This report began life in October 2020 at the start of the Language In The Human-Machine
Era network (lithme. eu). Several online co-writing workshops followed, working together in …

Background It is increasingly essential for translators to possess a high level of
technological proficiency to succeed in their work, as technology is becoming an integral …

While various neural machine translation (NMT) methods have integrated multiple prior
knowledge to guide the translation, no research is available on combining with source-target …

Multi-head self-attention recently attracts enormous interest owing to its specialized
functions, significant parallelizable computation, and flexible extensibility. However, very …

Prior work has proved that pivot-based method can boost the performance of neural
machine translation (NMT). However, in low-resource scenarios, the efficient of pivot-based …

To study the impact of the appeal of green advertisements on consumers' consumption
intention, this paper first studies low-resource language machine translation based on …

While various neural machine translation (NMT) methods have integrated mono-lingual
syntax knowledge into the linguistic representation of sequence-to-sequence, no research is …

Abstract Language understanding has been a topic of study that has drawn attention from a
variety of disciplines like linguistics, formal semantics, computer science, and psychology …

Abstract Machine translation has made significant progress in automating the conversion of
human languages using computational methods. However, achieving human-level …

Abstract The English-Chinese machine translation system is a current research topic. This
paper designs an English-Chinese comparison system based on Lagrangian search …