
Work on using AI to brain activity into speech - Osiris30
https://www.sciencemag.org/news/2019/01/artificial-intelligence-turns-brain-activity-speech
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fundamental
After working on the same task ~3 years back I will say: Be skeptical about
results. Neural activity shifts over the course of days, and experiments
without long term recordings will produce results which look a _lot_ better
than what can be obtained in realistic scenarios. As the article also
mentions, there is a sizable question about the differences in signals when
vocalization is not possible. I've seen some of that data, and in my opinion
we're still a good whiles away from being able to use that data in any
practical sense.

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lvbu
Iam very interested in brain computer interfaces. It would be great if you can
share any of your work here..

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fundamental
Poster from extracting speech articulation events using local field potentials
(electrodes inserted into brain matter) [http://fundamental-
code.com/tmp/2015-neurosig.pdf](http://fundamental-
code.com/tmp/2015-neurosig.pdf)

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myth_drannon
How does it compare with what [https://www.ctrl-labs.com/](https://www.ctrl-
labs.com/) are doing? It seems that they get the intent just from having a
device attached to the arm, so is it really necessary to attach the electrodes
to the brain? Because if the person is reading silently you can still get the
signal going from the brain to the muscles in the throat/mouth, can it be just
attached to the neck?

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fundamental
Typically the end target for applications like this are for patients who have
some impairment which prevents normal vocalization which would mean that the
EMG around the throat/mouth would not be reliably available.

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AnIdiotOnTheNet
With these kinds of MMIs, I often wonder if it wouldn't be better to train the
mind to the machine instead of the other way around. What I mean is, have the
machine convert certain brain activity into phonemes or some other primitive
and allow the human mind to do what it is already pretty good at: learn to use
a tool.

Since I'm not an expert in this domain, I assume there are reasons this isn't
how it is done. Is anyone aware of what they are?

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fundamental
To a degree there is some learning on both sides. I don't know if I've seen it
mentioned in detail in papers that I've read, but it was a general tone at a
few confs when dealing with coarse motor functionality.

As per why the same approach is not well suited for speech, one (of many)
components is the data bandwidth you need for speech to happen at a reasonable
rate. For many applications the ML involved in the brain computer interface is
only able to extract a few bits per second. It works for applications where
the output is coarse (e.g. up/down/left/right) or where large delays are
acceptable, but it's not the best fit for speech.

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0xdeadbeefbabe
> extract a few bits per second

That's surprising. I thought it would be a lot higher than 3.3 bits for 10
fingers (probably not worth considering in this context).

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degenerate
The eeriness of the second audio clip reminds me of the first recorded voice
by Edouard-Leon Scott de Martinville:

[https://www.youtube.com/watch?v=q7Gi6j4w3DY](https://www.youtube.com/watch?v=q7Gi6j4w3DY)

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elisharobinson
Stephen hawking: AAAAHHHH you got be kidding me

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jacobtwotwo
This had me legitimately laughing out loud. Thank you ^_^

