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import csv
import datasets
_PROMPTS_URLS = {
"train": "train.csv",
"validation": "validation.csv",
"test": "test.csv",
}
_ARCHIVES = {
"train": "train.tar.gz",
"validation": "validation.tar.gz",
"test": "test.tar.gz",
}
_PATH_TO_CLIPS = {
"train": "train",
"validation": "validation",
"test": "test",
}
class MUPEASRDataset(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features(
{
"audio_id": datasets.Value("int64"),
"audio_name": datasets.Value("string"),
"file_path": datasets.Value("string"),
"speaker_type": datasets.Value("string"),
"speaker_code": datasets.Value("string"),
"speaker_gender": datasets.Value("string"),
"education": datasets.Value("string"),
"birth_state": datasets.Value("string"),
"birth_country": datasets.Value("string"),
"age": datasets.Value("int64"),
"birth_year": datasets.Value("int64"),
"audio_quality": datasets.Value("string"),
"start_time": datasets.Value("float32"),
"end_time": datasets.Value("float32"),
"duration": datasets.Value("float32"),
"normalized_text": datasets.Value("string"),
"original_text": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=16_000),
}
)
)
def _split_generators(self, dl_manager):
prompts_path = dl_manager.download(_PROMPTS_URLS)
archive = dl_manager.download(_ARCHIVES)
return [
datasets.SplitGenerator(
name = datasets.Split.VALIDATION,
gen_kwargs = {
"prompts_path": prompts_path["validation"],
"path_to_clips": _PATH_TO_CLIPS["validation"],
"audio_files": dl_manager.iter_archive(archive["validation"]),
}
),
datasets.SplitGenerator(
name = datasets.Split.TEST,
gen_kwargs = {
"prompts_path": prompts_path["test"],
"path_to_clips": _PATH_TO_CLIPS["test"],
"audio_files": dl_manager.iter_archive(archive["test"]),
}
),
datasets.SplitGenerator(
name = datasets.Split.TRAIN,
gen_kwargs = {
"prompts_path": prompts_path["train"],
"path_to_clips": _PATH_TO_CLIPS["train"],
"audio_files": dl_manager.iter_archive(archive["train"]),
}
),
]
def _generate_examples(self, prompts_path, path_to_clips, audio_files):
examples = {}
with open(prompts_path, "r") as f:
csv_reader = csv.DictReader(f)
for row in csv_reader:
audio_id = row['audio_id']
audio_name = row['audio_name']
file_path = row['file_path']
speaker_type = row['speaker_type']
speaker_code = row['speaker_code']
speaker_gender = row['speaker_gender']
education = row['education']
birth_state = row['birth_state']
birth_country = row['birth_country']
age = row['age']
birth_year = row['birth_year']
audio_quality = row['audio_quality']
start_time = row['start_time']
end_time = row['end_time']
duration = row['duration']
normalized_text = row['normalized_text']
original_text = row['original_text']
examples[file_path] = {
"audio_id" : audio_id,
"audio_name" : audio_name,
"file_path" : file_path,
"speaker_type" : speaker_type,
"speaker_code" : speaker_code,
"speaker_gender" : speaker_gender,
"education" : education,
"birth_state" : birth_state,
"birth_country" : birth_country,
"age" : age,
"birth_year" : birth_year,
"audio_quality" : audio_quality,
"start_time" : start_time,
"end_time" : end_time,
"duration" : duration,
"normalized_text" : normalized_text,
"original_text" : original_text,
}
inside_clips_dir = False
id_ = 0
for path, f in audio_files:
if path.startswith(path_to_clips):
inside_clips_dir = True
if path in examples:
audio = {"path": path, "bytes": f.read()}
yield id_, {**examples[path], "audio": audio}
id_ += 1
elif inside_clips_dir:
break
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