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Typical Localization Challenges and How Tech Can Help

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While big data presents an enormous challenge to localization professionals, it’s also the secret sauce that powers automated translation software and other linguistic tools that solve localization challenges, speeding up and optimizing otherwise tedious processes. In this Slideshare, we’ve explored a few emerging technologies that, against popular belief, could make localization teams more valuable to their organizations.

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Typical Localization Challenges and How Tech Can Help

  1. 1. Typical Localization Challenges and How Tech Can Help
  2. 2. When it comes to localization, friction is the enemy Creating content with a global audience in mind from the beginning vastly reduces costs. But many organizations become overwhelmed when it’s time to localize and struggle to get behind the concept. If done manually, the localization process can be long, repetitive, and arduous—filled with emails, phone calls, and file transfers. Manual practices are not only outdated but add costs that localization is designed to cut, with too much time dedicated to administrative tasks that take away from bottom line-driven responsibilities. Technology has come a long way in removing this friction. Here’s a look at three of the most common challenges in localization and technologies that speed up the process, getting you to market faster.
  3. 3. INEFFICIENT BUSINESS PROCESSES Using email, phone, and FTP systems to manage, share, and track translation assets leads to inefficient processes—not to mention high administrative overhead and lack of visibility. OVERWHELMED RESOURCES Relying only on bilingual in-country specialists to review translated content places significant pressure on resources. Many of them also juggle a day job. DISPARATE CONTENT SYSTEMS Translating content across multiple, disparate systems can often be the most difficult part of the process— but it’s also the most critical. 01 CHALLENGE 02 CHALLENGE 03 CHALLENGE 03
  4. 4. Technology can take you to the next level But technology can also take you beyond the limitations of human translation, which is becoming more and more critical. The digital economy has created an explosion in the amount of content that might need to be translated: blogs, comments, forums, chat sessions, and social media posts to name a few. Providing hyper-targeted, personalized customer experiences in individuals’ own languages will require the use of advanced localization techniques. At each stage, CMS integration and automated workflows have the power to simplify inefficient, complex, and error-prone tasks. 04
  5. 5. Industry analysts estimate that human translators have the capacity to address only 0.00000000009% of the global content generated in a single day. Big data has increased the volume of content dramatically. At the same time, the following big-data-based innovations help close the growing gap between what’s generated and what’s actually translated. 05
  6. 6. 01 TECHNOLOGY As companies seek more efficient ways to deliver more content in more languages, NMT is evolving from a niche solution reserved for very large, global enterprises into a mainstream option. NMT uses the power of deep learning and a higher volume of training data to build an artificial neural network. The network can find patterns, such as contextual clues around the source sentence, that help accelerate and improve translations. Because big data yields so much information, NMT is able to identify complicated associations among these patterns that are beyond human ability to recognize. 06 NEURAL MACHINE TRANSLATION
  7. 7. 02 TECHNOLOGY On the one hand, the growth of content exceeds human ability to review everything, and on the other, there’s no time to waste. Overcoming this challenge requires marrying human translation with technology that automates predictable language quality checks. Automated language QA is a well-established, collaborative, and powerful quality control tool that uses pattern recognition and other approaches to identify potential problems—including broken or missing links, inconsistent terminology, and missing content. An automated QA engine can detect more errors than human review alone. This helps reviewers focus less on mechanical issues and more on brand messaging. 07 AUTOMATED LANGUAGE QA
  8. 8. 03 TECHNOLOGY ML algorithms are key not only for NMT, but also in every linguistic workflow step. Crucially, ML can map the right work at the right time to the best worker for the job. Using linguistic big data, ML identifies which human resource has proven experience translating a particular type of content. But it can also identify the right linguistic resources and processes, focusing translators’ attention on areas with potential translatability issues. In this way, everything is prepared from the beginning to assure the best possible quality. 08 MACHINE LEARNING
  9. 9. 09 Once you’ve established what tech you need, it’s time to get buy-in from your organization’s decision makers. Lay the groundwork for success by aligning these technologies with the people and processes best suited to deploy them.
  10. 10. 10 Download our whitepaper, The Strategic Shift: Localization’s Fast Track to Driving Greater Business Value, to learn how to get stakeholders on board with linguistic technologies and get started on a revenue-driven strategy. How to make your case It should come as no surprise that successful globalization requires commitment and coordination across your entire organization. But let’s face it— internal customers often put localization needs last. This line of thinking means localization teams may get left out of strategic decisions.
  11. 11. About Lionbridge Lionbridge enables more than 800 world-leading brands to increase market share, speed product adoption and effectively engage customer in local markets worldwide. We provide technical documentation, labor time, warranty and service information development and validation, training development, engineering services, translation, and application testing solutions that ensure global brand consistency, local relevancy and technical usability across all touch points of the customer lifecycle. Based in Waltham, Mass., Lionbridge maintains solution centers in 28 countries. LEARN MORE AT LIONBRIDGE.COM © 2017 Lionbridge. All Rights Reserved.

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