Machine Translation Post-Editing

date:2021-08-04 

Machine translation, also known as automatic translation or AI translation, is the process of using technology and AI to convert a source language into a target language. Post-editing is the manual process of proofreading and editing machine translation to ensure that they meet certain application standards.

The history of machine translation can be traced back to the 1930s and has had a long and winding journey, but quality has continued to improve. Now that the world is rapidly developing and globalizing economically, the Internet and machine translation technology becomes ever most important in promoting political, economic, and cultural exchanges.

Machine translation is being adopted in an increasing number of applications. Its lost cost and fast turnaround can greatly reduce labor and time investments for enterprises. When the source is translated, then manual proofreading and editing can meet application needs. Many large enterprises have begun to accept machine translation + post-editing model. Many believe that as AI continues to improve, it will become more ubiquitous in its application.

We propose MTPE as an alternative for projects where it is suitable and meets the customer’s needs.

 

Typical Cases

Customer: Real estate agency in Japan

Content: Machine translation + post-editing of property information. The information contains a large portion of repeated content and agreed-upon terms, and the sentences are short, making it suitable for MTPE, which can handle a large amount of real estate information in a short amount of time as well as ensuring consistency. The client was fully satisfied.

Customer: Cross-border e-commerce merchants

Content: Machine translation + post-editing of product information on e-commerce websites. E-commerce merchants have demanding requirements for timely return of product information, and sometimes require a large amount of information be updated in a very short period of time, plus they are always open for cheaper costs, which meant that they ultimately chose the MTPE model for their projects.

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