There are 132 posts filed in Language Technology (this is page 2 of 11).
With news this week that Google has improved some of the key linguistic functionalities of its search engine’s machine learning algorithms – including an AI spell check improvement that Google’s head of search considers more important by itself than the previous five years’ progress – it is an interesting moment in the brief history of […]
As governmental bodies determine their responses to the coronavirus pandemic, technology is reaching across nations to aid these efforts in a wide range of capacities, from supporting NGO communications to coordinating vaccine development efforts. In these times, information regularly crosses linguistic boundaries with the utmost urgency, and in response people all over the world have […]
All employees go through some sort of training in their first days at a new job or company. In our global and increasingly contactless business culture, training protocol is now adapting to keep pace with the rise of remote employment, driving the development of technologies that can facilitate training through digital media and eLearning (electronic […]
Single source publishing is a content management concept that allows you to save time by storing all content in one master source file. Instead of creating content for every output you want to publish, you can easily generate it all from the master source file.
At this point, there is no real question as to whether or not Earth’s language diversity is dwindling, as it already clearly is. But there is a question as to how much of this phenomenon is due to increasingly powerful machine translation (MT) tools such as neural machine translation (NMT) versus how much is due to natural processes.
Pop culture references have always evaded dictionaries for some time after their initial adoption, and now due to the voracity and speed at which the internet consumes and discards new slang and references, machines can’t quite keep up. Ayan has pointed to “odd spellings, hashtags, urban slang, dialects, hybrid words, and emoticons” as being the major hurdles for NMT.
