hearbenchmark / hear2021-submitted-models

Open-source audio embedding models, submitted to the HEAR 2021 challenge

hear2021-submission-models

Open-source audio embedding models, submitted to the 2021 NeurIPS HEAR challenge and evaluated on the HEAR Benchmark. To find out more about the competition and HEAR benchmark please visit https://hearbenchmark.com.

All are pip3-installable, follow the HEAR API, and are open source.

See also the 3 baseline models.

Information about each model is available in models.json, including license information which may have been told directly to us by the authors.

Model checkpoints, where necessary, are available at Zenodo. Note that some models implicitly download their checkpoints from the internet, instead of explicitly loading from disk (as per the 2021 NeurIPS HEAR challenge rules), which reduces their replicability.

Models are grouped into three "installation groups". We found that most models (group 1) were pytorch >= 1.9 that could peacefully co-exist in one installation environment. Group 3 models were Tensorflow 2.4 models. Group 2 models were models that could not co-exist either with group 1 or group 3 models. Conflicting dependencies is the reason we can't provide one pip3-installable package for all NeurIPS 2021 HEAR challenge models.

To install a particular model, the steps are:

pip install git+{git_url}.git@{git_rev_2021_12_01} {pip3_additional_packages}
wget {zenodo_weights_url}

You can then follow heareval as usual. See, for example, this notebook.

Model code is mirrored in mirror/.