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Copyright 2001
Translation Research Group
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Last updated:
April 12, 2001
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Machine Translation

Making the Decision

At first glance, post-editing may seem like a panacea. Why not use machine translation for everything and then have a human post-edit the raw output up to normal publication quality if needed? The answer is an economic one. For a source text not restricted to a sublanguage, the cost of post-editing can be very high. If the post-editor must consult both the source and target texts, the effort, and therefore the time and cost for post-editing can easily approach the cost of paying a professional translator to translated the source text from scratch without the benefit of the raw machine translation output. It is sometimes argued that raw machine translation, not matter how bad, is useful because it includes consistent use of equivalents for specialized terms. That argument does not stand up when modern translator tools are considered. Such tools include automatic lookup of the source terms in a termbase and display of the corresponding target-language terms.

In the end, the question of whether or not to use machine translation will usually be answered on the basis of economics. Another colleague, Chris Langewis, has proposed a formula to help someone decide whether to use machine translation or human translation on the basis. I have suggested to him the following slightly modified version of his formula:

factors = specs; text-prep + terminology + MT/HT + postediting + timing.

Let me explain the formula. When deciding whether to use machine translation or human translation, the specifications of the translation job should first be examined. If indicative translation is called for and a machine translation system for the language pair in question is available, then by all means try using it. If publication quality translation is specified, then consider (1) the costs of preparing the text for translation (these costs may be considerably higher for machine translation), (2) the availability of the terminology in a format that can be automatically imported by the machine translation system or translator tools that would be used or the cost of making it importable (here the MARTIF standard becomes relevant, but that is a topic for other articles), (3) the cost of the actual machine translation (MT) or human translation (HT) step proper, and (4) the cost of post-editing (which may also be a factor in human translation since human translation is often reviewed and revised by another translator, even though post-editing human and machine translation are very different skills). When the costs of the various factors have been added up, it is just a matter of comparing total costs, unless it can be shown that the same quality final product can be produced faster by one method or the other. Caution should be exercised here, since it is not fair to pit machine translation against human translators have only word processing software. The only fair comparison is between machine translation and a team of human translators equipped with modern translator tools, including a central termbase that makes changes to the termbase immediately available to their software tools. A machine translation process that includes substantial post-editing is not necessarily capable of producing a result faster than a well-equipped team of human translators that has access to a termbase containing the same terminology found in the lexicons of the machine translation system.

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