In a global economy, lawsuits and government investigations frequently involve foreign language documents. Case teams can face thousands or even millions of documents written in multiple different languages. Lawyers in eDiscovery and litigation support professionals must quickly arrange for the translation of these documents so the case review can proceed.
With the advent of eDiscovery, many translation services emerged to do data translation. These businesses offered human translators with some legal knowledge. The manual translation process proved to be very costly and time-consuming. Review and production could be significantly delayed when large volumes of foreign language documents had to be translated.
Translation services have evolved over the years, with a tech revolution leading the way. However, a few things that have remained constant are the importance of translation accuracy, document chain of custody, security, and confidentiality. Let’s take a look at how technology has revolutionized translation in Discovery and where it’s going…
On-the-Fly Translation Apps for eDiscovery
About twenty years ago, publicly available translation Apps started to arrive on the scene. Google Translate is probably the best-known. Introduced in 2006, it’s a free tool that translates text and other media from one language into another. The translation is done “on the fly” — you drag and drop your documents/text into the App and the translation immediately appears.
But for eDiscovery professionals, data security and confidentiality concerns are big red flags with on-the-fly translators like Google Translate. Uploading your documents to an app poses security concerns — do you know for sure what happens to your data after you upload to a 3rd party wesbite for translation? If a hack occurs, will your client’s sensitive information be compromised? There is also a risk that your document chain of custody could be challenged if you use an on-the-fly translator.
Early Machine Translation Apps
Early machine translation Apps were rule-based. The machine translation software analyzed the source text, word for word, using a set of rules.
Early versions of Google Translate used the statistical machine translation (SMT) method. This method leverages the most common previous translations to translate a document or file phrase by phrase.
SMT Shortcomings for eDiscovery
Since then, legal tech companies and eDiscovery service providers started offering SMT-based machine translation in eDiscovery. The tool’s website often came with a plug-in to eDiscovery platforms.
However, there are shortcomings with SMT technology for data translation in eDiscovery. With SMT, a translation is only as good as the tool’s existing reference texts. Words or phrases in eDiscovery documents that aren’t in the SMT translator’s library won’t be found or will be garbled or translated out of context. SMT translators can give you the general gist of the text. However, they can fall short when translating grammatically incorrect language, idioms, cultural nuances, and context in language.
Anyone using SMT technology for legal data translation will want a human to review the translation results. In some instances, you may be able to limit the human review to key documents or documents from particular custodians.
From a practical perspective, your translation tool should ideally be well integrated with your discovery solution. If you use standalone solutions for data translation, you’ll have to migrate the translation results to your eDiscovery review platform. With a massive number of foreign documents, this will be time-consuming. Also, there is always a risk that data gets dropped during the migration.
Read full story at https://www.knovos.com/blog/the-evolution-of-translation-services-in-ediscovery/
