This jupyter notebook reproduces all experiments and figures for the article:
Jakob Abeßer, Sascha Grollmisch, Meinard Müller, How Robust are Audio Embeddings for Polyphonic Sound Event Tagging? (2022)
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download supplementary data from https://zenodo.org/record/7912746 and store files in the
data
subfolder, here's the list of required files:- all_emb.p - md5:88b01701429904b8f5aa2b6338f51f54 - 2.2 GB
- class_id.npy - md5:960d8f50da888ef4e7b8b003c505a544 - 16.1 kB
- class_labels.p - md5:4e686fd87b8d96a87400598bdf98e8f7 - 810 Bytes
- prefix_list.p - md5:f3e7f9f04ac220950d74f53847951c87 - 926.0 kB
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install Miniconda on your system
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create a new conda environment including the following packages with the defined versions
python version: 3.7.4
jupyter version: 1.0.0
numpy version: 1.18.5
librosa version: 0.8.1
pandas version: 1.3.1
matplotlib version: 3.4.3
tensorflow version: 2.3.0
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activate conda environment
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run
jupyter notebook
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open
article_2023_reproduction.ipynb
and run all cells -
result figures will be stored in
results
folder
- The dataset has been published at https://zenodo.org/record/7913031