Datasets:
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import datasets
_CITATION = """\
@dataset{sadia_sultana_2021_4526477,
author = {Sadia Sultana},
title = {SUST Bangla Emotional Speech Corpus (SUBESCO)},
month = feb,
year = 2021,
note = {{This database was created as a part of PhD thesis
project of the author Sadia Sultana. It was
designed and developed by the author in the
Department of Computer Science and Engineering of
Shahjalal University of Science and Technology.
Financial grant was supported by the university.
If you use the dataset please cite SUBESCO and the
corresponding academic journal publication in Plos
One.}},
publisher = {Zenodo},
version = {version - 1.1},
doi = {10.5281/zenodo.4526477},
url = {https://doi.org/10.5281/zenodo.4526477}
}
"""
_DESCRIPTION = """\
SUST Bangla Emotional Speech Coropus Dataset
"""
_HOMEPAGE = "https://huggingface.co/datasets/sustcsenlp/bn_emotion_speech_corpus"
_LICENSE = ""
class AudioSet(datasets.GeneratorBasedBuilder):
""""""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
'text': datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=16000),
}
),
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
audio_archive = dl_manager.download("https://huggingface.co/datasets/sustcsenlp/bn_emotion_speech_corpus/resolve/main/subesco.tar.gz")
audio_iters = dl_manager.iter_archive(audio_archive)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"audios": audio_iters
}
),
]
def _generate_examples(self, audios):
"""This function returns the examples in the raw (text) form."""
idx = 0
for filepath, audio in audios:
description = filepath.split('/')[-1][:-4]
#description = description.replace('_', ' ')
yield idx, {
"audio": {"path": filepath, "bytes": audio.read()},
"text": description,
}
idx += 1 |