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# Copyright 2023 GTTS (http://gtts.ehu.eus)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Lint as: python3
"""Basque Parliament dataset"""
import datasets
from datasets.utils.py_utils import size_str
import os
import csv
from tqdm import tqdm
from .languages import LANGUAGES
from .release_stats import STATS
_CITATION = """\
"""
_HOMEPAGE = "https://huggingface.co/datasets/gttsehu/basque_parliament_1"
_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
_DESCRIPTION = (
f"Basque Parliament dataset blah blah blah..."
f"blah blah blah..."
f"blah blah blah..."
)
_BASE_URL = "https://huggingface.co/datasets/gttsehu/basque_parliament_1/resolve/main/"
_AUDIO_URL = _BASE_URL + "audio/{split}_{shard_idx}.tar"
_METADATA_URL = _BASE_URL + "metadata/{split}.tsv"
class BasqueParliamentConfig(datasets.BuilderConfig):
"""BuilderConfig for BasqueParliament."""
def __init__(self, name, version, **kwargs):
self.language = kwargs.pop("language", None)
self.release_date = kwargs.pop("release_date", None)
self.num_clips = kwargs.pop("num_clips", None)
self.num_speakers = kwargs.pop("num_speakers", None)
self.validated_hr = kwargs.pop("validated_hr", None)
self.total_hr = kwargs.pop("total_hr", None)
self.size_bytes = kwargs.pop("size_bytes", None)
self.size_human = size_str(self.size_bytes)
description = _DESCRIPTION
super(BasqueParliamentConfig, self).__init__(
name = name,
version = datasets.Version(version),
description = _DESCRIPTION,
**kwargs,
)
class BasqueParliament(datasets.GeneratorBasedBuilder):
"""Basque Parliament is a free Basque-Spanish speech corpus."""
DEFAULT_CONFIG_NAME = "all"
BUILDER_CONFIGS = [
BasqueParliamentConfig(
name=lang,
version=STATS["version"],
language=LANGUAGES[lang],
release_date=STATS["date"],
num_clips=lang_stats["clips"],
num_speakers=lang_stats["users"],
total_hr=float(lang_stats["totalHrs"]) if lang_stats["totalHrs"] else None,
size_bytes=int(lang_stats["size"]) if lang_stats["size"] else None,
)
for lang, lang_stats in STATS["locales"].items()
]
def _info(self):
description = (
f"Basque Parliament dataset blah blah blah..."
f"blah blah blah..."
f"blah blah blah..."
)
features = datasets.Features(
{
"path": datasets.Value("string"),
"audio": datasets.features.Audio(sampling_rate=16_000),
"sentence": datasets.Value("string"),
"speaker_id": datasets.Value("string"),
"language": datasets.Value("string"),
"PRR": datasets.Value("float32"),
"length": datasets.Value("float32"),
}
)
return datasets.DatasetInfo(
description = _DESCRIPTION,
features = features,
supervised_keys = None,
homepage = _HOMEPAGE,
license = _LICENSE,
citation = _CITATION,
version = self.config.version,
)
def _split_generators(self, dl_manager):
lang = self.config.name
audio_urls = {}
splits = ("train", "train_clean", "dev", "test")
for split in splits:
if split == "train_clean": continue
audio_urls[split] = [
_AUDIO_URL.format(split=split, shard_idx=i) for i in range(STATS["n_shards"][split])
]
audio_urls["train_clean"]=audio_urls["train"]
archive_paths = dl_manager.download(audio_urls)
local_extracted_archive_paths = dl_manager.extract(archive_paths) if not dl_manager.is_streaming else {}
metadata_urls = {split: _METADATA_URL.format(lang=lang, split=split) for split in splits}
metadata_paths = dl_manager.download_and_extract(metadata_urls)
split_generators = []
split_names = {
"train": datasets.Split.TRAIN,
"dev": datasets.Split.VALIDATION,
"test": datasets.Split.TEST,
}
for split in splits:
split_generators.append(
datasets.SplitGenerator(
name=split_names.get(split, split),
gen_kwargs={
"local_extracted_archive_paths": local_extracted_archive_paths.get(split),
"archives": [dl_manager.iter_archive(path) for path in archive_paths.get(split)],
"metadata_path": metadata_paths[split],
},
),
)
return split_generators
def _generate_examples(self, local_extracted_archive_paths, archives, metadata_path):
lang = self.config.name
data_fields = list(self._info().features.keys())
metadata = {}
with open(metadata_path, encoding="utf-8") as f:
reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
metadata = { row["path"]:row for row in tqdm(reader, desc="Reading metadata...") }
excluded = 0
for i, audio_archive in enumerate(archives):
for path, file in audio_archive:
if path not in metadata :
excluded += 1
continue
result = dict(metadata[path])
if lang == "all" or lang == result["language"] :
# set the audio feature and the path to the extracted file
path = os.path.join(local_extracted_archive_paths[i], path) if local_extracted_archive_paths else path
result["audio"] = {"path": path, "bytes": file.read()}
result["path"] = path
yield path, result
print(excluded,'audio files not found in metadata')
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