Abstract Machine translation is an important and challenging task that aims at automatically
translating natural language sentences from one language into another. Recently …

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

Self-attention networks have proven to be of profound value for its strength of capturing
global dependencies. In this work, we propose to model localness for self-attention …

Existing neural machine translation (NMT) models generally translate sentences in isolation,
missing the opportunity to take advantage of document-level information. In this work, we …

Abstract Recently, Self-Attention Networks (SANs) have shown its flexibility in parallel
computation and effectiveness of modeling both short-and long-term dependencies …

In this paper, we present Neural Phrase-based Machine Translation (NPMT). Our method
explicitly models the phrase structures in output sequences using Sleep-WAke Networks …

Current state-of-the-art neural machine translation (NMT) uses a deep multi-head self-
attention network with no explicit phrase information. However, prior work on statistical …

Text is one of the most common unstructured data, and usually, the most primary task in text
mining is to transfer the text into a structured representation. However, the existing text …

Neural machine translation (NMT) has gained more and more attention in recent years,
mainly due to its simplicity yet state-of-the-art performance. However, previous research has …

La presente investigación tiene por objetivo analizar el rendimiento de dos sistemas de
traducción automática neuronal (TAN)—Google Translate y DeepL—en la traducción (ES> …