Computer system transcribes words users 'speak silently'
Originally shared by Ward Plunet
Computer system transcribes words users 'speak silently'
Researchers have developed a computer interface that can transcribe words that the user verbalizes internally but does not actually speak aloud. Electrodes in the device pick up neuromuscular signals in the jaw and face that are triggered by internal verbalizations -- saying words 'in your head' -- but are undetectable to the human eye...used a neural network to find correlations between particular neuromuscular signals and particular words. Like most neural networks, the one the researchers used is arranged into layers of simple processing nodes, each of which is connected to several nodes in the layers above and below. Data are fed into the bottom layer, whose nodes process it and pass them to the next layer, whose nodes process it and pass them to the next layer, and so on. The output of the final layer yields is the result of some classification task. The basic configuration of the researchers' system includes a neural network trained to identify subvocalized words from neuromuscular signals, but it can be customized to a particular user through a process that retrains just the last two layers.
https://www.sciencedaily.com/releases/2018/04/180405133040.htm
Computer system transcribes words users 'speak silently'
Researchers have developed a computer interface that can transcribe words that the user verbalizes internally but does not actually speak aloud. Electrodes in the device pick up neuromuscular signals in the jaw and face that are triggered by internal verbalizations -- saying words 'in your head' -- but are undetectable to the human eye...used a neural network to find correlations between particular neuromuscular signals and particular words. Like most neural networks, the one the researchers used is arranged into layers of simple processing nodes, each of which is connected to several nodes in the layers above and below. Data are fed into the bottom layer, whose nodes process it and pass them to the next layer, whose nodes process it and pass them to the next layer, and so on. The output of the final layer yields is the result of some classification task. The basic configuration of the researchers' system includes a neural network trained to identify subvocalized words from neuromuscular signals, but it can be customized to a particular user through a process that retrains just the last two layers.
https://www.sciencedaily.com/releases/2018/04/180405133040.htm
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