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renumics/esc50

Dataset Card for "esc50" This is a mirror for the ESC-50 dataset. Original sources: https://github.com/karolpiczak/ESC-50 K. J. Piczak. ESC: Dataset for Environmental Sound Classification. Proceedings of the 23rd Annual ACM Conference on Multimedia, Brisbane, Australia, 2015. [DOI: http://dx.doi.org/10.1145/2733373.2806390] The dataset is available under the terms of the Creative Commons Attribution Non-Commercial license. Exploring the dataset You can visualize… See the full description on the dataset page: https://huggingface.co/datasets/renumics/esc50.

sourceHugging Facecc-by-nc-2.0updated 3y agoView on Hugging Face
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Dataset Card

Dataset Card for "esc50"

This is a mirror for the ESC-50 dataset. Original sources:

https://github.com/karolpiczak/ESC-50 K. J. Piczak. ESC: Dataset for Environmental Sound Classification. Proceedings of the 23rd Annual ACM Conference on Multimedia, Brisbane, Australia, 2015. [DOI: http://dx.doi.org/10.1145/2733373.2806390]

The dataset is available under the terms of the Creative Commons Attribution Non-Commercial license.

Exploring the dataset

You can visualize the dataset using Renumics Spotlight:

python
import datasets
from renumics import spotlight

ds = datasets.load_dataset('renumics/esc50', split='train')

spotlight.show(ds)

Explore enriched dataset

To fully understand the dataset, you can leverage model results such as embeddings or predictions.

Here is an example how to use zero-shot classification with MS CLAP for this purpose:

python
ds_results = datasets.load_dataset("renumics/esc50-clap2023-results",split='train')
ds = datasets.concatenate_datasets([ds, ds_results], axis=1)

spotlight.show(ds, dtype={'text_embedding': spotlight.Embedding, 'audio_embedding': spotlight.Embedding})

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