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import csv
import os
import json
import datasets
_CITATION = """ TBD """
_DESCRIPTION = """\
ALORESB is a collection of african speech corpus for ASR Task.
"""
_DL_URL_FORMAT = "audio/{name}"
class AloresbConfig(datasets.BuilderConfig):
"""BuilderConfig for aloresb"""
def __init__(
self, name, **kwargs
):
"""
Args:
name: name of the configuration
**kwargs: keyword arguments forwarded to super.
"""
super(AloresbConfig, self).__init__(
version=datasets.Version("1.0.0", ""), name=name, **kwargs)
self.data_root_url = _DL_URL_FORMAT.format(name=name)
class Aloresb(datasets.GeneratorBasedBuilder):
"""
The Aloresb dataset
"""
BUILDER_CONFIGS = [
AloresbConfig(name="fongbe", description="Fongbe aloresb dataset"),
AloresbConfig(name="hausa", description="Hausa aloresb dataset"),
AloresbConfig(name="ahmaric", description="Ahmaric aloresb dataset"),
AloresbConfig(name="wolof", description="Wolof aloresb dataset"),
AloresbConfig(name="swahili", description="Swahili aloresb dataset"),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"file": datasets.Value("string"),
"text": datasets.Value("string"),
"audio_id": datasets.Value("string"),
}
),
supervised_keys=("file", "text"),
task_templates=None,
)
def _split_generators(self, dl_manager):
"""
Returns SplitGenerators.
"""
if self.config.name in ["hausa", "wolof"]:
transcripts = dl_manager.download({
"train": self.config.data_root_url + "/train/transcripts.txt",
"dev": self.config.data_root_url + "/dev/transcripts.txt",
"test": self.config.data_root_url + "/test/transcripts.txt",
})
audio_filenames_paths = dl_manager.download({
"train": self.config.data_root_url + "/train/audio_filenames.txt",
"dev": self.config.data_root_url + "/dev/audio_filenames.txt",
"test": self.config.data_root_url + "/test/audio_filenames.txt",
})
else:
transcripts = dl_manager.download({
"train": self.config.data_root_url + "/train/transcripts.txt",
"test": self.config.data_root_url + "/test/transcripts.txt",
})
audio_filenames_paths = dl_manager.download({
"train": self.config.data_root_url + "/train/audio_filenames.txt",
"test": self.config.data_root_url + "/test/audio_filenames.txt",
})
audio_archives = {}
for split in audio_filenames_paths:
if os.path.exists(audio_filenames_paths[split]):
with open(audio_filenames_paths[split], encoding="utf-8") as f:
audio_filenames = [line.strip() for line in f.readlines()]
audio_archives[split] = dl_manager.download([
self.config.data_root_url + "/" + split + "/audio/" + filename
for filename in audio_filenames
])
# (Optional) In non-streaming mode, we can extract the archive locally to have actual local audio files:
local_extracted_archives = dl_manager.extract(audio_archives) if not dl_manager.is_streaming else {}
train_splits = [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"transcript_path": transcripts["train"],
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["train"]],
"local_extracted_archive": local_extracted_archives.get("train"),
}
),
]
if self.config.name in ["hausa", "wolof"]:
return train_splits + [
datasets.SplitGenerator(
name=datasets.Split.VALIDATION, gen_kwargs={
"transcript_path": transcripts["dev"],
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["dev"]],
"local_extracted_archive": local_extracted_archives.get("dev"),
}
),
datasets.SplitGenerator(
name=datasets.Split.TEST, gen_kwargs={
"transcript_path": transcripts["test"],
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["test"]],
"local_extracted_archive": local_extracted_archives.get("test"),
}
),
]
print(train_splits)
return train_splits + [
datasets.SplitGenerator(
name=datasets.Split.TEST, gen_kwargs={
"transcript_path": transcripts["test"],
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["test"]],
"local_extracted_archive": local_extracted_archives.get("test"),
}
),
]
def _generate_examples(self, transcript_path, audio_archives, local_extracted_archive):
"""
Generate examples as dicts.
"""
transcripts = {}
with open(transcript_path, encoding="utf-8") as f:
for line in f:
audio_id, text = line.strip().split("\t")
transcripts[audio_id] = text
for archive_idx, audio_archive in enumerate(audio_archives):
for audio_filename, file in audio_archive:
# get the audio_filename extension
ext = os.path.splitext(audio_filename)[1]
audio_id = audio_filename.split(ext)[0]
audio_transcript = transcripts[audio_id]
local_audio_file_path = os.path.join(
local_extracted_archive[archive_idx], audio_filename
) if local_extracted_archive else None
yield audio_filename, {
"file": local_audio_file_path,
# "audio": {
# "path": local_audio_file_path if local_audio_file_path else audio_filename,
# "bytes": file.read()
# },
"text": audio_transcript,
"audio_id": audio_id
}
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