VAD-Temp / audio_textgrid_dataset.py
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import os
import datasets
class AudioTextgridDataset(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features({
"audio": datasets.Audio(),
"textgrid": datasets.Value("string"),
})
)
def _split_generators(self, dl_manager):
data_dir = dl_manager.download_and_extract("path/to/dataset_folder")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"data_dir": data_dir},
),
]
def _generate_examples(self, data_dir):
metadata_path = os.path.join(data_dir, "metadata.csv")
with open(metadata_path, "r") as f:
for id, line in enumerate(f):
audio_file, textgrid_file = line.strip().split(",")
yield id, {
"audio": os.path.join(data_dir, "data", audio_file),
"textgrid": open(os.path.join(data_dir, "data", textgrid_file)).read(),
}