File size: 2,116 Bytes
6140e29 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
import os
import datasets
import pandas as pd
_DESCRIPTION = """\
This data is CS data
"""
_CITATION = "Some citation"
_data_dir = "data"
class CSData(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"path": datasets.Value("string"),
"filename": datasets.Audio(sampling_rate=16_000),
"transcription": datasets.Value("string"),
}
),
supervised_keys=None,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
download_dir = dl_manager.download_and_extract(
{
"files": os.path.join(_data_dir, "files.zip"),
"metadata": os.path.join(_data_dir, "metadata.zip")
}
)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"split": datasets.Split.TRAIN,
"data_dir": os.path.join(download_dir["files"], "files"),
"metapath": os.path.join(download_dir["metadata"], "metadata", "data.csv"),
},
),
# datasets.SplitGenerator(
# name=datasets.Split.TEST,
# gen_kwargs={
# "split": datasets.Split.TEST,
# "data_dir": os.path.join(download_dir["files"], "files"),
# "metapath": os.path.join(download_dir["metadata"], "metadata", "test.csv"),
# },
# ),
]
def _generate_examples(self, data_dir, metapath, split):
metadata = pd.read_csv(metapath)
for key, row in metadata.iterrows():
audio_path = os.path.join(data_dir, row["filename"])
yield key, {
"filename": audio_path,
"transcription": row["transcription"],
"path": audio_path,
} |