Bela is fantastic because it pairs good audio hardware with low latency software. Elk looks good, but I'd need something better than a Raspberry Pi in terms of audio IOs to use that full potential.
Counter to a lot of the sentiment in this thread, I think it's pretty obvious that a different set of ethical beliefs would result in advocating for a totally different set of policies and that's how it should be. If even a single covid death is unacceptable to you (something I've heard expressed by a couple folks on the far left), then it's pretty obvious that advocating for continued caution is the right answer.
That said, obviously economic distress, depression and other factors are taking years off of people's lives too, any reasonable viewpoint must accept some level of tradeoff here.
I think the trouble you're running into is that a spectrogram discards phase information so it's not informationally complete, and impossible to perfectly invert. Basically, a Fourier Transform represents a sound as a series of many sound waves at different frequencies added together. In order to make a pretty picture, the phase is thrown away, and only the magnitude of each wave is shown. The trouble is, to go back to a pleasant/accurate sound, we need that phase information that is missing.
Vosk does a solid job, and there are a couple other alternatives. Trouble is, the bottleneck for quality here is dataset size/quality/availability, so closed-source models with private data have the leg up.
Difference from DataFrames: it's possible to use on larger-than memory data, as long as you have it in separate csv files which can be super useful at times!
Any plans for DataFrames to support larger-than-memory data though? JuliaDB is super useful for this I've found, basically a solid Julia alternative to Dask.
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