language available.

It’s hard to underestimate the importance of readily accessible machine translation. Just as search engines help us better understand the world, machine translation engines help us better understand one another.

And, yes, they’re far from perfect. But they’re far better than nothing at all. And they are finding their way into countless applications and countless fixed and mobile devices, each additional language offering another glimpse into another world.

Six months later, Google added ten more languages, a two-year growth trajectory illustrated below:

Google went from 13 languages to 51 languages in less than 16 months.

Not bad.

And, yes, I’m aware that we must not confuse quantity of translations with quality of translations. Your translation mileage will most certainly vary by language pair. Still, as language pairs go, Google is the only game in town across many.

Here are the 10 most recently added languages:

• Albanian
• Afrikaans
• Belarusian
• Icelandic
• Irish
• Macedonian
• Malay
• Swahili
• Welsh
• Yiddish

On a related noted, 41 of these languages are now incorporated into Google Docs.

Every month there seems to be more of them, which could mean that the quality of Google Translate is improving, or this site is doing better in the rankings, or some combination of the two. Or, it could be simply be that more people have discovered Google Translate.

Given my passion for country codes, it’s fair to say that I also enjoy language codes. And it is through language codes that you can figure out what languages users were translating your site “from” and “to.”

Here is one referral string from my site:

First, you can see that the person was using Google Korea, so it’s fair to say the person was translating from English into Korean. The “To” line is actually the blog title post translated into Korean.

That was an easy one.

This next one is a bit more challenging:

This person was using Google.com, so you have to focus on the language codes. There are two here — an “id” (which follows  “hl=”) and an “en” (which follows “sl=”). What this means is the person was translating from English into Indonesian (Bahasa Indonesia).

Here is what the translated page looks like:

The quick and easy way to know the target language is to focus on the “hl=” string. In the screen shot below, the target language is German.

And here is a language code reference if you want to study your web logs.

What I want to know is what percentage of web traffic is taken up by Google Translate. Anyone care to share their Web log stats?

Based on my cursory analysis, I would estimate the figure to be between 5% and 10%, but that’s very rough.

For now, I’d like you to try entering the following text strings into both Bing and Google (to save you time I created pre-loaded hyperlinks):

• Translate I love you: Bing vs. Google
• Translate I love you into Chinese: Bing vs. Google
• How do you say I love you in Italian: Bing vs. Google

Below are screen shots of the first text string in both Bing and Google. I’ll let the pictures speak for themselves:

Google, despite its massively powerful translation engine, doesn’t simply answer your translation question. Instead, it provides links.

I realize that this is a relatively minor feature and that it currently only supports a small number of very common text strings, but it’s still a very handy feature for a translation geek such as myself.

Now, I’m not saying Bing is perfect. When it comes to technical searches — or when I just need to look up a Wikipedia article quickly — Google still does better, sometimes far better.

But I’m glad to see Bing integrating translation in an intuitive way. It’s a feature that I’ll be using again.

PS: Here is the blog announcement of this feature from Microsoft Translate team.

That said, I do wonder how this article is going to be received by the translators of the world who actually expect to be paid for their services.

For example the for-profit, invite-only conference company TED saved about $500,000 using volunteer translators. Clearly TED could have coughed up the money.

I can see this article spurring on CEOs across the land to think that they too can get free translations.

One thing I mentioned awhile back is that you need to be translation-worthy to get away with pro-bono services, particularly if you’re a for-profit company.

Facebook, Google and, now, TED appear to be translation-worthy. But I wouldn’t expect to see, say, General Motors succeeding in this area (though they could certainly use the help).

But the larger issue here is to the extent that volunteer translation for companies that can afford to pay for translation undermines the translation industry. I don’t believe machine translation undermines human translation because companies generally use it to translation text they would never have hired people to do (or they use it as a first pass before bringing on the human translators).

But volunteer translation is different.

Are  volunteer translators taking money away from their colleagues? After all, TED and Google and Facebook certainly can afford to pay. Or are volunteer translators raising awareness for the value of their work, thereby benefiting the translation industry as a whole?

Personally, I think we’re entering a dangerous area where companies that don’t know better are going to think they don’t have to pay for translation. This all reminds me of Seinfeld‘s George Costanza’s aversion to parking garages: Why should I pay, when if I apply myself, maybe I could get it for free?

This photo arrived courtesy of Gareth Morgan at Neovia Financial.

Apparently the proprietor of this restaurant in China decided to create an English-language sign using machine translation (MT) software and, apparently, the MT engine wasn’t working all that well.

So instead of “restaurant” we have “translate server error.”

It’s certainly one of the more memorable restaurant names I’ve come across. I’ll be sure to look out for it when I visit!

And I’ve love to know which MT engine delivered this message.

According to the unofficial Google blog, Google has inserted its “translate” link into a number of localized Google sites — such as France and Spain. Google.com is not yet included.

This is just another sign that translation is becoming a core element of Google’s world domination strategy. If you’re curious about Google’s market share around the world — here’s an interesting “crowdsourced” document.

Here is the France home page:

I rarely ever use this pull-down menu and I wonder how many others do. I realize that Google strives to keep an austere home page and this is one solution — but I’m not sure it’s worth it. If users can’t find the translation link they may never use it.

Google Translate is no longer growing up, it’s growing out — integrating itself across all of its many properties.

I’m happy to see Microsoft Research launch this new Web site widget.

I’ll have to test it out on my site when I get the time — and would love to hear from others who have tried it.

A demo site is here.

I really like how the widget creates a more seamless translation experience, which is a big step toward taking machine translation to the masses. I’m looking forward to the day when I no longer have to manually copy and paste URLs into Google Translate and the like.

However, I did get confused initially on figuring out how to return the page back to English. That bar at the top of the page blended in a bit too much at first. I’d like to see a language reset button on the widget itself.

I haven’t tried it yet. It looks like you have to post PDF files and then link to them to trigger the translation engine — not exactly what I’d call user friendly. But it’s a start..

This time last year, Google supported a mere 13 languages, which was in itself not bad.

But I particularly like the minor tweaks made to the site’s interface. As shown below, you can now click on your language to make it one half of a language pair — a welcome alternative to the pull-down menu, which continues to grow.

What I would like to see — and I suspect is less than a year away — is the ability to simply enter a URL and have Google auto-translate that Web site into your language without you having to specify your language. Google should already know this based on your locale setting — or at least let you set that preference ahead of time.

Google Translate can auto-detect the language for you right now — but you have to ask it to do that. Perhaps the processing overhead is such that Google doesn’t want to turn on this feature by default.

So, will Google support 70 or so languages a year from now? I doubt it, given the current economic climate. As Google notes on its blog, these 41 languages already address 98% of all Internet users. I assume that Google will focus less on language expansion and more on integrating Google Translate into its products as well as improving the UI.

To give you an idea of just how aggressive Google has been in this area, here is a screen grab of Google Translate from 2006:

And here is one from today:

That’s roughly twice the number of languages in two years.

Microsoft has also been busy over the past year. Like Google, it now supports machine translation using its own in-house engine.

And it also offers a handy Web translation widget that you can insert into your Web page to allows users to self-translate your site into their language.

The portfolio of languages is still on the light side, but like I’ve mentioned before, these types of developments illustrate that machine translation (despite its inherent limitations) is becoming a critical piece of the Web globalization puzzle.

UPDATE: Here’s an interview with Google MT researcher Franz Och.

The post I wrote on the Google Translation Center has been the most-visited page on this blog over the past month. Clearly, Google has struck a nerve in the translation industry — and its service is not even live yet.

The Translation Automation User Society does not appear to be as welcoming as I am of the Google Translation Center. A new essay on its site says:

Private companies will always seek world domination and customer lock-in. As a professional in the translation industry, the Google Translation Centre may help you on the short-term, but you only help Google long-term and you don’t help the world at all. Ultimately we pay the price for putting all translated words and sentences in the possession of a single company.

There is a distinct “evil empire” tone to this essay, which is understandable to a point. Google appears to be entering that evil empire stage of its development. Though I still use the search engine.

And the last I checked, Google’s “terms and services” page for the Translation Center had been taken down. So I can’t really say what Google’s policy will be regarding the translation memory (TM) that it may or may not leverage from this Center.

But it is no coincidence that TAUS is planning to develop a massive database of TMs of its own. I’m sure it wants readers to come away thinking that TAUS is going to be far more open with its TMs than Google will be.

TAUS says that its TM database will be free to the world for the looking up of translations of terms and phrases. But you’ll have to be a member to actually have access to the database (on a reciprocal basis) and membership is not free. I’m confident that this database will be of the highest quality as TAUS has some impressive corporate members, such as Intel, Microsoft, and Oracle (Google does not appear to be a member).

Personally, I’m glad to see both services emerging — as well as services from Asia Online and Language Weaver (which is now offering a Web-based SaaS translation service). We are entering uncharted waters and it’s important to have a mix of large and small players, as well as a nonprofit, to keep everyone on their toes.

Is there a risk to the world if Google owns the world’s largest TM (which it might have already accomplished)?

Perhaps.

TAUS raises important questions. The answers have yet to emerge.

My biggest concern is slow-loading Web pages. And, yes, I know the quality of the translation will leave plenty to be desired, but what I really like about the widget are the little RSS feed buttons. Just click the button and you can have translated feeds delivered to whatever feed reader you use.

What I don’t understand is the significance of the name “mloovi.” Am I missing something?

But here comes Google…

According to Blogoscoped, Google is about to launch the Google Translation Center.

This is an exciting development, though I don’t expect everyone to suddenly ditch ProZ for Google. Why? Because much of the appeal of ProZ is the community, which Google does not appear to be trying to support. Still, freelancers will certainly want to investigate this potential new resource.

I’ve called out ProZ as one company under threat from Google Translation Center. But EVERY translation agency needs to keep a close eye on this service. It could be a threat. It could also end up being something translation agencies use themselves — instead of paid platforms from SDL. Naturally, for this to happen this new platform has a lot of evolving to do. Still, I can’t help but wonder.

There is no mention of whether or not Google will support machine translation and/or translation memory. I’m assuming they will.

I have LOTS of questions and this service isn’t even live yet. So we shall see what happens. But this is big news, no question.

I wrote awhile back, that the translation industry as we know it is over. The technologists have taken over and they’re bringing brute force computing and massive networks to the table to reduce costs and increase time to market. This is just another sign of this macro trend.

What do you think? Is Google going to disrupt the translation industry or is this new platform going to fall flat?

(Thx Chris for the heads up!)

Update: I just read an insightful article on this Google’s service at GigaOm…