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 …

We introduce a Multi-modal Neural Machine Translation model in which a doubly-attentive
decoder naturally incorporates spatial visual features obtained using pre-trained …

Developing artificial learning systems that can understand and generate natural language
has been one of the long-standing goals of artificial intelligence. Recent decades have …

Text image translation (TIT) aims to translate the source texts embedded in the image to
target translations, which has a wide range of applications and thus has important research …

Translating e-commercial product descriptions, aka product-oriented machine translation
(PMT), is essential to serve e-shoppers all over the world. However, due to the domain …

Image translation is a task that translates an image containing text in the source language to
the target language. One major challenge with image translation is the modality gap …

Multimodal machine translation (MMT) aims to translate a sentence in the source language
into the target language with the context of an associated image. According to where the …

The neural machine translation model has suffered from the lack of large-scale parallel
corpora. In contrast, we humans can learn multi-lingual translations even without parallel …

Visual storytelling is an intriguing and complex task that only recently entered the research
arena. In this work, we survey relevant work to date, and conduct a thorough error analysis …

In recent years, multi-modal machine translation has attracted significant interest in both
academia and industry due to its superior performance. It takes both textual and visual …