Mode d'emploi GOOGLE PIXEL EARBUDS

[. . . ] Language identification (LID): this system uses machine learning to identify what language is being spoken within a couple of seconds. This is important because everything that follows is Credit: Shutterstock language specific. For language identification, phonetic characteristics alone are insufficient to distinguish languages (languages pairs like Ukrainian and Russian, Urdu and Hindi are virtually In the Hitchhiker's Guide to The Galaxy, Douglas identical in their units of sound, or "phonemes"), so Adams's seminal 1978 BBC broadcast (then book, completely new acoustic representations had to be feature film and now cultural icon), one of the many developed. [. . . ] This is not as simple as substituting nouns and So how does it work?verbs, but includes decoding the meaning of the input speech, and then re-encoding that meaning Real-time speech translation consists of a chain of as output speech in a different language - with all several distinct technologies – each of which have the nuances and complexities that make second experienced rapid degrees of improvement over languages so hard for us to learn. The chain, from input to output, goes like this: Speech synthesis or text-to-speech (TTS): almost the opposite of ASR, this synthesises natural Input conditioning: the earbuds pick up sounding speech from a string of words (or background noise and interference, effectively phonetic information). Older systems used additive 1/3 synthesis, which effectively meant joining together improve their translation models. Updating a model lots of short recordings of someone speaking is easy on their own cloud servers. It is much more different phonemes into the correct sequence. More difficult to do when installed in an earbud. modern systems use complex statistical speech models to recreate a natural sounding voice. The late Douglas Adams would surely have found the technology behind these real life translating machines amazing – which it is. But computer Putting it all together scientists and engineers will not stop here. The So now we have the five blocks of technology in the next wave of speech-enabled computing could chain, let's see how the system would work in even be inspired by another fictional device, such practice to translate between languages such as as Iron Man's smart computer, J. A. R. V. I. S (Just Chinese and English. Another Rather Very Intelligent System) from the Marvel series. This system would go way beyond Once ready to translate, the earbuds first record an translation, would be able to converse with us, utterance, using a VAD to identify when the speech understand what we are feeling and thinking, and starts and ends. Background noise can be partially anticipate our needs. [. . . ] And it is necessary – firstly, because the processor in the earbuds is not powerful enough to do translation by itself, and secondly because their memory storage is insufficient to contain the language and acoustics models. Even if a powerful enough processor with enough memory could be squeezed in to the earbuds, the complex computer processing would deplete the earbud batteries in a couple of seconds. Furthermore, companies with these kind of products (Google, iFlytek and IBM) rely on continuous improvement to correct, refine and Provided by The Conversation 2/3 APA citation: How Google's Pixel Buds earphones translate languages (2017, November 15) retrieved 9 December 2018 from https://techxplore. com/news/2017-11-google-pixel-buds-earphoneslanguages. html This document is subject to copyright. [. . . ]