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Is it possible to provide a non-quantized model, as I have found that quantized models sometimes don't work in real tests, and I'd like to test how accurate non-quantized is
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My native language is not English, and sometimes it's hard to detect when the pronunciation is not quite right, and I wondered if I could improve it by adding some additional audio data. Thank you very much for your answer! @kahrendt
My native language is not English, and sometimes it's hard to detect when the pronunciation is not quite right, and I wondered if I could improve it by adding some additional audio data. Thank you very much for your answer! @kahrendt
I wonder if fine-tuning the models would be possible.. 🤔 maybe that would help? #38
In my benchmarking tests, the quantization doesn't reduce the model accuracy in a consistent way. Sometimes it performs slightly better than the floating point model and sometimes slightly worse. When I mean slightly different, I mean the probability cutoff to only have a 5% false rejection rate differs from by 0.01.
There isn't an easy way to run the non-quantized models; they won't work on an ESP32. They really only work using the test functions in the mWW code itself.
Is it possible to provide a non-quantized model, as I have found that quantized models sometimes don't work in real tests, and I'd like to test how accurate non-quantized is
The text was updated successfully, but these errors were encountered: