Inspiration
There is a huge issue in society where people who are speech impaired (7 million in the US alone) aren't able to communicate effectively.
What it does
BrainScan gives speech impaired people a voice by converting their brain waves into audible speech.
How we built it
- Hardware and Data Processing -- Used the Muse BrainSensing Headset to read brainwaves.
- Neural Networks -- Used the python keras library to convert brainwaves into readable text.
- Amazon Web Services -- Used AWS to create an Alexa skill that read out the readable text.
Challenges we ran into
We only had 1000 data points, which was not enough to effectively train our neural network model on.
Accomplishments that we're proud of
We got our validation accuracy of the number classification 5% over the baseline.
What we learned
We learned a lot about Amazon Web Services, specifically about Lambda Functions.
What's next for BrainScan
We hope to implement the three step process with synchronous communication and have an instantaneous feedback loop.
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