SMT and Hybrid systems of the QTLeap project in the WMT16 IT-task

By R. Gaudio, Gorka Labaka, Eneko Agirre, P. Osenova, K. Simov, Martin Popel, Dieke Oele, Gertjan van Noord, Luís Manuel dos Santos Gomes, J. Rodrigues and 5 more. 2016

5 citations recorded by the source corpus.

This paper presents the description of 12 systems submitted to the WMT16 IT-task, covering six different languages, namely Basque, Bulgarian, Dutch, Czech, Portuguese and Spanish. All these systems were developed under the scope of the QTLeap project, presenting a common strategy. For each language two different systems were submitted, namely a phrasebased MT system built using Moses, and a system exploiting deep language engineering approaches, that in all the languages but Bulgarian was implemented using TectoMT. For 4 of the 6 languages, the TectoMT-based system performs better than the Moses-based one.

Subfields: Artificial Intelligence, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Natural Language Processing

Citations in the corpus

Findings of the 2016 Conference on Machine Translation (2016, background): “Gaudio et al. (2016) describe the remaining QTL-* systems (partners 10http://metashare.metanet4u.eu/go2/ qtleapcorpus from the QTLeap project: HF&FCUL for Portuguese, UPV/EHU for Spanish and Basque, IICT-BAS for Bulgarian, CUNI for Czech and UG for Dutch).”
Dictionary-based Domain Adaptation of MT Systems without Retraining (2016, methodology): “We use two systems, Moses (Koehn et al., 2007) and TectoMT ( ˇZabokrtsk´y et al., 2008), as well as their combination Chimera (Bojar et al., 2013); see also a more detailed description of the Moses and TectoMT systems within the QTLeap project by Gaudio et al. (2016) in these proceedings.”