Top Reasons For Translation Crowdsourcing

We reviewed dozens of articles and cases about translation crowdsourcing and collected in this article all the reasons why companies do crowdsourcing. Most of the benefits are related to issues that are present in any translation work. But there are other reasons as well.

Translation cost naturally plays an important role. Surprisingly, in many articles the cost has been regarded as a secondary or minor reason for crowdsourcing translation. This is somewhat difficult to understand. For example, Facebook has been translated to 70 languages with over 100 000 words each. With the price of e.g. USD 0,10 per word that would be about USD 7 million which is a significant cost saving. On the other hand, Adam Wooten of Globalization Group Inc. claims that crowdsourcing will cost the same if not more than traditional professional translation. He does not mention any sources, though. Perhaps a reason that cost savings are not mentioned as important is that it could be difficult to persuade users to translate for free if the reason would be increasing company profits. Not surprisingly, some professional translators object strongly translation crowdsourcing by for-profit companies.

Translation speed is generally regarded as one of the most important reasons for translation crowdsourcing. An enlightening example is translation of Facebook to French. 4000 Facebook users translated the whole site to French in 24 hours! That must be a world record in translation speed. That kind of translation speed seems to be something that just can’t be achieved with traditional organization of translation. And as we all know, time is money: when Facebook surpassed MySpace it happened exactly because of its international users. The day Facebook became bigger than MySpace, in US MySpace still had twice as much users as Facebook.

Translation crowdsourcing is often very scalable. One user base is able to translate to many languages. There is no overhead in finding and recruiting translators for different languages. For example, Facebook would have had a difficult task in mere finding skilled translators for 70 languages.

What about translation quality then? Some believe that the users do produce better quality than professional translators because they know the field much better. While some disagree, I think it’s safe to say that the quality by crowdsourcing is at least “sufficient” or better. That has been the way with Facebook and Twitter. Microsoft and Cisco name quality and speed for the main reasons of translation crowdsourcing.

Marketing benefit, that is engaging users, has been regarded as one of the most important reasons for crowdsourcing. According to Facebook, 300 000 users have taken part in its translation. Facebook has over 500 000 000 users so roughly 6 in 10 000 users have been engaged by the translation process. Whether that is little or much is relative. In my opinion, crowdsourcing has not been an effective way to engage users for Facebook. Especially when probably only small share of the 300 000 (that downloaded the Facebook translation application) has actually translated actively. The user engagement benefit is further diminished with large languages. Of French speaking Facebook users, only 2 in 10 000 have had some part in the translation.

CONCLUSIONS

Speed is the greatest benefit of translation crowdsourcing. About quality there are differing views but we can say for certain that at least Facebook and Twitter have achieved good quality. Some argue that quality is better with crowdsourcing than with traditional translation. About cost it is difficult to get reliable information. At least Facebook has saved money with translation crowdsourcing.

Translation crowdsourcing improves scalability. This is also related to translation speed. Obviously recruiting professional translators for dozens of languages is much slower and more difficult compared to translation crowdsourcing in which it is sufficient to communicate with one’s own user base.

User engagement is regarded as an important reason but, at least for Facebook, its effectiveness seems to be limited.

Do you find this list complete or is there some reasons which should be added to this list?

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List of sources used in this article:

  • http://www.facebook.com/topic.php?uid=17732333448&topic=9517
  • http://techcrunch.com/2008/06/12/facebook-no-longer-the-second-largest-social-network/
  • http://www.deseretnews.com/article/705366964/Can-companies-obtain-free-professional-services-through-crowdsourcing.html?pg=1
  • http://blog.matthewbennett.es/44/linkedin-infuriates-professional-translators-10-big-questions/
  • http://welocalize.blogspot.com/2010/03/crowdsourcing-translation.html
  • http://www.globalization-group.com/edge/2011/03/why-crowdsource-translation/
  • http://www.commonsenseadvisory.com/Default.aspxContenttype=ArticleDetAD&tabID=63&Aid=591&moduleId=391

 

 

Are Translators Losing Their Jobs Because of Machine Translation?

Quite many professional translators are afraid that they will be replaced by emerging technology: machine translation. Machine translation would take their jobs or at least lower their salaries. I made some Internet searches and found interesting numbers. This article is about how many translators are needed to satisfy the communication needs in the whole world.

Please note that the following calculations and numbers are estimates and intended to give just a rough understanding of the situation.

For one professional translator translating 2000-2500 words per day seems to be quite a normal result (sources: Proz, Tips for Translators). Naturally the speed depends on the language and the translator. But we can use this number to calculate our rough estimates.

On one page there is on average 300-500 words. (source: NumberOf.net) When we combine this information with the average translation speed we conclude than an average translator can translate roughly 4-9 pages per day. Let’s use the average of 7 pages per day in our estimation.

Estimates of the total number of professional translators in the whole world vary between 150 000 and 300 000 (source: T&I Business).In the world there are currently over 6 900 000 000 people (source: Wikipedia). That is, below 0,005% of us work as professional translators. It is 20 000 people per one translator. To employ one translator 20 000 people (or companies they work for) should buy translation of 7 pages per day.

What do you think, is there enough work for all the translators, considering both the emergence of machine translation technology and that world trade and communication between people via Internet is growing fast?

My personal feeling is that 20 000 people (and the companies they work for) could use a lot more translations that just 7 pages per day. To me it seems there should be plenty of work even for more translators than currently exist. Maybe the prices of translations are preventing translation volumes from growing substantially?

Guidelines For Writing Text That Machine Can Translate Better

Machine translation is potentially a very effective technology. However, it is not 100% reliable and can not translate everything. The reliability of translation depends on the languages that are translated and especially on the text to-be-translated. By following certain, simple guidelines you can write text that machines can translate better.

1. Write short sentences.

When one sentence carries one meaning it’s easier for a computer to translate. Long, complicated sentences containing sub-clauses tend to be more difficult to translate. We recommend maximum of 25 words per sentence.

2.Write full, grammatically correct sentences.

Humans can understand more than computers. If you leave some words out of your sentences humans can usually nevertheless understand your meaning. However, computers will make more mistakes. The more possibilities there are for misunderstanding, the more mistakes machine translation will make.

3. Use common vocabulary.

Keep your language simple and use words that you use in normal language. Also note that machine translation can not usually translate specialized words well. For example, legal, medical, engineering etc. texts often contain special, field-specific words that the computer can not translate.

4. Avoid words that have several meanings.

If you use words that can be understood in several ways it’s likely that sometimes your meaning will be misunderstood. Therefore, when possible use words that are impossible to misunderstand.

All this can be summed up in one mnemonic: write text that is easy to understand and difficult to misunderstand. When you follow these guidelines your text will be easier to translate with a computer. And most of all, your text will be easier to understand by your readers too!

 

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Machine Translation: Friend or Foe For Human Translators?

Machine translation has a negative echo in many human translators’ ears. Many professional translators are afraid that as machine translation gets better and better, less and less human work is required and human translators might eventually lose their jobs.

Please consider this example. In the early 1900 car had just been invented. It was a new, exclusive technology. Car’s were difficult to manufacture and they were very expensive. What happened when Henry Ford developed ways to manufacture cars more efficiently and cheaply? One could think that some auto-workers lost their jobs because less people were required to manufacture a car. Instead, the opposite happened. The number of auto-workers increased dramatically because, thanks to more efficient and cheaper production, more and more people could now afford a car. Earlier middle or low income people had no chance of buying a car. When the car prices had sunk suddenly a lot of people could afford to buy a car and, in fact, actually bought one.

Now compare the professional translator’s situation to auto-worker’s situation. What will happen to professional translators when machine translation is making their work more effective? Will the professional translators lose their jobs? Or will the same happen with translators as with auto-workers in early 1900, when more and more companies and even private persons can really afford to buy translation and buying translation is becoming so easy in internet?

Using Machine Translation Is Like Driving a Car

I like to compare machine translation to driving a car. We all know how convenient and useful it is to travel to various places with a car. And many of us can and have a license to drive a car. Driving a car is a skill that has to be learned. When one has learned to drive a car, it is easy and useful to use the skill. But driving has some crucial limitations. Even when one can drive a car well, it is not possible to drive with the car anywhere, for example in the forest or from Europe to Australia or to the Moon. One has to stay on the road and on the solid soil. The situation is very similar with machine translation. One must know when and how machine translation can be used.

Machine translation is not a turnkey solution to all possible translation problems. One must know when machine translation can be used and especially how it should be used. For example, if you expect a computer to translate literature perfectly from one language to another you will surely be disappointed. But if you want to communicate simple matters to another language you might be positively surprised.

I would like to emphasize that machine translation is potentially a very effective tool that must be used correctly. Like a car, you must first learn how to drive it and where you can drive with it. Same applies to machine translation. Luckily, using machine translation is far, far easier to learn than driving a car.