MOLTO's goal is to develop a set of tools for translating texts between multiple languages in real time with high quality. Languages are separate modules in the tool and can be varied; prototypes covering a majority of the EU's 23 official languages will be built.
As its main technique, MOLTO uses domain-specific semantic grammars and ontology-based interlinguas. These components are implemented in GF [2] (Grammatical Framework), which is a grammar formalism where multiple languages are related by a common abstract syntax. GF [2] has been applied in several small-to-medium size domains, typically targeting up to ten languages but MOLTO will scale this up in terms of productivity and applicability.
A part of the scale-up is to increase the size of domains and the number of languages. A more substantial part is to make the technology accessible for domain experts without GF [2] expertise and minimize the effort needed for building a translator. Ideally, this can be done by just extending a lexicon and writing a set of example sentences.
The most research-intensive parts of MOLTO are the two-way interoperability between ontology standards (OWL) and GF [2] grammars, and the extension of rule-based translation by statistical methods. The OWL-GF [2] interoperability will enable multilingual natural-language-based interaction with machine-readable knowledge. The statistical methods will add robustness to the system when desired. New methods will be developed for combining GF [2] grammars with statistical translation, to the benefit of both.
MOLTO technology will be released as open-source libraries which can be plugged in to standard translation tools and web pages and thereby fit into standard workflows. It will be demonstrated in web-based demos and applied in three case studies: mathematical exercises in 15 languages, patent data in at least 3 languages, and museum object descriptions in 15 languages.
MOLTO is funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement FP7-ICT-247914
Follow MOLTO on Twitter at http://twitter.com/moltoproject [3].