This git contains code for CRNNs we used to achieve first rank in Task 5 of the DCASE 2020 challenge. This task focuses on hierarchical multilabel urban sound tagging with spatiotemporal context. The technical report can be found here.

Python version recquired : 3.6 (Higher might work). We recommand first to create a new environment in conda/virtualenv then to activate it.

Pip install

pip install -r requirements.txt

Conda install

conda env create -f environment.yml

Manual install

pip install numpy scikit-learn pandas tqdm albumentations librosa tensorboard torch torchvision oyaml pytorch-lightning numba==0.49

You should edit PATH in config.py to match the directory in which everything will be stored.

Use the following to download the dataset and precompute inputs for TALNet and CNN14.

WARNING : It requires about 30Go of free space.

python data_prep.py --download --mel

If you want to manualy download and decompress files, you have to put everything in the audio directory. Then you have to use the aboce command without the --download.

The code should work on both CPU and GPU. Add --gpu followed by the number of GPUs to use them.

Add --seed followed by the seed for to set seed for random operations.

python training_system1 --gpu 1 --seed 1

You can add --cleaning_strat Relabeled --relabeled_name INSERT_CSV_HERE to train on a specific relabeled dataset. See below for relabelling. The pretrained TALNet on Audioset can be found at http://islpc21.is.cs.cmu.edu/yunwang/git/cmu-thesis/model/TALNet.pt.

Once system3 has been trained a first time, we can use it to relabel everything.

You have to specify the ckpt path and the hparams.yml path. Because of a bug in the pytorch-lighnting build used, hparams.yml has to be edited to remove the early stop part.

python relabel.py --path_to_ckpt INSERT_HERE --path_to_yaml INSERT_HERE

Like the relabelling part, hparams.yml has to be edited to remove the early stop part.

Once it is done, you have to specify both the path to the checkpoint of the model and the path to the hparams edited.

python sub_system1 --path_to_ckpt INSERT_HERE --path_to_yaml INSERT_HERE

@techreport{Arnault2020,
    Author = "Arnault, Augustin and Riche, Nicolas",
    title = "{CRNNs} for Urban Sound Tagging with Spatiotemporal Context",
    institution = "DCASE2020 Challenge",
    year = "2020",
    month = "October",
    abstract = "This paper describes CRNNs we used to participate in Task 5 of the DCASE 2020 challenge. This task focuses on hierarchical multilabel urban sound tagging with spatiotemporal context. The code is available to our GitHub repository at https://github.com/multitel-ai/urban-sound-tagging."
}