TechGist05

 This is a guest post on Translation Metadata by Luigi Muzii. Some may recall his previous post: The Obscure and Controversial Importance of Metadata . Luigi's view of translation metadata is much broader and all-encompassing than most descriptions we see in the translation industry which usually only reference TM descriptors . In addition to descriptors about the TM, it can also be about the various kinds of projects, the kinds of TM, translators used, higher levels of an ontological organization, client feedback, profitability and other parameters that are crucial to developing meaningful performance indicators (KPI). As we head into the world of AI-driven efficiencies, the quality of the data and the quality and sophistication of the management of your data becomes significantly more strategic and important. I have observed over the years that LSPs struggle to gather data for MT engine training and that for many if not most, the data sits in an unstructured and unorganized ma...

This is a guest post by Ondřej Matuška, t he Sales & Marketing Manager of Lexical Computing , a company that develops a corpus and language data analysis product called Sketch Engine .  I was first made aware of Sketch Engine by Jost Zetzsche's newsletter (276th Edition of the Tool Box) a few weeks ago. As relatively clean text corpora proliferate and grow in data volume, it becomes necessary to use new kinds of tools to understand this huge volume of text data, which may or may not be under consideration for translation. These new tools help us to understand how to accurately profile the most prominent linguistic patterns in large collections of textual language data and extract useful knowledge from these new corpora to help in many translation related tasks. For those of us in the MT world, there have always been student-made (mostly by graduate students in NLP and computational linguistic programs )  tools that were used and needed to understand the corpus for better M...