Module 3 of 10

Evaluating & Implementing AIĀ 

Quality is one of the most important aspects to consider when choosing an AI provider. There are tried and tested methods for determining the quality of machine translation content, and they don’t include asking translators open-ended questions! In this module, we will provide an overview of different ways to evaluate the quality of machine translation, including error analysis (which is later used to customise systems and/or inform post-editors through post-editing guidelines).

What You'll Learn

Topics covered in this Module

Is automatic translation the same for all languages and content types?

Languages – from the most suitable to the most complex

Content – required characteristics for suitable content

Automatic metrics (from Bleu to Comet)

Human evaluation

Most common errors

Gross mistranslations

Post-edit distance

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