Installation

pip install aac-datasets

Examples

Create Clotho dataset

from aac_datasets import Clotho

dataset = Clotho(root=".", download=True)
item = dataset[0]
audio, captions = item["audio"], item["captions"]
# audio: Tensor of shape (n_channels=1, audio_max_size)
# captions: list of str

Build PyTorch dataloader with Clotho

from torch.utils.data.dataloader import DataLoader
from aac_datasets import Clotho
from aac_datasets.utils import BasicCollate

dataset = Clotho(root=".", download=True)
dataloader = DataLoader(dataset, batch_size=4, collate_fn=BasicCollate())

for batch in dataloader:
    # batch["audio"]: list of 4 tensors of shape (n_channels, audio_size)
    # batch["captions"]: list of 4 lists of str
    ...

Datasets stats

Here is the statistics for each dataset :

For Clotho, the dev subset should be used for training, val for validation and eval for testing. The test and analysis subsets contains only audio files without labels from the DCASE challenge.

Here is the train subset statistics for each dataset :

¹ This duration is estimated on the total duration of 46230/49838 files of 126.7h.

² The sentences are cleaned (lowercase+remove punctuation) and tokenized using the spacy tokenizer to count the words.

Requirements

Python packages

The requirements are automatically installed when using pip on this repository.

torch >= 1.10.1
torchaudio >= 0.10.1
py7zr >= 0.17.2
pyyaml >= 6.0
tqdm >= 4.64.0

External requirements (AudioCaps only)

The external requirements needed to download AudioCaps are ffmpeg and youtube-dl. These two programs can be download on Ubuntu using sudo apt install ffmpeg youtube-dl.

You can also override their paths for AudioCaps:

from aac_datasets import AudioCaps
AudioCaps.FFMPEG_PATH = "/my/path/to/ffmpeg"
AudioCaps.YOUTUBE_DL_PATH = "/my/path/to/youtube_dl"
dataset = AudioCaps(root=".", download=True)

Download datasets

To download a dataset, you can use download argument in dataset construction :

dataset = Clotho(root=".", subset="dev", download=True)

Or use the corresponding function in the code :

from aac_datasets.download import download_clotho

download_clotho(root=".", subsets=["dev"])

However, if you want to download datasets from a script, you can also use the following command :

aac-datasets-download --root "." clotho --subsets "dev"

References

AudioCaps

[1] C. D. Kim, B. Kim, H. Lee, and G. Kim, “Audiocaps: Generating captions for audios in the wild,” in NAACL-HLT, 2019. Available: https://aclanthology.org/N19-1011/

Clotho

[2] K. Drossos, S. Lipping, and T. Virtanen, “Clotho: An Audio Captioning Dataset,” arXiv:1910.09387 [cs, eess], Oct. 2019, Available: http://arxiv.org/abs/1910.09387

MACS

[3] F. Font, A. Mesaros, D. P. W. Ellis, E. Fonseca, M. Fuentes, and B. Elizalde, Proceedings of the 6th Workshop on Detection and Classication of Acoustic Scenes and Events (DCASE 2021). Barcelona, Spain: Music Technology Group - Universitat Pompeu Fabra, Nov. 2021. Available: https://doi.org/10.5281/zenodo.5770113

Cite the aac-datasets package

If you use this software, please consider cite it as below :

@software{
    Labbe_aac-datasets_2022,
    author = {Labbé, Etienne},
    license = {MIT},
    month = {05},
    title = {{aac-datasets}},
    url = {https://github.com/Labbeti/aac-datasets/},
    version = {0.3.3},
    year = {2023}
}

Contact

Maintainer:

• Etienne Labbé "Labbeti": labbeti.pub@gmail.com