Language Lessons: translating the global conversationFebruary 21st, 2011 by Ville Miettinen
Over the years, computers have come a long way from being humble adding machines. These days hardware is lightweight and good looking, while some software is so sophisticated it practically comes with Michelin stars. Despite all this progress, one area where machines have traditionally struggled is language translation (remember the bad old days of Alta Vista’s Babel Fish?).
The problem is that human languages are too complex to be easily broken down into computer-proof algorithms. However, as we’ve discussed before, machine translation is now starting to evolve. Google, in particular, has pioneered new techniques that work by using cloud computing to trawl through and analyze huge numbers of multilingual documents online.
On the web, English remains dominant, and businesses still have to speak English to survive (except in Denmark, according to our Travelling Salesman). However, the development of web 2.0, mobile internet and broadband mean people are spending more and more personal time online. And, as life gets uploaded, so do languages. Our friends at the social network Xiha Life have even added a “Translate button” to their site interface. Using machine translation, the button allows members (who come from over 200 countries) to switch between languages in real-time.
Facing the crowd
While machine translation is slowly improving, crowdsourced translation is booming. Take Facebook for example: in 2008 the social network launched Translations, an open community where users translate, review and verify new language versions of the site. There have been some teething troubles but, two years on, Facebook is now available in 64 languages and counting. Similar crowdsourcing methods have been used by Twitter and Wikipedia (as well as by smaller, but equally useful, sites like Italian subs addicted).
But the “community translation method” isn’t always popular. In 2009, business network LinkedIn tried pretty much the same thing as Facebook. LinkedIn asked members who were listed as professional translators to help render the site into more languages. When users realized the work was unpaid, many refused and some even said they felt insulted.
I guess the lesson is to pitch to the right crowd. Facebook users are there to socialize, have fun, and spam you with endless friend requests. Translations became another way of getting involved and meeting new people. LinkedIn, on the other hand, provides a service for business people. It’s a useful networking tool, but not necessarily a site users want to spend all hours of the day on or personally help develop.
A crowded market
The big names of web 2.0 may choose to translate internally, but crowdsourcing translation startups are also on the rise. There’s a long list of companies offering everything from document translation to software localization.
Take servioTranslate, part of crowdsourcing heavyweight CloudCrowd. ServioTranslate focuses on cheap (6.7 cents a word) and speedy document translation. The process runs like an assembly line: text is divided up, put through a machine translation and then distributed to the crowd (via a Facebook app) for error checking and reassembly. In contrast, at German startup toLingo the mantra is quality. ToLingo boasts a pre-checked database of 6000 translators, guaranteed native speakers and “triple checks” on documents. One potential issue with both startups is that users have to upload text or documents individually. Compared to the cutting edge services on offer, this seems old-fashioned and inflexible – the Servio uploader, for example, will only accept MS Word documents.
It’s too early to tell which startup will emerge as leader of the multi-lingual pack. The race is on to create a service with the perfect combination of high speed, high quality and low-cost. Of course, the only way to test if the crowd can really beat computers at translation is to try them out. If anyone’s had experience, good or bad, with crowdsourced translation, we’d love to hear from you. Comments in your language of choice.