Ethics in Machine Translation [Podcast]

Ethics in Machine Translation [Podcast]

Reading Time: 1 minute We’re in a localization and globalization market now where more words are translated every day through machine translation than what was translated in the entire human language corpus in the past. Not only does such a massive amount of machine translation radically change the role of human translators, it also creates a whole new range of …

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MT Isn’t Good For Languages, But..

MT Isn’t Good For Languages, But..

Reading Time: 3 minutes In a Sci-Fi movie we all know, there is the machine invention merging in to fulfill a certain demand and a great need covering all the routine and dangerous work. But, there is this end; that we all know by heart as well, the machine evolves and revolts against the maker and works for the …

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Six Challenges for Neural Machine Translation

Six Challenges for Neural Machine Translation

Reading Time: 1 minute Abstract We explore six challenges for neural machine translation: domain mismatch, amount of training data, rare words, long sentences, word alignment, and beam search. We show both deficiencies and improvements over the quality of phrase-based statistical machine translation. See the paper from here

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Quantisation of Neural Machine Translation models

Quantisation of Neural Machine Translation models

Reading Time: 1 minute When large amounts of training data are available, the quality of Neural MT engines increases with the size of the model. However, larger models imply decoding with more parameters, which makes the engine slower at test time. Improving the trade-off between model compactness and translation quality is an active research topic. One of the ways …

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Issue #55 – Word Alignment from Neural Machine Translation

Issue #55 – Word Alignment from Neural Machine Translation

Reading Time: 1 minute Word alignments were the cornerstone of all previous approaches to statistical MT. You take your parallel corpus, align the words, and build from there. In Neural MT however, word alignment is no longer needed as an input of the system. That being said, research is coming back around to the idea that it remains useful in …

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Evaluating machine translation in a low-resource language combination

Evaluating machine translation in a low-resource language combination

Reading Time: 1 minute Aim • Main aim: • Determining which type of MT system (RBMT, PBMT or NMT) is perceived as more adequate in the context of a minoritized language such as Galician in a MT+PE workflow. 3 • Specific aims: • BLEU automatic evaluation. • Human evaluation (quality perception survey conducted among experienced professional posteditors) • Error …

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Hungarian translators’ perceptions of neural machine translation in the European Commission

Hungarian translators’ perceptions of neural machine translation in the European Commission

Reading Time: 1 minute In the framework of its investigative mandate, the Office collects information of investigative interest, including personal data, from various sources – public authorities, private entities and natural persons – and exchanges it with Union institutions, bodies, offices and agencies, with competent authorities of Member States and third countries, as well as with international organisations before, …

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