Hi Mark,
What I wonder about TM is, how does it work with
languages with
different structures?
It's quite obvious TM works well for Russian, Italian, Spanish,
French, German, other languages of similar structure. I heard it also
works for Chinese, Japanese, Korean, Arabic, Farsi, Hebrew as well.
So my main questions are:
1) Can it handle languages which don't separate words in writing?
Examples are Thai, Lao, Japanese, Chinese, and a number of smaller
languages.
Yes - there are translators using Thai, Japanese and Chinese within
OmegaT - we also have people in the development team that work at least
with one of these languages.
2) Can it handle languages of all typological
classifications? So far
I have seen it works well for isolating (such as Chinese, Vietnamese)
and inflecting languages (such as Russian, Polish, Latin), but what
about polysynthetic languages (such as Inuktitut, Turkish, Georgian,
Adyghe, Abkhaz, Mohawk)? I would imagine it would be more difficult
for these languages. For example, Western Greenlandic
"Aliikusersuillammassuaanerartassagaluarpaalli." means "However, they
will say that he is a great entertainer, but..." (for other long words
like this, just look at the greenlandic wikipedia, kl.wp).
Well within OmegaT you have UTF-8 usage - so most languages are
supported, for some we might have to try out, others might require
special solutions. Basically all that is UTF-8 should not create problems.
3) Can it mass-process huge amounts of content quickly,
to be reviewed
later by humans?
No - when Talking about OmegaT wer are not talking about machine
translation, but computer assisted translation - that means a human
translator re-uses translation memories from other projects, exchanged
TMs etc. While translating the glossary entries are checked and OmegaT
shows you the matching entries in a separate window. Should sentences be
equal to former translated ones or similar, according to your settings
within the software you can have it just proposed in a separate window
or OmegaT can overwrite the sentence to be translated with the full or
partial match sentence.
One feature I would very much like to see is assemble from portions, but
this will be only at discussion after having it connected to
Wiktionaryz, that is when there is tbx support - it does not make sense
to talk about this very specific and helpful feature before.
The translation memory you are working with is only as good as you
created it. The more you work with it, the better it becomes. That's
basically it.
One thing that I also find very helpful: people that speak a language,
but are not mothertognue easily can check how a word was translated
before - which context etc. So this can help a lot during work and gives
better results. Therefore the proof reading effort by mothertognue
speakers will be less.
With proper set up segmentation rules, for example, you can go through
the born and died people of the calendar quite fast, sinche descriptions
are quite repetitive.
Please note: I am having a meeting with a group of colleagues this
week-end and next week I am at the university of Pisa to give a
presentation and a workshop - so if you write and need answers from me
directly, please note it in the subject since it could well be that I
then cannot see all posts.
Have a great week-end!
Best, Sabine
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