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Home / Overview / New Rules for Translation Requirements

Very few organizations are staffed with the specialized-software engineers, linguists and translators needed to conduct a successful multilingual project.

Costs aside, for information-based businesses, human translation is simply too slow and too costly to keep up with ever changing data. Time-sensitive applications such as news monitoring or stock trading can become obsolete in the hours, or even days that are needed for human translation. Multilingual customer support and communication also require on-demand translation, and often involve large volumes of text. Some examples are Internet self-help applications such as self-service technical support, email support and click-to-chat support. Users of these applications expect immediate results, a standard that would be impossible to meet with human translation. Even when translations are not needed immediately, it is prohibitively expensive to translate high-volume customer communications. Likewise, within organizations, email and instant messages require rapid turnaround at high volumes. These cannot be addressed with human translation solutions. Human translation and localization services are not feasible for highly-dynamic content. Many software companies maintain large knowledge bases of support materials. This content changes substantially as new bug reports, fixes and upgrade information are added. The cost and delays of retranslating a large, dynamic content source is unsupportable for any business. Some companies have attempted to use Translation Memory systems in conjunction with content management software to manage translation of their content. This solution is not adequate for dynamic content. TM systems rely on an existing resource of bilingual translation data. For example, a Translation Memory system can store a set of recurring sentences or phrases, and the translations that were made. Later, these translations can be simply “plugged in”, speeding the translation process.

For dynamic content, however, the percentage of reused content is low, making Translation Memory systems of limited value. Further, a Translation Memory system is not useful until it contains a large database of parallel source and target text. Producing the source and target text requires substantial effort by human translators. The cost and delay of human translation is unsupportable for any high volume or dynamic content. Automation of the translation process with Automated Real-Time Translation Software is the only viable solution for the majority of these applications. To date, companies have implemented this technology because of the compelling return on investment of Automated Real-Time Translation. In some cases also, organized opposition by translators has been a factor in the decision not to use Automated Real-Time Translation. The quality issue is central to the debate, and is the most frequently cited reason for not automating translation functions. This contention is addressed on multiple fronts, through integration support, custom lexical development, and quality review tools and metrics. The Mesa Group works with customers to ensure they understand the Automated Real-Time Translation workflow. This is critical to ensuring a successful implementation of Automated Real-Time Translation.