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Mar 6, 2014   //   by Patricio   //   Blog  //  No Comments

10 points about MT. Fact or Fiction?

Let me start out by saying that I love Machine Translation. There is just something magical about inputting text which is totally foreign to you on a computer screen, clicking a button and then reading it in your own language. If you are lucky enough to own your own MT server or software, like I do, and can adjust dictionary terms and create language rules, it becomes even more magical.

 

I am somewhat of an authority on MT, having spent four years of my life developing software and workflows around MT. We developed a product, the GTS WordPress Plugin, which translates WordPress websites and blogs into over 30 languages. Our software has been installed in over 1,000 websites. More about that here.

 

So when Jaap asked me to write a blog post on the TAUS blog, I thought that perhaps it would be a good idea to express my own convictions about MT. I’ll state my case, but it will be up to you to decide if the points I make are fact or fiction. Please feel free to add your comments to this post and contribute to the discussion.

 

Ready? Here goes:

 

1. MT is as mature as it will ever be. Let’s face it. Ever since SMT became the standard, MT reached its maturity stage. For years people said that MT is in the embryonic stage and predicted that technological breakthroughs will make it better, near human quality. I say that the time for that has passed and that MT is as good as it will ever be. For several years now people have been saying that Google has been making deals with content owners to align zillions of megatons of corpora for MT training. But the result, as anyone who uses Google Translate knows, is often laughable.

 

2. MT will never be as good as professional, human translation. The logical succession to my previous point is that MT will never, ever be as good as human translation.

 

3. The VCs have rendered their decision: MT is out, human translation is in. In the last 2-3 year a number of venture capital companies have poured millions into companies that develop human translation automation platforms. Smartling, One Hour Translation and Gengo are some examples. The smart VC money is going into human translation and no or very little money is going into MT. What does that indicate about the financial viability of MT as a business?

 

4. Post-editing MT will never go mainstream with translators. We need to face reality. Professional translators will always disdain MT, mistrust it. MT will never be a hit with translators. LSPs that want to sell edited MT will either have to cajole freelancers to take work that they don’t want, hire inferior translators, or train in-house staff.

 

5. Post-edited MT is not as good as from-scratch. Everyone has heard the ‘you get 2 out of 3’ saying. When you deliver post-edited translations, it will be cheap and fast, but will not be (as) good. LSPs will need to have two SLAs, one for a pure human process and one for PE-MT. I have heard this stated by Wayne Bourland, the localization chief at Dell, at the AMTA 2012 conference in San Diego. I think that this should  become an industry standard.

 

6. Universal translator? Only on Star Trek. Now and then we read about a new speech-to-speech Universal Translator, where one person speaks e.g. in Chinese on one end and the other person hears e.g. English on the other end. Google, Microsoft and others have developed prototypes. I say that these products will never reach a point where they can be used in day-to-day situations, at least not in our lifetime.

 

7. Training MT engines is a game for big boys. Training an MT engine for a specific domain, customer etc. is a very costly and knowledge intensive exercise. You need to have heavy computing resources, computational linguists, software engineers, system admins. There are not that many companies that have the resources to train MT and this activity is best left to the experts. One example that comes to mind is Alon Lavie at Safaba who offers custom MT development.

 

8. Training in a cloud is pipe dream. Recently, some companies have come out with cloud solutions which allow you to upload a training corpus and create and access a custom MT engine. Sounds like a great idea but I say that it is about as feasible as the Universal Translator.

 

9. 99% of the world’s population will remain ignorant about what MT is really about. When I tell people that I sell translation services for a living, I invariably hear someone ask :”isn’t that all done by Google nowadays?” I used to get irked by these responses and respond with long speeches. Now I just smile and say “have a nice day.”

10. The demand for MT will grow. Everyone who is connected to this business sees how the demand for translation services is constantly growing. As more and more content needs to get translated, organizations will turn to MT as a viable option for material which is non mission-critical

(Autor: David Grunwald, izvor: https://blog.taus.net/blog/10-points-about-mt-fact-or-fiction)

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