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Post Hoc Denoising
Although the call detection network will reject many non-vocal noise events, we have tuned to value sensitivity over precision.
False positives may be automatically identified and rejected using a post hoc neural network. The network must be located in "DeepSqueak\Denoising Networks\CleaningNet.mat".
To use the post hoc denoiser:
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Select "Tools > Automatic Review > Post Hoc Denoising"
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In the list box, select the detection files to denoise. All noise events found will be classified as "Noise" and rejected.
To train a post hoc denoiser:
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Select "Tools > Network Training > Train Post Hoc Denoiser"
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In the list box, select the detection files to to use for training.
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Calls labeled as "Noise" are used as negative training sample.
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Accepted calls not labeled as "Noise" are used as positive training samples.
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When training is finished, the new network will be automatically saved as "DeepSqueak\Denoising Networks\CleaningNet.mat".
- Training will overwrite the older network. It is wise to create a backup of the old network.
Copyright © 2018 by Russell Marx & Kevin Coffey. All Rights Reserved. https://doi.org/10.1038/s41386-018-0303-6