Can the web community help improve machine translation?
I am not a linguist. I think this is an interesting idea but the problem is that translation is more than simple substitution. The rules of natural languages are numerous, complex, and inconsistent. The contributors would be limited to those who know two languages and understand how to specify rules in whatever system you to specify grammar. On the other hand, it seems your idea would be good for building multi-lingual dictionaries.
They’ve thought of that. The relevant chapter from a book on machine translation. In general, there are two approaches one can take to the treatment of idioms. The first is to try to represent them as single units in the monolingual dictionaries. What this means is that one will have lexical entries such as kick_the_bucket. One might try to construct special morphological rules to produce these representations before performing any syntactic analysis — this would amount to treating idioms as a special kind of word, which just happens to have spaces in it. As will become clear, this is not a workable solution in general.And so on… the whole book is pretty interesting. OTOH, I can see how there would be some potential to distributing this kind of work. If there are 100 variations of a particular idiom, a researcher might assume that’s impossible to deal with over the whole language. Too much effort. But you
I’ve been noticing that this guy (a VC) has some interest in machine translation on the web for the purpose of improving communication between the west and the arab world (and if he can find a way to build a business around it, all the better, I’m sure). You might browse his posts on the subject and see if there is anything relevant, you might also ping him with your idea and see if he knows anything or anyone. I don’t think its as simple as goodnewsfortheinsane makes it out to be either, but tapping the web for collaborative training of machine translation could be interesting and wouldn’t require teaching the participants a system for specifying grammar. Rather than building dictionaries or ann
Any idiot could knock together a one word => one word machine translator in half a day, so I think they’re a bit more complicated than you give them credit for. They have proper linguists working on this and I’m sure they’ve though of everything obvious. The other thing is that the public being able to tell the system what the correct answer was won’t really help evolve the algorithm. It might know what to do it if sees the exact same phrase again, but it won’t know what other circumstances it needs to make the same correction, if any, and how to recognise them. Defining the scope of when to apply a certain linguistic rule is the hard part, and that’s probably what MT designers spend their time hand-optimizing. I don’t think throwing numbers will help this problem – any useful data will be lost in the noise of everyone’s suggestions.
