How MateCat Calculates Payable Words

MateCat relies on a combination of advanced TM technology (MyMemory) and a reduction in word weighting applied for machine translation suggestions. This allows MateCat to reveal more matches than any other translation tool.

According to industry standards, words or phrases with a 100% Translation Memory match are given a weighting of 30% and words or phrases with a partial TM match are given a weighting of 60%.

Below you will find an example of how MateCat calculates weighted words:

No TM match = 100%
Machine Translation= 80-90% (varies according to the language pair)
Lower fuzzy ranges = 100%
Higher fuzzy ranges = 60%
100% match = 30%
Repetition (same segment repeated in the document) = 30%
Context match (more than 100% match, because of same context information in the TM) = 0%

For Machine Translation, MateCat decides which reduction in weighting to apply depending on the extent to which the MT has been useful for the past 1 million words for each language pair. MateCat assumes that the less the machine translation suggestion is edited by translators, the more useful it is.

We decided to split the benefits of this technology between the language service provider and the translator. So, if a translator saves 20% of their time, the word count is reduced by 10% only.

How MateCat counts payable words in a project is indicated in the Volume Analysis Report generated during creation of the project itself, which can be downloaded on the same page.

Find out more on this topic in the specific section of the FAQ.
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