Abstract Machine translation (MT) is a technique that leverages computers to translate
human languages automatically. Nowadays, neural machine translation (NMT) which …

Deep vision multimodal learning aims at combining deep visual representation learning with
other modalities, such as text, sound, and data collected from other sensors. With the fast …

This paper discusses neural machine translation (NMT), a new paradigm in the MT field,
comparing the quality of NMT systems with statistical MT by describing three studies using …

Abstract Multimodal Machine Translation (MMT) aims to introduce information from other
modality, generally static images, to improve the translation quality. Previous works propose …

Multi-modal neural machine translation (NMT) aims to translate source sentences into a
target language paired with images. However, dominant multi-modal NMT models do not …

Abstract Interest in Artificial Intelligence (AI) and its applications has seen unprecedented
growth in the last few years. This success can be partly attributed to the advancements made …

Vision-and-language pre-training has achieved impressive success in learning multimodal
representations between vision and language. To generalize this success to non-English …

Though visual information has been introduced for enhancing neural machine translation
(NMT), its effectiveness strongly relies on the availability of large amounts of bilingual …

We introduce multi-modal, attention-based neural machine translation (NMT) models which
incorporate visual features into different parts of both the encoder and the decoder. We …

Multimodal machine translation (MMT), which mainly focuses on enhancing text-only
translation with visual features, has attracted considerable attention from both computer …