For ASR/STT on a budget, you want https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3 - it works great on CPU.

I haven't tried on a raspberry pi, but on Intel it uses a little less than 1s of CPU time per second of audio. Using https://github.com/NVIDIA-NeMo/NeMo/blob/main/examples/asr/a... for chunked streaming inference, it takes 6 cores to process audio ~5x faster than realtime. I expect with all cores on a Pi 4 or 5, you'd probably be able to at least keep up with realtime.

(Batch inference, where you give it the whole audio file up front, is slightly more efficient, since chunked streaming inference is basically running batch inference on overlapping windows of audio.)

EDIT: there are also the multitalker-parakeet-streaming-0.6b-v1 and nemotron-speech-streaming-en-0.6b models, which have similar resource requirements but are built for true streaming inference instead of chunked inference. In my tests, these are slightly less accurate. In particular, they seem to completely omit any sentence at the beginning or end of a stream that was partially cut off.