Machine Translation


Microsoft adds Māori to translator as New Zealand pushes to revitalize the language – TechCrunch

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The benefits of machine translation are easy to see and experience for ourselves, but those practical applications are only one part of what makes the technology valuable. Microsoft and the government of New Zealand are demonstrating the potential of translation tech to help preserve and hopefully breathe new life into the Māori language. Te reo Māori, as it is called in full, is of course the language of New Zealand's largest indigenous community. But as is common elsewhere as well, the tongue has fallen into obscurity as generations of Māori have assimilated into the dominant culture of their colonizers. Māori people make up about 15 percent of the population, and only a quarter of them speak the language, making for a grand total of 3 percent that speak te reo Māori.


Visualisation of embedding relations (Word2Vec, BERT)

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In this story, we will visualise the word embedding vectors to understand the relations between words described by the embeddings. This story focuses on word2vec [1] and BERT [2]. To understand the embeddings, I suggest reading a different introduction (like this) as this story does not aim to describe them. This story is part of my journey to develop Neural Machine Translation (NMT) using BERT contextualised embedding vectors. Word embeddings are models to generate computer-friendly numeric vector representations for words.


DataCareer: Your Career Platform for Data Science in the UK and Ireland

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Grade: G13/3 (net (basic) monthly salary* for this vacancy: EUR 12 435,12, which may be supplemented by various allowances depending on your personal circumstances) Duration of appointment: 5 years Career path: Managerial Location: Munich Application deadline: 17.11.2019 With almost 7 000 employees, the European Patent Office (EPO) is the second-largest public service institution in Europe. It supports innovation, competitiveness and economic growth across Europe through a commitment to high-quality and efficient services delivered under the European Patent Convention, its founding treaty. It has a yearly budget of EUR 2.3 billion, entirely financed by the fees paid by its users. As set out in its Strategic Plan 2023, the EPO is proud to deliver high-quality patents and efficient services that foster innovation, competitiveness and economic growth.


Legal translation tool launching for French

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In addition to being designed particularly for the French markets of Canada, the company is trying to lure customers with enterprise-centred options such as customization, review by human translators, and cybersecurity. Kalaci says the technology, which is not affiliated with Amazon's Alexa, is hosted on Canadian servers and the text is destroyed once it is translated. There is also an option for firms to use their data to train a customised tool. Either way, he says, is an improvement over free services offered on the web. "Most web-based tools you use, have a disclosure wherein they say, 'Any content you put in here, we keep.' And that's how they keep improving their tools," says Kalaci.


Legal translation tool launching for French

#artificialintelligence

In addition to being designed particularly for the French markets of Canada, the company is trying to lure customers with enterprise-centred options such as customization, review by human translators, and cybersecurity. Kalaci says the technology, which is not affiliated with Amazon's Alexa, is hosted on Canadian servers and the text is destroyed once it is translated. There is also an option for firms to use their data to train a customised tool. Either way, he says, is an improvement over free services offered on the web. "Most web-based tools you use, have a disclosure wherein they say, 'Any content you put in here, we keep.' And that's how they keep improving their tools," says Kalaci.


Google's New AI Milestone: Neural Machine Translation Engine Can Now Translate 103 Languages

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Neural Machine Translation (NMT), one of the most important topics in deep learning, has gained much attention from the industries and academia over the last few years. In order to create simple models out of the complex ones, tech giant Google has been doing a lot of innovations in the domain of human to machine and machine to human translations for quite a few years now. Back in 2017, the tech giant introduced a solution to use a simple Neural Machine Translation (NMT) model to translate between multiple languages where the researchers merged 12 language pairs into a single model. Models into three types which are many-to-one, one-to-many and many-to-many models. Recently, the researchers at Google AI Team built a more enhanced system for neural machine translation (NMT) and published a paper known as "Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges".


Machine Learning for Translation: What's the State of the Language Art? - ReadWrite

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A new batch of Machine Translation tools driven by Artificial Intelligence is already translating tens of millions of messages per day. Proprietary ML translation solutions from Google, Microsoft, and Amazon are in daily use. Facebook takes its road with open-source approaches. What works best for translating software, documentation, and natural language content? And where is the automation of AI-driven neural networks driving?


Machine Learning for Translation: What's the State of the Language Art? - ReadWrite

#artificialintelligence

A new batch of Machine Translation tools driven by Artificial Intelligence is already translating tens of millions of messages per day. Proprietary ML translation solutions from Google, Microsoft, and Amazon are in daily use. Facebook takes its road with open-source approaches. What works best for translating software, documentation, and natural language content? And where is the automation of AI-driven neural networks driving?


Deciphering The Limitations Of Machine Learning Translations

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Machine learning is offering businesses a new opportunity to translate documents. They can use machine learning to translate marketing materials and other literature. However, these AI solutions may not always be the best. Towards Data Science has discussed this development. The term is called neural machine translation.


Machine Learning is Fun Part 5: Language Translation with Deep Learning and the Magic of Sequences

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So how do we program a computer to translate human language? The simplest approach is to replace every word in a sentence with the translated word in the target language. This is easy to implement because all you need is a dictionary to look up each word's translation. But the results are bad because it ignores grammar and context. So the next thing you might do is start adding language-specific rules to improve the results.