Notice GOOGLE PIXEL EARBUDS

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GOOGLE PIXEL EARBUDS

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o 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. removed within the earbuds themselves, or once the recording has been transferred by Bluetooth to This article was originally published on The a smartphone. It is then compressed to occupy a much smaller amount of data, then conveyed over Conversation. Read the original article. WiFi, 3G or 4G to Google's speech servers. Google's servers, operating as a cloud, will accept the recording, decompress it, and use LID technology to determine whether the speech is in Chinese or in English. The speech will then be passed to an ASR system for Chinese, then to an NLP machine translator setup to map from Chinese to English. The output of this will finally be sent to TTS software for English, producing a compressed recording of the output. This is sent back in the reverse direction to be replayed through the earbuds. This might seem like a lot of stages of communication, but it takes just seconds to happen . 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. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. 3/3 Powered by TCPDF (www.tcpdf.org) [...] ation into words. By using the rules of spoken their own version of the Babel Fish, called Pixel grammar, context, probability and a pronunciation Buds. These wireless earbuds make use of Google dictionary, ASR systems fill in gaps of missing Assistant, a smart application which can speak to, information and correct mistakenly recognised understand and assist the wearer. One of the phonemes to infer a textual representation of what headline abilities is support for Google Translate the speaker said. which is said to be able to translate up to 40 different languages. Impressive technology for Natural language processing: NLP performs under US$200. machine translation from one language to another. 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. recent years. 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 g [...]..

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