Speech

With how hard something like this is, we should be looking at the positive side. Picovoice here solves both the issues of hotword/wake-word detection and intent extraction. This looks like something you could build on top of ARM's [keyword spotting program](https://github.com/ARM-software/ML-KWS-for-MCU) and the wake word services listed in [Rhasspy's docs](https://rhasspy.readthedocs.io/en/latest/wake-word/#raven) But, to implement something like this from scratch would take a good while. Also, here are some Automatic Speech Recognition toolkits (which won't run offline on a microcontroller) out there. These are useful to pipe the data into a program that deals with intents (something like [RASA](https://rasa.com) (Require Internet) * [Deepgram](https://deepgram.com) - I believe they build upon OpenAI's Whisper model and have their own c

I think there's been talk to do speaker diarization with whisper-asr-webservice[0] which is also written in python and should be able to make use of goodies such as pyannote-audio, py-webrtcvad, etc. Whisper is great but at the point we get to kludging various things together it might start to make more sense to use something like Nvidia NeMo[1] which was built with all of this in mind and more. [0] - https://github.com/ahmetoner/whisper-asr-webservice [1] - https://github.com/NVIDIA/NeMo

Out of interest, did you try Nemo? https://github.com/NVIDIA/NeMo