In case anyone with practical skills in ML+deep learning (but not in audio or embedded) wants to tackle this project, I am willing to mentor on those things. Mi

In case anyone with practical skills in ML+deep learning (but not in audio or embedded) wants to tackle this project, I am willing to mentor on those things. Microcontroller-level audio ML is my speciality. One can find me in the Sound of AI Slack. Ping me there and we can create a channel etc. It will be a multi-month endeavour though. Getting to PoC level is quite quick, but then getting robust performance in nearfield / high SNR cases across diverse background noise is a lot more work. And then tackling low SNR and far-field like with Alexa is yet another level. Model architecture wise the problem is rather well understood, there are several good papers available from ARM etc. Deployement infrastructure also pretty good these days, for example with Tensorflow Lite Micro. In addition to ML skills, the project would need someone that is good at organizing volunteer outreach, in order to build a good sized dataset. The Espressif docs are a reasonable spec for something quite good on the voice side. But then we would also need a good dataset of background noise. Of course those with embedded/microcontroller skills are also very welcome.