Post Editing - What does it REALLY mean?

While many people may consider that all post-editing is the same, there are definitely variations that are worth a closer look. This is a guest post by Mats Dannewitz Linder that digs into three very specific PEMT scenarios that a translator might view quite differently. Mats has a more translator-specific perspective and as the author of the Trados Studio manual, I think provides a greater sensitivity to the issues that do matter to translators. 

From my perspective as a technology guy, this post is quite enlightening as it provides real substance and insight on why there have been communication difficulties between MT developers and translator editors. PEMT can be quite a range of different editor experiences as Mats describes here, and if we now factor in the change that Adaptive MT can have, we now have even more variations on the final PEMT user experience.  

I think a case can be made for both major cases of PEMT that I see from my vantage post, the batch chunk mode and the interactive TU inside the CAT mode.  Batch approaches can make it easier to do multiple corrections in a single search and replace action, but interactive CAT interfaces may be preferred by many editors who have very developed skills in a preferred CAT tool. Adaptive MT, I think, is a blend of both and thus I continue to feel that it is especially well suited for any PEMT scenario as described in this post. The kind of linguistic work done for very large data sets is quite different and focuses on correcting high-frequency word patterns in bulk data, described in this post: The Evolution in Corpus Analysis Tools. This is not PEMT as we describe here, but it is linguistic work that would be considered high value for eCommerce, customer support and service content and any kind of customer review data that has become the mainstay of MT implementations today. 

For those in the US, I wish you a Happy Thanksgiving holiday this week, and I hope that you enjoy your family time. I have pointed out previously, however, that for the indigenous people of the Americas, Thanksgiving is hardly a reason to celebrate.“Thanksgiving” has become a time of mourning for many Native People, hopefully, this changes, but it can only change when at least a few recognize the historical reality and strive to alter it in small and sincere ways.

The emphasis and images below are all my doing so please do not blame Mats for them.

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I have read – and also listened to – many articles and presentations and even dissertations on post-editing of machine translation (PEMT), and strangely, very few of them have made a clear distinction between the editing of a complete, pre-translated document and the editing of machine-translated segments during interactive translation in a CAT tool. In fact, in many of them, it seems as if the authors are primarily thinking of the latter. Furthermore, most descriptions or definitions of “post-editing” do not even seem to take into account any such distinction. All the more reason, then, to welcome the following definition in ISO 17100, Translation services – Requirements for translation services:

      post-edit

      edit and correct machine translation output

Note: This definition means that the post-editor will edit output automatically generated by a machine translation engine. It does not refer to a situation where a translator sees and uses a suggestion from a machine translation engine within a CAT (computer-aided translation) tool.

And yet… in ISO 18587, Translation services – Post-editing of machine translation output – Requirements, we are once again back in the uncertain state: the above note has been removed, and there are no clues as to whether the standard makes any difference between the two ways of producing the target text to be edited.

This may be reasonable in view of the fact that the requirements on the “post-editor” arguably are the same in both cases. Still, that does not mean that the situation and conditions for the translator are the same, nor that the client – in most cases a translation agency, or language service provider (LSP) – see them as the same. In fact, when I ask translation agencies whether they see the work done during interactive translation using MT as being post-editing, they tell me that it’s not.

But why should this matter, you may ask. And it really may not, as witness the point of view taken by the authors of ISO 18587 – that is, it may not matter to the quality of the work performed or the results achieved. But it matters a great deal to the translator doing the work. Basically, there are three possible job scenarios:

1. Scenario A:- The job consists of editing (“post-editing”) a complete document which has been machine-translated; the source document is attached. The editor (usually an experienced translator) can reasonably assess the quality of the translation and based on that make an offer. The assessment includes the time s/he believes it will take, including any necessary adaptation of the source and target texts for handling in a CAT tool.
2. Scenario B:- The job is very much like a normal translation in a CAT tool except that in addition to, or instead of, an accompanying TM the translator is assigned an MT engine by the client (normally a translation agency). Usually, a pre-analysis showing the possible MT (and TM) matches is also provided. The translator is furthermore told that the compensation will be based on a post-analysis of the edited file and depend on how much use has been made of the MT (and, as the case may be, the TM) suggestions. Still, it is not possible for the translator either to assess the time required or the final payment. Also, s/he does not know how the post-analysis is made so the final compensation will be based on trust.
3. Scenario C:- The job is completely like a normal translation in a CAT tool, and the compensation is based on the translator’s offer (word price or packet price); a TM and a customary TM matches analysis may be involved (with the common adjustment of segment prices). However, the translator can also – on his or her own accord – use MT; depending on the need for confidentiality it may be an in-house engine using only the translator’s own TMs; or it may be online engines with confidentiality guaranteed; or it may be less (but still reasonably) confidential online engines. Whatever the case, the translator stands to win some time thanks to the MT resources without having to lower his or her pricing.

In addition to this, there are differences between scenarios A and B in how the work is done. For instance, in A you can use Find & replace to make changes in all target segments; not so in B (unless you start by pre-translating the whole text using MT) – but there you may have some assistance by various other functions offered by the CAT tool and also by using Regular expressions. And if it’s a big job, it might be worthwhile, in scenario A, to create a TM based on the texts and then redo the translation using that TM plus any suitable CAT tool features (and regex).

Theoretically possibly, but practically not

There is also the difference between “full” and “light” post-editing: Briefly, the former means that the resulting text is comprehensible and accurate, but the editor need not – in fact, should not – strive for a much “better” text than that, and should use as much of the raw MT version as possible. The purpose is to produce a reasonably adequate text with relatively little effort. The latter situation means that the result should be of “human” translation quality. (Interestingly, though, there are conflicting views on this: some sources say that stylistic perfection is not expected and that clients actually do not expect the result to be comparable to “human” translation.) Of course these categories are only the end-points on a continuous scale; it is difficult to objectively test that a PEMT text fulfils the criteria of one or the other (is the light version really not above the target level? is the full version really up to the requirements?), even if such criteria are defined in ISO 18587 (and other places).

Furthermore, all jobs involving “light-edit” quality is likely to be avoided by most translators 

Source: Common Sense Advisory

These categories mainly come into play in scenario A; I don’t believe any translation agency will be asking for anything but the “full” quality in scenario B. Furthermore, all jobs involving “light” quality is likely to be avoided by most translators. Not only does it go against the grain of everything a translator finds joy in doing, i.e. the best job possible; experience also shows that all the many decisions that have to be made regarding which changes need to be made and which not often take so much time that the total effort with “light” quality editing is not much less than that with “full” quality.

Furthermore, there are some interesting research results as to the efforts involved, insights which may be of help to the would-be editor. It seems that editing medium quality MT (in all scenarios) takes more effort than editing poor ones – this is cognitively more demanding than discarding and rewriting the text. Also, the amount of effort needed to detect an error and decide how to correct it may be greater than the rewriting itself and reordering words and correcting mistranslated words takes the longest time of all. Furthermore, it seems that post-editors differ more in terms of actual PE time than in the number of edits they make. Interestingly, it also seems that translators leave more errors in TM-matched segments than in MT-matched ones. And the mistakes are of different kinds.

These facts, plus the fact that MT quality today is taking great steps forward (not least thanks to the fast development of neural MT, even taking into account the hype factor), are likely to speed up the current trend, which according to Arle Lommel, senior analyst at CSA Research and an expert in the field, can be described thus:

"A major shift right now is that post-editing is being replaced by “augmented translation.” In this view, language professionals don't correct MT, but instead, use it as a resource alongside TM and terminology. This means that buyers will increasingly just look for translation, rather than distinguishing between machine and human translation. They will just buy “translation” and the expectation will be that MT will be used if it makes sense. The MT component of this approach is already visible in tools from Lilt, SDL, and others, but we're still in the early days of this change."

In addition, this will probably mean that we can do away with the “post-editing” misnomer – editing is editing, regardless of whether the suggestion presented in the CAT tool interface comes from a TM or an MT engine. Therefore, the term “post-editing” should be reserved only for the very specific case in scenario A, otherwise, the concept will be meaningless. This view is taken in, for instance, the contributions by a post-editor educator and an experienced post-editor in the recently published book Machine Translation – What Language Professionals Need to Know (edited by Jörg Porsiel and published by BDÜ Fachverlag).

Thus it seems that eventually we will be left with mainly scenarios B and C – which leaves the matter, for translators, of how to come to grips with B. This is a new situation which is likely to take time and discussions to arrive at a solution (or solutions) palatable to everyone involved. Meanwhile, we translators should aim to make the best possible use of scenario C. MT is here and will not go away even if some people would wish it to.

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Mats Dannewitz Linder has been a freelance translator, writer and editor for the last 40 years alongside other occupations, IT standardization among others. He has degrees in computer science and languages and is currently studying national economics and political science. He is the author of the acclaimed Trados Studio Manual and for the last few years has been studying machine translation from the translator’s point of view, an endeavour which has resulted in several articles for the Swedish Association of Translators as well as an overview of Trados Studio apps/plugins for machine translation. He is self-employed at Nattskift Konsult.