A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Coverage for Character Based Neural Machine Translation
2017
Revista de Procesamiento de Lenguaje Natural (SEPLN)
In recent years, Neural Machine Translation (NMT) has achieved stateof-the-art performance in translating from a language; source language, to another; target language. However, many of the proposed methods use word embedding techniques to represent a sentence in the source or target language. Character embedding techniques for this task has been suggested to represent the words in a sentence better. Moreover, recent NMT models use attention mechanism where the most relevant words in a source
dblp:journals/pdln/KazimiC17
fatcat:4g3mxoxotjbfrnuoprcq2xhg3y