Machine translation based on semantics
Machine translation systems could be a cost-effective alternative to human translators in a variety of situations but there are serious flaws in existing systems. Some take semantics partially into account, others tend to focus on the fluency of the translated text rather that the adequacy of the read. The EU-funded SEBAMAT project aims to provide state of the art translation that considers word senses rather than words only. The project also strives to use role labelling for identifying the semantic roles of the words in a sentence.
Call for proposal
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