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Source separation of underwater acoustic radiated noise signals from ships with unknown numbers of signals. Using keras 2.2.4 with tensorflow-gpu 1.12.0 backend.

License: MIT License

Python 100.00%
autoencoder deep-learning deep-neural-networks keras-tensorflow signal-separation source-separation underwater-acoustics

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unknown_number_source_separation's Issues

Z_4_ns_train.hdf5?

Hello, I've been trying to try out your code for research purposes, but ran into a problem. I managed to get past the small bugs such as the default data path and such, but when I try to run the train_separation_multiple_autoencoder.py file, I get the following problem:
OSError: Unable to open file (unable to open file: name = '../data/shipsEar/mix_separation\10547_10547\s0tos3\mix_1to3sep\wavmat\max_one_rand\Z_4_ns_train.hdf5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)

The problem is, Z_4_ns_train.hdf5 is not generated in any of the previous codes. It did generate other .hdf5 files, but never Z_4_ns_train or the like, and I cannot seem to figure out how to make it do that.

Publish some fatal problems affecting parts of the results of the experiments.

Fatal problems:

  • DPRNN models cannot save weights caused by a Lambda layer.
  • A Lambda layer that slices specific channel of data doesnot run correctly.

Small bugs:

  • A sample of s3 is mislabeled in file "data_dir_tree.md". Fortunately, this mistake did not affect the results of previous experiments.
  • A default path of data in file "data_dir_tree.md" is wrong.
  • A bug about decoder input in model 8.
  • Some models are not compatible with specific batch size.

New features:

  • No "environment.yml" for linux os.

These problems will be fixed in next published version.

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