TechGist05

This is a guest post by David Snider, Globalization Architect at LinkedIn - Reprinted here with permission. I thought the article was interesting because it points out that MT quality is now quite adequate for several types of Enterprise applications, even though MT might very well be a force that influences and causes the "crapification" (a word I wish I had invented) of  overall language quality. While this might seem like horror to some, for a lot of business content that has a very short shelf life, and value only if the information is current, this MT quality is sufficient for most of the people who have in interest in the specific content. While David thinks that the language quality will improve, I doubt very much if much of this MT content will improve much beyond what is possible by the raw technology itself. Business content that has value for a short time and then is forgotten simply cannot justify the effort to raise it the level of "proper" written mat...

This is the second part of an interview with Jean Senellart (JAS) , Global CTO and SYSTRAN SAS Director General. The first part can be found here: A Deep Dive into SYSTRAN’s Neural Machine Translation (NMT) Technology . Those translators who accuse MT vendors of stealing or undermining their jobs should take note that SYSTRAN is the largest independent MT vendor. A position it has held for most of its existence, but has never generated more than €20 million in annual revenue. Which to me suggests that MT is mostly being used for different kinds of  translation tasks and is hardly taking any jobs away. The problem has been much more related to unscrupulous or incompetent LSPs who used MT improperly in rate negotiations. MT is hugely successful for those companies who find other ways to monetize the technology, as I pointed out in  The Larger Context Translation Market .This does suggest that MT has huge value in enabling global communication and commerce, and even in its les...

One of the wonderful things about my current independent status is the ability to engage deeply with other MT experts who were previously off limits because competing MT vendors don't usually chat with open hearts and open cloaks. MT is tough to do well and I think the heavy lifting should be left to people who are committed for the long run, and who are willing to play, invest and experiment in spite of regular failure. This is how humans who endure and persist, learn and solve complex problems. This is Part 1 of a two-part post on the SYSTRAN NMT product announcement. The second part will focus on comparing NMT with RBMT and SMT and also with the latest Adaptive MT initiatives. It can be found here: Comparing Neural MT, SMT and RBMT – The SYSTRAN Perspective Press releases are so filled with marketing-speak as to be completely useless to most of us. They have a lot of words but after you read them you realize you really don't know much more than you got from the headline. S...

This is an important subject and one that needs ongoing examination and continuing study to get to real insight and find greater process efficiency. I hope that this post by Silvio Picinini will trigger further discussion and I also invite others who have information, and opinions to share on this subject, to step forward. In my observation of MT output over time, I have seen that MT produces a greater number of actual errors, but the types of errors most often generated by MT are easy to spot and clean up. Unlike the incorrect or inconsistent terminology and sometimes misunderstood source errors, that may often be hidden in the clear grammar and flow of a human translation.  These human errors are much harder to find, and not as easy to correct without multiple stages of review by independent reviewers.  ----- It is common to see a focus on the errors that machine translation makes. But maybe there are also strengths in MT that can benefit translators and customer...

This is a third post in a series on expert MT systems developers. Iconic fits my definition of expert much more closely (as does tayou) as they do-it-for-you rather than give you a technology platform to do-it-yourself. (DIY does not work well for those who do not really know what they are doing.) They bring deep expertise to bear on the very specific translation problem that you bring to them, and may create a unique MT solution for each customer. In the case of Iconic, the components used to build an MT solution, may also vary from customer to customer, as they assemble sub-components to address unique customer problems, which can vary by content, language and quality expectation. In general, the interaction with an expert is going to much more consultative and customer specific and less off-the-shelf. As MT is an evolving technology, it is especially useful for an expert developer to have close ties with an academic institution that is engaged in ongoing research in M...

This is a second post from the MT Language Specialist team at eBay, by Juan Martín Fernández Rowda . I have often been asked by translators about what kinds of tools are useful when working with MT. There is a lot of corpus level data analysis, preparation and editing going on around any competent MT project. While TM tools have some value, they tend to be segment focused and do not scale, there are much better tools out there to do the corpus pattern analysis, editing and the comparison work that is necessary to build the best systems. We are fortunate to have some high-value tools laid out very clearly for us here by Juan who has extensive direct experience working with large volumes of data and can provide experience-based recommendations. ---------------------------------------------------------------------------------- If you are a linguist working with Machine Translation (MT), your job will be a lot easier if you have the right tools at hand. Having a strong toolkit, and...