Big Data is Predicting the Future of Translation

Posted on July 5, 2017 By

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Many organisations have multiple, multi-layered translation requirements that need accurate handling and quick turnaround. To meet the needs of these organisations, many translation service providers use various automated tools that offer both accuracy and efficiency, yet fall short of delivering quantifiable measurements to truly gauge the effectiveness of their service.

Enter cloud-based translation tools. These tools store content in the cloud and may be used by any number of organisations and services. While desktop tools live in a corporate hard drive somewhere and sit in isolation, cloud-based translation tools serve as a ‘house’ to the translation projects of a large number of organisations. It can thus aggregate the information it collects in terms of languages used, who the human translators are, who the clients are, the industries represented, the types of communication materials translated, the subject matters covered, the length of time each translation takes, and many more.

The result: big data that can generate trends and answer such questions as:

  • Which languages are growing in demand and which ones are decreasing?
  • Which human translators are producing reliable and accurate work?
  • How long does it take for certain types of work to be completed?

Cloud-based tools can also be used to generate specific reports on specific projects or campaigns, and yield comparisons such as accuracy levels between a human and a machine translator.

Looking beyond generating trends, cloud-based translation tools also store language ‘memory’ in one place, collating information across all the documents that it stores across all the languages used. ‘Acquiring’ the languages and organising all the language knowledge in a single place means fewer errors as the translation tool ‘learns’ over time. This increases the reliability of its results, and enables providers and human translators to focus on essential elements such as style, tone, nuances, and the natural flow of words..

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