Crowdsourcing for Software Localization
Leveraging the power of the crowd to provide translation is an increasingly popular way to satisfy some organization’s translation and localization requirements for different content types such as user generated content (UGC).
This can also apply to some content associated to software. With global software products, there is quite often a wealth of associated lower impact content such as blogs, wikis, knowledge bases, user forums and other less formal content types that may qualify for crowdsourcing translation. Some of these content types are published by the software companies themselves, some content is published by the users and developer community.
Social media can also be very active around the software community with forums discussing and reviewing new product features. Quite often, this content falls outside of the main software localization program, where there is greater emphasis on the higher impact content like UI strings, product literature, support and marketing materials.
One way companies are addressing the real-time translation for high volume content types is with the power of the global crowd. It can help with product adoption, around-the-clock translation in real-time, market expansion and user experience. As Joaquin Soler, Welocalize Vice President of Supply Chain at Welocalize, wrote in his blog, What is Crowdsourcing?, “Crowdsourcing has become an iconic concept of the new collaborative, truly global economy.”
In the world of software localization, crowdsourcing is more frequently used for supporting material and content types. The question some are asking now, can crowdsourcing be used to localize the product itself? The world’s largest wiki, Wikipedia, uses crowdsourcing to create and translate the articles; however, it is the user generated content (UGC) that is crowdsourced and not the product itself.
For open-source software, crowdsourcing is being used to localize the product. Mozilla is an example where software development takes place using the crowd. 40% of Mozilla’s work, from coding to brand development, is completed by volunteers or as we would refer to as a crowd.
Mozilla has an array of localized software. Mozilla Firefox is one of the most localized web browsers with 90 languages localized in its latest release. Mozilla Firefox is an open source application and the company has a global team of volunteer translators who use web-based localization tools like Pontoon, Verbatim and Narro to input and localize the product. Mozilla has extensive resources online informing their volunteer “localizers” on patching localization bugs, writing localization code and how to use their web-based localization tools. Mozilla frequently uses external talent pools who donate their time and skills to assist localization and product development.
For commercial and licensed software, there are notable risks when using the crowd for product localization — primarily with challenges related to quality. Beyond usability, a failure to accurately translate a string could actually create a product launch failure in a certain language or software bug that would disable users completely.
No software company can afford to risk a new release based on a badly translated line of code. In fact, it would be unheard of for most global software enterprises to directly release software post-crowd translation. Volunteers may be used to translate aspects of the product code; however, there are several follow-up steps that in a proven software localization workflow to get a product market-ready. The code doesn’t just need translating, it also requires rigorous testing, quality assurance and engineering to confirm all linguistic applications are accurate and secure. This level of quality and expertise are not easily applied to a crowd situation.
The power of the crowd, when managed correctly, can be of tremendous value and benefit. The role of crowdsourcing in software localization is far more successful for supporting content, like UGC, wikis, forums and social media, rather than the product itself.
What are your opinions on crowdsourcing for software localization?