More companies want multilingual content produced cheaply and quickly by Language Service Providers (LSPs); Machine Translation is becoming a more popular choice as a result.
TechNavio predicted that the market for Machine Translation will grow at a compound annual growth rate (CAGR) of 18.05% until 2016, and the report attributes a large part of this rise to “the rapidly increasing content volume”. Of course, while Machine Translation may help to cut costs and turnaround times, its success is ultimately judged on whether it can not only produce correct translations-but also content that meets the quality standards of each individual client.
This places the spotlight firmly on the post-editing stage of the Machine Translation process. In this post, we are going to examine the Machine Translation post-editing stage and discuss how automatic post-editing can be incorporated into it.
What is Machine Translation post-editing?
Jeff Allen says the purpose of the post-editing stage, or more specifically the post-editor, is to “edit, modify, and/or correct pre-translated text that has been processed by an MT system from a source language into (a) target language(s)”. The most important thing to take from this is that post-editing is not the same as translation.
The fundamental aim of the post-editing process is to make Machine Translation output understandable or stylistically appropriate (depending on client requirements). Automatic post-editing is when computer technology is used to complete parts of the post-editing process.
Does this mean some stages of the post-editing process can be completely automated?
Not exactly. Automated post-editing is not an entirely mechanised process whereby a machine parses and corrects a document without human intervention. Humans must still proofread translation output and make sure that the each client’s standards are met. However, post-editing technologies can automate a number of steps that would have previously required manual intervention and multiple edits by the post-editor.
As Bartolomé Mesa-Lao of Copenhagen Business School in Denmark says, the less edits required the better a post-editors productivity. This is one of the main reasons why, in an age where companies want multilingual user content on-demand, post-editing technologies are becoming increasingly more important to LSPs. If we take an example of using KantanMT’s post-editing technologies as part of the post-editing process, we can see how it works:
A document has been translated by a KantanMT engine but there is a word that begins with a lower case letter which should begin with a capital letter. This mistake has been repeated throughout the document several hundred times. Rather than a post-editor having to manually find and correct each occurrence of this error, KantanMT’s PEX technology can find and correct the mistake using its “find and replace” rules. This means that post-editors can save time and turn their attention to fixing more complex stylistic errors. All of this results in faster project completion times and lower costs.
In our next post, we will look at some of the best practices you can use to make sure that you keep your post-editing times to a minimum.