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Detecting signals from .wav files after deep learning network is trained

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Ashley Cook
Ashley Cook le 7 Juin 2021
Commenté : ytzhak goussha le 30 Juin 2021
Are there any follow up tutorials or examples on how to detect sounds in .wav files after you train a network to classify spectrograms? The 'deep learning with MATLAB course' teaches how to classify spectrograms, but in order for this to be useful in my work I wanted to be able to then use the the trained network to evaluate ~30 min .wav files and detect a desired sound type. Any links or suggestions are welcome.
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ytzhak goussha
ytzhak goussha le 30 Juin 2021
Hey,
  1. reshape your vector into a matrix, it possible that you might have to zero pad it or truncate it to able to reashe the vector into a matrix with desider number or row.
  2. use audioFeatureExtractor to create an extractor with desird parameters and use it to extract spectrograms from you audio matrix
  3. feed the spectrograms to your model. if your spectrograms are too large, feed the matrix in small batches

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