What is Speech to Speech Translation?


No longer in the realm of science fiction, the concept of a real-time universal translator is currently in the works as pioneering companies such as Google and Facebook are acquiring and developing technologies that support speech recognition, language translation, and speech synthesis. In 2006, an advancement that led to the development and use of layered models of inputs, termed deep neural networks (DNN), brought speech recognition to its highest level of accuracy yet, clearing the way for speech-to-speech translation. As a result, today’s consumers are habitually interacting with voice-activated virtual assistants on their mobile phones and even in their vehicles with greater ease and comfort. Researchers are now applying DNN to automatic translation engines in efforts to increase the semantic accuracy of interpreting the world’s languages, and Microsoft engineers have already demo-ed software that can synthesize an individual’s own voice in another language, from English to Mandarin. Progress in machine learning technologies is bringing the universal translator closer to the consumer’s hand, and is poised to transform communication and collaboration at the global level.

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1) How might this technology be relevant to the educational sector you know best?

Repeating what I said in last year's discussions: This technology will broaden the opportunites and possibilities in globalized teaching and learning - it will democratize studies and make it possible for students to work across boarders. Also joint degrees will benefit from the initiative. Most important for the future HE. - ole ole Aug 10, 2016 It will also create opportunities for language teachers and companies who are able to develop AI good enough to decode more sophisticated language features such as metaphors and irony. - paulo.dantas paulo.dantas Sep 16, 2016
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(2) What themes are missing from the above description that you think are important?

  • Literal translations are not always effective in communicating what is actually meant, and fail spectacularly when idioms, non-standard phrases or regional colloquialisms are used e.g. "many a mickle makes a muckle" is a local Yorkshire phrase that would simply stump anyone from outside the region (and quite a few from inside the region!), let alone translation tools developed anywhere but right on our doorstep. Regional accents seem to confound such softwares too. And as for context, often delivered by tone of voice, facial cues or gestures, forgedaboudit... - damian.mcdonald damian.mcdonald Sep 22, 2016 Of course you're right, but things develop and so does SST. Anyway, there are many fields in which the technology will be very useful. Furthermore, there are teachers in the non-Anglosaxon countries who have severe language issues, and here SST can make a difference - in spite of the suprasegmental features that the technology doesn't catch. - ole ole Oct 3, 2016.

(3) What do you see as the potential impact of this technology on higher education?

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(4) Do you have or know of a project working in this area?


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