Technology is inextricably linked to
today’s language business. Decades ago a translator may have been able to work
alone on his or her typewriter, but now vast systems are needed to manage every
aspect of language deliverables.
Here are some of the most important
language technologies and systems in use today:
Content Management Systems (CMS)
These systems help create, manage,
and publish content, particularly in larger companies. The best products today
support the creation and management of content in multiple languages.
Increasingly, CMSs must connect to other technologies, such as translation
memories and terminology databases.
Translation Memory (TM)
These systems store translations as
human translators create them. The paired source-target translations can then
be called up later for re-use when the identical or similar text appears. TMs
are standard tools in localization nowadays because they vastly increase the
efficiency and consistency of translation work, but they do not translate
automatically on their own. They are only as good as the human translations
that have been stored in them, and they only help to translate text that is the
same or similar as previously translated texts. Consequently, highly original
texts (such as marketing collateral) generally benefit little from TM.
Machine Translation (MT)
Machine translations are produced in
a fully automated way without human intervention based on software algorithms.
Because of MT’s speed and automation, it is often used to translate vast
amounts of information involving millions of words that could not possibly be
translated the traditional way. MT output can vary considerably in terms of
quality; the best quality is obtained by MT systems that have been trained
specifically for the domain and language pair required. Untrained MT systems
may often produce garbled or comical results.
There are two basic types of MT
systems:
Rule-Based
Machine Translation (RbMT)
This type of system relies on
intelligent algorithms coded into software based on grammar, syntax, and other
rules.
Statistical
Machine Translation (SMT)
These systems rely on
pattern-matching against vast amounts of reference texts to find translations
that are statistically most likely to be suitable.
Increasingly, some combination of
the two above systems is now being used (these are called “hybrid MT,” or HMT
systems).
Translation Management Systems (TMS)
TMS technologies are designed to
streamline and accelerate the translation workflow. They range from simple
portals for submitting source content to a language supplier and receiving back
the translations to enterprise-wide complex systems that automate most of the
handoffs between clients, LSPs, project managers, translators, editors,
proofreaders, quality assurance staff, reviewers, terminologists, and more. TMS
systems may or may not include built-in TM. Some systems also include
vendor management tools to make it easier to qualify translators, assign work,
and pay suppliers.
Connectivity Solutions
With a broad array of technologies
now available to help with translation, each providing an elegant “island of
efficiency”, the need to connect these various solutions together in seamless,
end-to-end networks has become more pronounced. The more the processes can be
integrated, however, the closer the “content translation lifecycle” will come
to near total automation – providing tremendous scalability, reliability, and
security. Connectivity platform products are now available to connect all types
of disparate systems – typically a CMS to a TMS or an MT Server – automating
the flow and routing of content between the various systems.
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