On Fri, 30 Jul 2010 23:22:00 +0200, Nikola Smolenski wrote:
Дана Thursday 29 July 2010 10:38:20 Samuel Klein
написа:
There is definitely a "free TM" project
waiting to happen. It would be
nice to see translatewiki [for instance] incorporate such a tool, but
it may be a nontrivial amount of work.
At Project Rastko for years now there is the idea of building something
called Global Translation Project, where volunteers could
collaboratively translate texts in a manner somewhat similar to
Distributed Proofreaders.
To give some detail: the idea is to first parse the original text with a
rule-based machine translation engine (of course this should be free
software with free dictionary).
Hi. I'm a contributor to Apertium (
http://apertium.org), a Free Software
RBMT system which... is exactly what you describe.
The basic problem that these engines
have is that they are unable to resolve ambiguities in the text (a
classic example is sentence "Time flies like an arrow": does it means
that time is flying as fast as an arrow or that there exist some insects
called time flies (like there are fruit flies) which like some arrow?).
This often ends in a mistranslation.
The crux of the idea is that it would be humans who resolve ambiguities
in this step. For example, these two possible meanings of the sentence
would in another language be translated to two completely different
sentences. A human could then simply pick the correct one. After several
people have done this for several independent languages, and their
translations agree, the system would know what is the correct parsing of
the original text. Then this parsing could be translated fully
automatically to a large number of languages, and it will be highly
likely that the translations will be close to correct.
Apertium has a sister project, Tradubi (
http://tradubi.com), which is
developing exactly this.
An offshoot of this is a crowdsourced dictionary
project in GalaxyZoo
style. Instead of doing battle with Wiktionary's or similar interface,
volunteers could build a dictionary by solving various simple tasks
(say, pick a word's gender, or verify that a word is correctly
declined); if the supermajority of the volunteers gives the same answer,
the word enters the dictionary.