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import csv
import datasets
_PROMPTS_URLS = {
"dev": "data/audios_dev_metadata.csv",
}
_ARCHIVES = {
"dev": "data/dev.tar",
}
_PATH_TO_CLIPS = {
"dev": "dev",
}
class NurcSPDataset(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features(
{
"audio_name": datasets.Value("string"),
"file_path": datasets.Value("string"),
"text": datasets.Value("string"),
"start_time": datasets.Value("string"),
"end_time": datasets.Value("string"),
"duration": datasets.Value("string"),
"quality": datasets.Value("string"),
"speech_genre": datasets.Value("string"),
"speech_style": datasets.Value("string"),
"variety": datasets.Value("string"),
"accent": datasets.Value("string"),
"sex": datasets.Value("string"),
"age_range": datasets.Value("string"),
"num_speakers": datasets.Value("string"),
"speaker_id": 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["dev"],
"path_to_clips": _PATH_TO_CLIPS["dev"],
"audio_files": dl_manager.iter_archive(archive["dev"]),
}
),
]
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_name = row['audio_name']
file_path = row['file_path']
text = row['text']
start_time = row['start_time']
end_time = row['end_time']
duration = row['duration']
quality = row['quality']
speech_genre = row['speech_genre']
speech_style = row['speech_style']
variety = row['variety']
accent = row['accent']
sex = row['sex']
age_range = row['age_range']
num_speakers = row['num_speakers']
speaker_id = row['speaker_id']
examples[file_path] = {
"audio_name": audio_name,
"file_path": file_path,
"text": text,
"start_time": start_time,
"end_time": end_time,
"duration": duration,
"quality": quality,
"speech_genre": speech_genre,
"speech_style": speech_style,
"variety": variety,
"accent": accent,
"sex": sex,
"age_range": age_range,
"num_speakers": num_speakers,
"speaker_id": speaker_id,
}
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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