Greater than 3 minutes, my friend!
So first of all, for the record, I don’t have any interest in LILT. I just started to use the product in a very early stage and every time they announce something new, I try to test it as well.
Recently SDL started to talk about Adaptive MT — this new technology they call “Transformational machine translation” will be part of Studio 2017. For those of you that don’t know what Adaptive MT is, test LILT. Some of you will like it, some probably won’t. In any case, I do like it.
If you’re using a CAT today and you feel comfortable to post-edit MT output, you are using “static” MT: the whole sentence is translated by an engine and that is what you start to post-edit. Your work is stored in the memory and as long as you don’t retrain the engine, you will only get suggestions from your memory. The machine does not learn anything from your corrections until you or someone else retrains the engine. What is in the memory does not blend with the MT engine when you’re using static MT. Also, as long as the work isn’t done, you don’t know what is the quality of the MT output. You just edit what you get. And if you fix an error you may bump into the same error somewhere else in the text.
With LILT that won’t happen: what you edit, is immediately stored in the MT engine; new sentences that require the same translation for the same subsegment, will get your own edit, and not the output of the engine. You will recognize what you translated before even when the MT engine is not re-trained. TM and MT are blended while you are translating. What you write now, influences the suggestion for the translation of the rest of the sentence. If you make mistakes, you will get more mistakes. If you do a good job, the job will get better: the further in the document, the more of your own work is already used as a translation suggestion. When you start using LILT you use a generic system, but the more you use the system, the more it becomes YOUR system, the more it uses your voice.
That, in a nutshell is what Adaptive MT is.
From a technical perspective it is pretty impressive: store your translation, don’t mix it with translations from others, re-use the subsegments you corrected before and fit them in the machine translation smoothly… it’s really high-tech. But the most impressive is, I think, the user experience. Creating a translation that is suggested on the fly, has more risk to get into conflict with the translation that the translator had in mind. Suggesting the pre-translation without frustrating a translator who wishes to be productive above all, is not easy. In my opinion, for those translators that can get used to this way of translating, LILT delivers. To me it feels more like translating than post-editing.
MT creates translations of unknown quality. This may be one of the main reasons why some translators don’t want to use MT. Adaptive MT is still producing unknown quality, but as the tool adapts to your own editing at runtime, you have much more control 1. on how sentences are translated and 2. on all future suggestions. (For the record: Fair Trade Translation helps translators to cope with the risk of using static MT; it can’t measure the quality of translations done in LILT. Both products however strive to give more control on the job to the translator.)
If an LSP (agency) pre-translates the files it outsources to freelance translators, usually not a lot of translators like the MT output in there, especially if the engine was not trained. Adaptive MT is probably not something LSPs are considering today. It is more something a translator can use, if he wishes and if he’s happy with this way of working. I feel much more in control of my own job with this new way of working.
But also some LSPs could benefit from this new technology: if the LSP I’m working for makes all translators work together as a team, online & in real time, I can see how an adaptive MT system might boost our productivity and the consistency of the whole team more than the existing TM systems. An LSP that just cuts big jobs in small pieces and dispatches those to individual translators that don’t work together, adaptive MT won’t help them. But maybe this new technology finally gives them a good reason to change their approach.
My feeling is that many existing tools will try to put Adaptive MT technology in their product in the next couple of years. They will have to compare their implementation to the one of the ground breaker. It will be different as their users should still recognize their tool. It will be hard to beat LILT — LILT created their solution from scratch, with Adaptive MT in the core of the product. They already tweaked their product based on feedback of loyal users. It won’t be easy for anyone to beat the new kid on the block.
Looking forward to some constructive battles.