|
|
|
Machine translation is more relevant than ever, especially
in a global economy with many different languages.
For instance, the European Union has 23 official languages.
What will happen to languages such as Dutch? Will it survive as
a language of commerce, or will it be abandoned in favour
of English? By lowering translation costs, we would hope
to sustain the viability of different languages in a globalized
world. Statistical machine translation holds the promise of instant machine translation. Given open source tools such the Moses decoder, just add a parallel corpus and you have a machine translation system. This talk will present some problems where the standard phrase-based approach fails, and where attention to the specifics of the languages involved is required. I will present methods that deal with different word order, morphology and agglutinative compounding. |