MT for workflow optimization

Since machine translation started to be commercially available, commercial users of machine translation had the challenge to identify use cases where MT increases value for the respective company. Over the years, three major use case categories seem to have evolved:

• MT for big data
• MT for workflow optimization
• MT as part of a translation service

For the category of workflow optimization, the main criterion is “cost”, but also “revenue”. To achieve that, MT use is put in the different workflows to minimize human involvement and therefore cost, or to increase speed of translation and therefore generating a competitive advantage. In some cases, the use of own technology is preferred, either in-house development, building on top of open source technology, or by using third-party MT tools. The use cases in this category can be from a fully automated translation service (MT service), over human-aided machine translation (HAMT service), to machine-aided human translation (MAHT service).

Adobe now uses Machine Translation plus post-editing as the default localization process for all of its product documentation and most of its UI.  The MT engines are customized using in-house translation memories, and post-editing is charged at a discounted rate as compared to translation from scratch.  The discounts are set by calculating the amount of time saved by post-editing.

TransPerfect’s proprietary methodology combines machine translation with complementary technologies and human translators to quickly and reliably produce usable translations for review of large volumes of text, all completed in a fraction of the time that would be required for a standard translation process. While machine translation quality falls far short of human translation, if used properly in conjunction with human reviewers, the utility of machine translation can be stretched to include both non-distribution applications including document review, legal discovery, and internal correspondence, as well as distribution-level materials for which extremely fast turnaround times are a requirement.

Etsy, an e-commerce marketplace specializing in vintage, art, and handmade goods, recently released a test integration of Machine Translation on user product listing.  Listings in a small set of non-English languages are automatically translated into English, allowing those sellers access to a much wider audience of buyers.  The hypothesis guiding the test is that although commercial transactions is an area where extremely high translation quality is traditionally required, the Machine Translation can provide enough understanding that users feel confident to complete the transaction.