Neural Machine Translation (NMT) is one of the most popular approaches for language translation. In this paper, we proposed to use multi-encoder NMT for English to Malay translation by using different resources as an extra information for NMT. TensorFlow is the existing toolkits that used in this research paper. By using multi-encoder NMT, we try to increase the BLEU score for a specific domain and general domain
Most Indian languages lack sufficient parallel data for Machine Translation (MT) training. In this s...
The last few years have witnessed a surge in the interest of a new machine translation paradigm: neu...
In this research article, we study the problem of employing a neural machine translation model to tr...
Title: Indonesian-English Neural Machine Translation Author: Meisyarah Dwiastuti Department: Institu...
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and ...
Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) are the state-of-the-art ...
We present an approach to neural machine translation (NMT) that supports multiple domains in a singl...
Machine Translation (MT) systems are now being improved with the use of an ongoing methodology known...
Neural Machine Translation (NMT) is a new approach to machine translation that has made great progre...
The Helsinki-NLP team participated in the AmericasNLP 2023 Shared Task with 6 submissions for all 11...
Machine Translation bridges communication barriers and eases interaction among people having differe...
Machine translation (MT) is an important sub-field of natural language processing that aims to trans...
In this paper, we propose an architecture for machine translation (MT) capable of obtaining multilin...
Previous works mostly focus on either multilingual or multi-domain aspects of neural machine transla...
Attention-based Encoder-Decoder has the effective architecture for neural machine translation (NMT),...
Most Indian languages lack sufficient parallel data for Machine Translation (MT) training. In this s...
The last few years have witnessed a surge in the interest of a new machine translation paradigm: neu...
In this research article, we study the problem of employing a neural machine translation model to tr...
Title: Indonesian-English Neural Machine Translation Author: Meisyarah Dwiastuti Department: Institu...
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and ...
Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) are the state-of-the-art ...
We present an approach to neural machine translation (NMT) that supports multiple domains in a singl...
Machine Translation (MT) systems are now being improved with the use of an ongoing methodology known...
Neural Machine Translation (NMT) is a new approach to machine translation that has made great progre...
The Helsinki-NLP team participated in the AmericasNLP 2023 Shared Task with 6 submissions for all 11...
Machine Translation bridges communication barriers and eases interaction among people having differe...
Machine translation (MT) is an important sub-field of natural language processing that aims to trans...
In this paper, we propose an architecture for machine translation (MT) capable of obtaining multilin...
Previous works mostly focus on either multilingual or multi-domain aspects of neural machine transla...
Attention-based Encoder-Decoder has the effective architecture for neural machine translation (NMT),...
Most Indian languages lack sufficient parallel data for Machine Translation (MT) training. In this s...
The last few years have witnessed a surge in the interest of a new machine translation paradigm: neu...
In this research article, we study the problem of employing a neural machine translation model to tr...
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