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import glob
import os
from functools import partial
import datasets
LANGS = [
"he"
]
VERSION = datasets.Version("0.0.1")
class PublicSpeech(datasets.GeneratorBasedBuilder):
"""Public Speech dataset."""
BUILDER_CONFIGS = [
datasets.BuilderConfig(name=lang, version=VERSION, description=f"Public Speech {lang} dataset")
for lang in LANGS
]
def _info(self):
return datasets.DatasetInfo(
description="youtube audio of kan digital samples",
features=datasets.Features(
{
"audio": datasets.Audio(sampling_rate=16000),
"sentence": datasets.Value("string"),
}
),
supervised_keys=("audio", "sentence"),
homepage="https://huggingface.co/datasets/imvladikon/hebrew_speech_kan",
citation="TODO",
)
def _split_generators(self, dl_manager):
downloader = partial(
lambda split: dl_manager.download_and_extract(f"data/{self.config.name}/{split}.tar.gz"),
)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"root_path": downloader("train"), "split": "train"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"root_path": downloader("dev"), "split": "dev"},
),
]
def _generate_examples(self, root_path, split):
split_path = os.path.join(root_path, split)
for wav in glob.glob(split_path + "/*.wav"):
uid = os.path.splitext(os.path.basename(wav))[0]
with open(os.path.join(split_path, f"{uid}.txt"), encoding="utf-8") as fin:
text = fin.read()
example = {
"audio": wav,
"sentence": text,
}
yield uid, example
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