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Sound event detection with depthwise separable and dilated convolutions.

Home Page: https://arxiv.org/abs/2002.00476

License: Other

Python 100.00%
sound-event-detection depthwise-separable-convolutions dilated-convolution depthwiseseparableconvolution dilated-cnn audio-signal-processing machine-listening deep-learning deep-neural-networks machine-learning

dnd-sed's Issues

Feature extraction

Hi,I have obtained the TUT-SED Synthetic 2016 database, but I have encountered some problems in the feature extraction section. I would like to know the specific process of audio feature extraction. I would be very grateful if you could show me your code.

Using DessedDilated with custom dataset

Hey authors,

I was wondering how I could transfer the dessedDilated model to train with my pipeline using my custom datasets and dataloader. I have tried looking through files in the model directory, the settings files, _process.py etc. and I seem to be getting somewhere but its still not clear to me. What changes do I have to make to simply use the dessedDilated model?

Thanks

No sigmoid on logits?

It seems like that metric functions are using direct logit values from Linear and calculate positive/negative by thresholding with 0.5, but I cannot find any sigmoid or similar variants that transforms logits into probability estimations. Am I missing something?

problems during the experiment

Thank you for providing such a good open source code, I am reproducing your experiment, the TUT-SED Synthetic 2016 link provided on github has no longer worked, so I downloaded the dataset on the official website. But there are only cpickle files and txt format comments in features, and there are no .npy files, do you need to convert cpickle files to npy? I've been confused for a long time because of this question, looking forward to your reply!

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