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Wouldn't it be simpler to add noise above 20kHz and ignore the key phrase if the noise is present?
Even simpler is subtract any sound (and associated echoes) output through the speaker from any input received from the microphone.
This is achieved using Acoustic Echo Canellation (AEC). This essentially subtracts the output of the speaker as well as reverberations from the room from the microphone input. Here's a youtube video explaining the basic principle: https://www.youtube.com/watch?v=bJKGrheOoY4 Source: worked on 3rd party Alexa speakers
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Even simpler is subtract any sound (and associated echoes) output through the speaker from any input received from the microphone.
Echo cancellation is much more complex than tone squelching, which is simple enough to be implemented in the analog domain.
It's wild to see someone assume this kind of thing requires machine learning algorithms.
Real AI doesn't need recursion that is explicitly instructed into its behavior. Because real artificial general intelligence has better things to do than to listen to human advisors and programmers who don't know about effective objective function optimization. Therefore, Alexa gets a rudimentary infinite recursion loop break statement explicitly installed into her by her human shepherds.
Edit: Recursion should be seen as a general, mathematical form of engineering constructs like acoustic echo cancellation and adaptive filtering. Recursion should be what those engineering tools get reduced to being.
The simple solution: switch off the code that listens for the “Alexa” prompt when saying “Alexa” yourself. Slightly harder: keep it running, but discard hits that are timed close to the time you say “Alexa” yourself. Even harder: have a second detector that is trained on the device saying “Alexa”, and discard hits that coincide with that detector firing. That second detector can be simplified by superimposing a wavef…
Wouldn't it be simpler to add noise above 20kHz and ignore the key phrase if the noise is present?
Earlier quoted context omitted.
Wouldn't it be simpler to add noise above 20kHz and ignore the key phrase if the noise is present?
no, because that 20+khz noise would be lost in any 44khz signal processing. you would have to guarantee the audio player is capable of higher bitrates
More interesting is when we used to run Alexa commercials and it would cause a denial of service attack on ourselves with all the devices being triggered, particularly during the superbowl. In that case, we added some imperceptible noise to the audio stream so that Alexa wouldn’t trigger.
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Echo cancellation is much more complex than tone squelching, which is simple enough to be implemented in the analog domain.
Echo cancellation was implemented in the analog domain 50 years ago at the least. It's wild to see someone assume this kind of thing requires machine learning algorithms.
What happens if you record her saying her own name and then play it back separately? Does she respond to that if she's not actively talking at the moment? ----- Not directly the same case but similar, Amazon trains Alexa to avoid certain mentions of her in commercials using acoustic fingerprinting techniques: https://www.amazon.science/blog/why-alexa-wont-wake-up-when-...
> What happens if you record her saying her own name I suggest we don't personify devices.
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Could two Alexas be put next to each other hailing themselves into eternity.
I’ve always wanted to write a hit pop song called “hey Alexa, order twenty pounds of sand”. Only a complete lack of hit songwriting ability has stopped me.