We are currently working on implementing a baby cry detection model in the frontend of our app but have encountered some challenges with the mel spectrogram transformation.
Our mel spectrogram class, developed in python, leverages librosa for generating mel spectrograms (librosa.feature.melspectrogram and librosa.power_to_db). While we have successfully exported the model to a .mlmodel file, the results we obtain in Swift differ significantly from those generated by our Python code.
Could this discrepancy be due to the use of librosa in Python, which might not be directly compatible with Swift? Or should the transformation process be inherently consistent once exported to a .mlmodel file?
apocappella
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