596 citations · 667 across the 21 of their papers we have counts for
11 papers · 2 filters
Multimodal Machine Translation through Visuals and Speech
Umut Sulubacak, Ozan Caglayan, Stig-Arne Grönroos +4
Multimodal machine translation involves drawing information from more than one modality, based on the assumption that the additional modalities will contain useful alternative view…
Transformer-based Cascaded Multimodal Speech Translation
Zixiu Wu, Ozan Caglayan, Julia Ive +2
This paper describes the cascaded multimodal speech translation systems developed by Imperial College London for the IWSLT 2019 evaluation campaign. The architecture consists of an…
Imperial College London Submission to VATEX Video Captioning Task
Ozan Caglayan, Zixiu Wu, Pranava Madhyastha +2
This paper describes the Imperial College London team's submission to the 2019' VATEX video captioning challenge, where we first explore two sequence-to-sequence models, namely a r…
Estimating post-editing effort: a study on human judgements, task-based and reference-based metrics of MT quality
Carolina Scarton, Mikel L. Forcada, Miquel Esplà-Gomis +1
Devising metrics to assess translation quality has always been at the core of machine translation (MT) research. Traditional automatic reference-based metrics, such as BLEU, have s…
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation
Zhenhao Li, Lucia Specia
Neural Machine Translation (NMT) models have been proved strong when translating clean texts, but they are very sensitive to noise in the input. Improving NMT models robustness can…
EASSE: Easier Automatic Sentence Simplification Evaluation
Fernando Alva-Manchego, Louis Martin, Carolina Scarton +1
We introduce EASSE, a Python package aiming to facilitate and standardise automatic evaluation and comparison of Sentence Simplification (SS) systems. EASSE provides a single acces…