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Analysis of Chinese Machine Translation Training Based on Deep Learning Technology.

Computational intelligence and neuroscience
With the advent of the information age, people can establish good communication through Internet technology. Mechanical translation has become a key means to solve people's communication problems. However, there are still obstacles to communication b...

Semantic Analysis Technology of English Translation Based on Deep Neural Network.

Computational intelligence and neuroscience
English translation plays an important role in the development of science and technology and cultural exchanges. With the increase in translation volume, intelligent translation has become inevitable, but there is no effective solution for semantic t...

Unreferenced English articles' translation quality-oriented automatic evaluation technology using sparse autoencoder under the background of deep learning.

PloS one
Currently, both manual and automatic evaluation technology can evaluate the translation quality of unreferenced English articles, playing a particular role in detecting translation results. Still, their deficiency is the lack of a close or noticeable...

Heavyweight Statistical Alignment to Guide Neural Translation.

Computational intelligence and neuroscience
Transformer neural models with multihead attentions outperform all existing translation models. Nevertheless, some features of traditional statistical models, such as prior alignment between source and target words, prove useful in training the state...

Machine Translation System Using Deep Learning for English to Urdu.

Computational intelligence and neuroscience
Machine translation is an ongoing field of research from the last decades. The main aim of machine translation is to remove the language barrier. Earlier research in this field started with the direct word-to-word replacement of source language by th...

ParaMed: a parallel corpus for English-Chinese translation in the biomedical domain.

BMC medical informatics and decision making
BACKGROUND: Biomedical language translation requires multi-lingual fluency as well as relevant domain knowledge. Such requirements make it challenging to train qualified translators and costly to generate high-quality translations. Machine translatio...

Automatic Detection of Grammatical Errors in English Verbs Based on RNN Algorithm: Auxiliary Objectives for Neural Error Detection Models.

Computational intelligence and neuroscience
With the rapid development of neural network technology, we have widely used this technology in various fields. In the field of language translation, the research on automatic detection technology of English verb grammatical errors is in a hot stage....

Pseudotext Injection and Advance Filtering of Low-Resource Corpus for Neural Machine Translation.

Computational intelligence and neuroscience
Scaling natural language processing (NLP) to low-resourced languages to improve machine translation (MT) performance remains enigmatic. This research contributes to the domain on a low-resource English-Twi translation based on filtered synthetic-para...

Mixed-Level Neural Machine Translation.

Computational intelligence and neuroscience
Building the first Russian-Vietnamese neural machine translation system, we faced the problem of choosing a translation unit system on which source and target embeddings are based. Available homogeneous translation unit systems with the same translat...

Neural machine translation of clinical texts between long distance languages.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To analyze techniques for machine translation of electronic health records (EHRs) between long distance languages, using Basque and Spanish as a reference. We studied distinct configurations of neural machine translation systems and used d...