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Communication Dans Un Congrès Année : 2017

LIUM-CVC Submissions for WMT17 Multimodal Translation Task

Résumé

This paper describes the monomodal and multimodal Neural Machine Translation systems developed by LIUM and CVC for WMT17 Shared Task on Multimodal Translation. We mainly explored two mul-timodal architectures where either global visual features or convolutional feature maps are integrated in order to benefit from visual context. Our final systems ranked first for both En→De and En→Fr language pairs according to the automatic evaluation metrics METEOR and BLEU.
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Dates et versions

hal-01742382 , version 1 (26-03-2018)

Identifiants

  • HAL Id : hal-01742382 , version 1

Citer

Ozan Caglayan, Walid Aransa, Adrien Bardet, Mercedes Garcia-Martinez, Fethi Bougares, et al.. LIUM-CVC Submissions for WMT17 Multimodal Translation Task. SECOND CONFERENCE ON MACHINE TRANSLATION, 2017, Copenhagen, Denmark. pp.432 - 439. ⟨hal-01742382⟩
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