I’d love to hear how this goes, and we’ll keep you updated on our normalization work! Thank you for your detailed feedback, this is extremely is much more of a DSP expert than I am, so I’m sure he can add some interesting thoughts.This is a quick primer on analog signal processing, which lets you smooth out the noise from analog readings in Arduino microcontrollers, resolving one of the major disquiets of analog sensor inputs, very easily. If you experiment with this, you should also screen your existing training/test data to remove any samples that fall beneath the noise floor. In the immediate term, I think your idea of adding a noise floor in your Arduino program is a good one.
I hope to do some work on this feature some time in the next few months. A solution to this I’d like to implement in Edge Impulse is normalization using learned parameters across the entire dataset, so the normalized spectrogram accurately represents the relative loudness or quietness rather than throwing that information away. I think you’re probably right regarding the normalize function making it difficult to discern between quiet and loud noise. Hi This actually coincides with some thinking we’ve been doing internally regarding normalization. I am going to try adding in even more samples and seeing if that helps.Īny thoughts on other things I can try? I could always weight the confidence by the max volume for an inference sample. I have tried adding the background noise samples to training data, but it doesn’t seem to improve the model stability. The model still jumps around a lot when it is inside and it is quiet, but it will usually stay under 50% confidence.
The first think about is the low-frequency cutoff. The challenge here is to make sure our MFCC output represents these periodic variations in a way that is discernible from background noise. For example, the “chop” of a rotor blade may happen every n milliseconds. The sound of a helicopter contains regular periodic variations that the sound of “silence” (i.e. I’m not an audio processing expert, but here are my thoughts.