Neural machine translation is a modern technique that has been developed thanks to the use of artificial intelligence (AI) in the field of translation. The neural translator, an advanced AI system, uses machine learning techniques to constantly improve its translation capacity in different languages.
This type of translation differs from conventional statistical translation, since the neural translation model uses artificial neural networks to process and understand language, rather than simply comparing patterns and word frequencies.
Since its inception, neural translation has led to more accurate translations, as the system learns automatically from large datasets of previously translated texts, which improves its ability to identify patterns and understand the appropriate context for each word or phrase. In addition, neural machine translation allows large volumes of text to be translated faster and more efficiently, which can be very useful in professional environments that require real-time translations.
In this article we explain in detail what neural translation is and how we can take advantage of the features of neural machine translation as a support for traditional translations.
The challenges of neural machine translation
To understand neural machine translation, you need to start from the beginning: traditional machine translation. The ambiguity and variation which are inherent to human language make Machine Translation (MT) an extremely challenging task. Anyone who has ever translated a text will know that the correct translation of a given word or expression can rarely be predicted by simply consulting a dictionary. Translation choices are governed by a wide variety of factors which include not only the context of the original text, conventions in the target language which may be specific to the type of text or its genre, but also extra-linguistic factors, such as the target audience, the purpose of the translation, etc. Given the complexity of the task, until recently, even the best MT technology could not begin to compare with the quality of human translation.
What is neural machine translation?
Neural translation is an artificial intelligence discipline that is based on natural language processing (NLP) technology to produce efficient and accurate translations between languages. This technology is based on the use of deep neural networks to model language at a syntactical and semantic level.
Neural translation, a translation AI has been developed that uses a computational approach that encompasses understanding the context, identifying patterns and converting words. The main goal of neural translation is to improve the accuracy, efficiency and overall quality of translations.
Function of neural translation systems
Neural translation systems combine two different approaches, one based on existing data records and the other based on the principles of machine learning. These two approaches allow the system to understand the full meaning of the text and achieve a more accurate translation. This technology also uses algorithms to detect common translation failures, such as grammar errors and lack of consistency, as well as to improve the overall quality of the resulting text.
Neural translation offers much better results than other available translation systems. This is because the models used to build the system are much more advanced than the other systems, which allows the results to be much more accurate. In addition, because the system is able to understand the context and detect complex patterns, it is also able to offer much faster results. These characteristics make neural translation a very useful tool for those interested in obtaining more reliable results when carrying out their own translations.
The new approach to neural machine translation
A new approach called neural machine translation (MT) has emerged in recent years that may be able to achieve near-human-quality translation. Neural machine translation takes advantage of a new generation of machine learning systems called deep neural networks. These systems use complex internal representations to learn to perform tasks by extracting regularities from data.
In the case of translation, the data consists of large amounts of both original and translated texts, and the task at hand is to predict the translation based on the original sentence. Interestingly, the translation process in neural systems is similar to the human translation process. The original sentence is first processed and then transformed into a language-independent representation as learnt by the system during training. From this representation the translated sentence is then generated taking into account not only the content of the original, but also the regularities and conventions of the target language.
MT (Machine Translation) in ATLS
At ATLS we are working to provide the best neural machine translation (MT) solutions for our clients. Neural networks present some key advantages when compared to previous approaches to machine translation. As opposed to the previous generation of MT systems that proceed word by word or phrase by phrase, neural MT takes the context provided by the entire sentence into account when translating each of the source words. Furthermore, the abstract intermediate representation of the words allows the system to generalise and correctly translate combinations of words that it has not seen before. Finally, if it is trained with data from an area of expertise, a neural MT system can learn domain-specific behaviour for that area, reflecting the subtleties of language use that would otherwise be impossible to capture.
ATLS cuenta con más de 20 años de experiencia en servicios de traducción automática (TA). As a result, the company possesses rich bilingual dictionaries, linguistic information and domain-specific translation data. We combine the latest developments in data-driven MT technology with these invaluable resources, allowing neural MT to work in practice providing the best possible translation solutions which are customised for the needs of the client. Come and have a look at our website and discover our translation services!
Head of the MT department
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