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So... Is there a filter so it's not doing everything all the time?

Archive: https://archive.today/dNkr9

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>Commentary, video, and a publication in this week's Nature Neuroscience herald a significant advance in brain-computer interface (BCI) technology, enabling speech by decoding electrical activity in the brain's sensorimotor cortex in real-time. Researchers from UC Berkeley and UCSF employed deep learning recurrent neural network transducer models to decode neural signals in 80-millisecond intervals, generating fluent, intelligible speech tailored to each participant's pre-injury voice. Unlike earlier methods that synthesized speech only after a full sentence was completed, this system can detect and vocalize words within just three seconds. It is accomplished via a 253-electrode array chip implant on the brain. Code and the dataset to replicate the main findings of this study are available in the Chang Lab's public GitHub repository.

So... Is there a filter so it's not doing everything all the time? Archive: https://archive.today/dNkr9 From the post: >>Commentary, video, and a publication in this week's Nature Neuroscience herald a significant advance in brain-computer interface (BCI) technology, enabling speech by decoding electrical activity in the brain's sensorimotor cortex in real-time. Researchers from UC Berkeley and UCSF employed deep learning recurrent neural network transducer models to decode neural signals in 80-millisecond intervals, generating fluent, intelligible speech tailored to each participant's pre-injury voice. Unlike earlier methods that synthesized speech only after a full sentence was completed, this system can detect and vocalize words within just three seconds. It is accomplished via a 253-electrode array chip implant on the brain. Code and the dataset to replicate the main findings of this study are available in the Chang Lab's public GitHub repository.

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