> Today in Nature Communications, Chang and David Moses, a postdoctoral scholar in Chang’s lab at UCSF, published the results of a study demonstrating that brain activity recorded while people speak could be used to almost instantly decode what they were saying into text on a computer screen. While previous decoding work has been done offline, the key contribution in this paper is that the UCSF team was able to decode a small set of full, spoken words and phrases from brain activity in real time — a first in the field of BCI research. The researchers emphasize that their algorithm is so far only capable of recognizing a small set of words and phrases, but ongoing work aims to translate much larger vocabularies with dramatically lower error rate
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[ 3.4 ms ] story [ 12.0 ms ] thread> Today in Nature Communications, Chang and David Moses, a postdoctoral scholar in Chang’s lab at UCSF, published the results of a study demonstrating that brain activity recorded while people speak could be used to almost instantly decode what they were saying into text on a computer screen. While previous decoding work has been done offline, the key contribution in this paper is that the UCSF team was able to decode a small set of full, spoken words and phrases from brain activity in real time — a first in the field of BCI research. The researchers emphasize that their algorithm is so far only capable of recognizing a small set of words and phrases, but ongoing work aims to translate much larger vocabularies with dramatically lower error rate
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