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Multiword Units in Machine Translation and Translation Technology
Edited by Ruslan Mitkov, Johanna Monti, Gloria Corpas Pastor and Violeta Seretan
[Current Issues in Linguistic Theory 341] 2018
► pp. 81–100

Aligning verb + noun collocations to improve a French-Romanian FSMT system

We present several Verb + Noun collocation integration methods using linguistic information, aiming to improve the results of a French-Romanian factored statistical machine translation system (FSMT). The system uses lemmatised, tagged and sentence-aligned legal parallel corpora. Verb + Noun collocations are frequent word associations, sometimes discontinuous, related by syntactic links and with non-compositional sense (Gledhill, 2007). Our first strategy extracts collocations from monolingual corpora, using a hybrid method which combines morphosyntactic properties and frequency criteria. The second method applies a bilingual collocation dictionary to identify collocations. Both methods transform collocations into single tokens before alignment. The third method applies a specific alignment algorithm for collocations. We evaluate the influence of these collocation alignment methods on the results of the lexical alignment and of the FSMT system.
Keywords: MWE, FSMT, hybrid collocation identification, lexical alignment, MWE-aware MT systems, collocation dictionary
Article outline
  • 1.Context and motivation
  • 2.Handling MWEs for MT
  • 3.Collocation definition
  • 4.Translation problems
  • 5.The Architecture of the FSMT system and verb + noun collocation integration
  • 6.Preprocessing Verb + Noun collocations
  • 7.The MWE dictionary
  • 8.The collocation alignment algorithm
  • 9.Experiments
    • 9.1MWEs and the lexical alignment system
    • 9.2MWEs and FSMT system
    • 9.3MWE identification before aligning
  • 10.Conclusions and future work
  • Notes
  • References
Published online: 20 July 2018
DOI logo
https://doi.org/10.1075/cilt.341.04tod
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