The machine translation era is coming quickly and the signs are that the process is evolving at a much faster pace than has ever been predicted. The main players are Google, Language Weaver, Microsoft, Prompt, and Systran. The hot topic for debate is who is currently delivering the most accurate translations across the range of texts likely suitable for the process.

Actually, that topic in the overall scheme of things is irrelevant. The fact is that the technology is evolving and will continue to evolve at an ever increasing speed. The end result of this is that within the very foreseeable future, machine translation is going to be a fact of life and a very useful tool.

In a much shorter time than many people expect, localization buyers will be demanding that their costs and timelines be reduced through the implementation of MT technology.

 
There are the obvious applications for machine translation such as
large websites with volumes of information that need to be disseminated to a much wider international readership
time-critical press releases which need fast turnaround and distribution
chat rooms and forums with participants speaking different languages
 
In order to get the best possible use for MT output, there are several possible methods:
large websites with volumes of information that need to be disseminated to a much
wider international readership
time-critical press releases which need fast turnaround and distribution
chat rooms and forums with participants speaking different languages

Of the above processes, only the first one does not require a talented linguist. The cost of each option is, of course, in line with the desired outcome, but no matter how it is approached, the aim is that it will be faster and cheaper than conventional localization processes.
 
 

MT will generate its own market in many ways that have not even been thoroughly explored yet. There is a rapidly expanding amount of technical knowledge, research data, legal case documents, and patent documents that are being posted online or otherwise made available to businesses with the specific interests.

Access to this huge amount of information is currently limited because of the specific languages in which the information is recorded. Such texts, if made searchable in English (and other languages as well), will open all the data up for the use and benefit of many more people. To have all of these fully translated in the normal way just to allow the searches to be
conducted is not only impractical, but out of the question on a cost and time basis.

Machine translation offers a practical opportunity to have such materials basically translated so that they can be stored in a searchable system. When relevant data is isolated, only those specific documents can then be given over to the full human translation and checking process, thus saving a great amount of time and cost.

Technical documentation is also a candidate for MT where domain-specific memories can be created. Since technical specs have specialized terminologies, domain databases can be constructed to narrowly apply to company or subject-specific projects.

   
 
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