TechGist05

In the many discussions by different parties in the professional translation world involving machine translation, we see a great deal of conflation and confusion because most people assume that all MT is equivalent and that any MT under discussion is largely identical in all aspects. Here is a slightly modified description of what conflation is from the Wikipedia. Conflation occurs when the identities of two or more implementations, concepts, or products, sharing some characteristics of one another, seem to be a single identity — the differences appear to become lost. [1] In logic , it is the practice of treating two distinct MT variants as if they were one, which produces errors or misunderstandings as a fusion of distinct subjects tends to obscure analysis of relationships which are emphasized by contrasts. However, there are many reasons to question this “all MT is the same” assumption, as there are in fact many variants of MT, and it is useful to have some general understanding...

IOLAR a Slovenian LSP, was interested in building a custom machine translation engine to translate technical engineering content from German to Slovenian. This language combination is difficult and has a relatively complex source language (for MT) combined with a very difficult target language (for MT) that, like other Slavic languages, has a large number of inflected forms.  While translator productivity was important, the primary objectives were to ensure a high level of writing-style consistency and terminological accuracy. As there was no specific and directly related translation memory available to train the system, several hundred thousand segments were gathered from several somewhat related sources, in a much broader domain than technical engineering. This data was combined to form a single corpus that was used to train the engine.  Earlier Attempts with Moses Based on the widespread publicity around Moses and the increasing number of publicized Moses Case Studies, I...

While we have reached a point in time where many more people realize that machine translation (MT) produces the best results when it is properly customized, what customization actually means is still not well understood.  There is a significant difference between shallow customization and deep customization in terms of the impact on the MT system’s output quality. The quality of output in turn has a direct impact on the potential business leverage and return on investment. There are a growing number of MT vendors, but very few real MT developers in the market today, and deep expertise is the key differentiator that leads directly to better output and better productivity. It is important for anyone considering purchasing an MT solution to understand the difference between the two types of vendors . Generally, MT developers have created either Rules Based Machine Translation (RBMT) or Statistical Machine Translation (SMT) systems with hands-on coding at the deepest levels of the co...

As the use of machine translation gathers momentum in the professional translation world, it is interesting to see that much of the essential economic rationale for effective deployment of this technology is still somewhat muddy and unclear. MT use on it's own does not guarantee ROI. The MT system has to produce output that actually improves the production process to generate meaningful ROI.   Poor quality MT impacts goodwill, reputation and is also a waste of time, effort and money. There are many in the industry who continue to view machine translation (MT ) with the same “project-oriented mentality” that is common with traditional translation work that sometimes involves the production use of translation memory (TM ).  However, MT is fundamentally different, and I think it requires a different mindset in design and technology deployment to maximize economic benefits. TM is often used as a way to reduce costs and often MT is seen as a new way to lower costs without any real ...