HYGHTRA

A Hybrid High Quality Translation System

Coordinatore	UNIVERSITY OF LEEDS    more  Organization address address: WOODHOUSE LANE city: LEEDS postcode: LS2 9JT contact info Titolo: Ms. Nome: Keri Cognome: Dunning Email: send email Telefono: +44 113 343 7690 Fax: +44 113 343 4058
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	833˙193 €
EC contributo	833˙193 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2009-IAPP
Funding Scheme	MC-IAPP
Anno di inizio	2010
Periodo (anno-mese-giorno)	2010-12-01   -   2014-11-30

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	UNIVERSITY OF LEEDS  Organization address address: WOODHOUSE LANE city: LEEDS postcode: LS2 9JT contact info Titolo: Ms. Nome: Keri Cognome: Dunning Email: send email Telefono: +44 113 343 7690 Fax: +44 113 343 4058	UK (LEEDS)	coordinator	571˙811.00
2	LINGENIO GMBH  Organization address address: KARLSRUHER STRASSE 10 city: HEIDELBERG postcode: 69126 contact info Titolo: Dr. Nome: Kurt Cognome: Eberle Email: send email Telefono: +49 6221 189827 Fax: +49 6221 619766	DE (HEIDELBERG)	participant	261˙382.00

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 Obiettivo del progetto (Objective)

'Since roughly a decade statistical machine translation (SMT) predominates in academic research. However, most commercial MT suppliers continue to offer systems based on more traditional rule-based architectures (RBMT). Difficulties with replacing the translation engines in the product set-up may explain this discrepancy in part. However, the main reasons are that RBMT makes available a whole bunch of functions which SMT does not provide, including human-readable, fully worked out 'conventional' dictionaries, and that for a number of language pairs RBMT-quality is still higher.

SMT needs huge bilingual text corpora to compute satisfactory translation models, and it is inherently weak when dealing with rare data and non-local phenomena. Its advantages are low cost and robustness. The main disadvantages of RBMT are high cost and shortcomings with respect to resolving structural and lexical ambiguities.

We propose a hybrid architecture for high quality machine translation which combines the strengths of both approaches and minimizes their weaknesses: At the core is a rule-based MT system which provides morphology, declarative grammars, semantic categories, and small dictionaries, but which avoids all expensive kinds of intellectual knowledge acquisition. Instead of manually working out large dictionaries and compiling information on disambiguation preference, we suggest a novel corpus-based bootstrapping method for automatically expanding dictionaries, and for training the analytical performance and the choice of transfer alternatives.

As bilingual corpora with good literal translations are a sparse resource, we focus in particular on exploiting comparable monolingual corpora. We locate unknown words and expressions, and then use a statistically tuned analysis component in combination with similarity assumptions to identify relations across languages. This approach should make it possible to overcome the data acquisition bottleneck of conventional SMT.'