Astro – Subtitle Processes AutomationVideo Case Study
Presented by Alphie Larrieu, SAVP Content and Localization Engineering, Products and Technology Division, Astro.
iflix – Seamless Workflow for Subtitling
LexisNexis Univentio – Enabling Unprecedented Insight in Intellectual Property
SAJAN – Multinational IT Company Technical Documentation
One of Sajan’s many clients is a large multinational corporation that operates in nearly every country globally with a wide range of IT products ranging from database software to computer hardware. Sajan’s client had many millions of words that needed to be translated into Simplified Chinese across these products.
As this was Sajan’s first project with Omniscien Technologies’ (formerly Asia Online) Language Studio, a small amount of work was performed by Sajan’s technical team to integrate Sajan’s Global Communication Management System (GCMS). This ensured a seamless workflow for project team members such as project managers and post-editors, as well as Sajan’s customers. XLIFF files were transmitted between the Sajan GCMS and Language Studio via the Language Studio API. As this is an industry-standard format, Sajan was able to develop their connector and have it production ready in a very short time. For more information, see the Sajan GCMS Architecture at the end of this case study.
OmniLingua – Automotive Manuals
One of the major challenges that enterprises have in the use of increased automation in business translation, is understanding the productivity and quality impact of any new automation strategy. As the discussion of quality and even productivity in the industry is often quite often vague and ill-defined, it is useful to show an example where a company understands with great precision what the impact is before and after the use of new translation production technology.
The key questions that one needs to understand are:
- What is my current productivity (time taken, words produced) to achieve a defined quality level?
- What impact does new automation e.g. an MT system, have on my existing productivity and final delivered quality?
IOLAR – German-Slovenian Technical Engineering
IOLAR was interested to build a custom machine translation engine to translate technical engineering content from German to Slovenian. This language pair has a relatively complex source language combined with a very difficult target language that, like other Slavic languages, has a large number of inflected forms.
While translator productivity was important, the primary objectives were to ensure a high level of writing-style consistency and terminological accuracy. As there was no specific and directly related translation memory available to train the system, several hundred thousand segments were gathered from several sources, in a much broader domain than technical engineering. This data was combined to form a single corpus that was used to train the engine.