AIMC Topic: Translating

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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....

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...

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...

A cross-lingual approach to automatic ICD-10 coding of death certificates by exploring machine translation.

Journal of biomedical informatics
Automatic ICD-10 coding is an unresolved challenge in terms of Machine Learning tasks. Despite hospitals generating an enormous amount of clinical documents, data is considerably sparse, associated with a very skewed and unbalanced code distribution,...

Deep learning and process understanding for data-driven Earth system science.

Nature
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, ...

A Neural Machine Translation Model for Arabic Dialects That Utilises Multitask Learning (MTL).

Computational intelligence and neuroscience
In this research article, we study the problem of employing a neural machine translation model to translate Arabic dialects to modern standard Arabic. The proposed solution of the neural machine translation model is prompted by the recurrent neural n...

Is Machine Translation a Reliable Tool for Reading German Scientific Databases and Research Articles?

Journal of chemical information and modeling
A significant number of published databases and research papers exist in foreign languages and remain untranslated to date. Important sources of primary scientific information in German are Beilstein Handbuch der Organischen Chemie, Gmelin Handbuch d...

The Moral Machine experiment.

Nature
With the rapid development of artificial intelligence have come concerns about how machines will make moral decisions, and the major challenge of quantifying societal expectations about the ethical principles that should guide machine behaviour. To a...