File size: 3,922 Bytes
7977cf7 |
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 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
import datasets
_DATA_URL = "data/vivos_noisy.tar.gz"
_PROMPTS_URLS = {
"train": "data/train_prompts.txt.gz",
"test": "data/test_prompts.txt.gz",
}
class VivosNoisyDataset(datasets.GeneratorBasedBuilder):
"""VIVOS NOISY is a Vietnamese speech corpus with added noise, based on the original VIVOS dataset.
This corpus is prepared for Vietnamese Automatic Speech Recognition task under noisy environments."""
VERSION = datasets.Version("1.1.0")
def _info(self):
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
features=datasets.Features(
{
"speaker_id": datasets.Value("string"),
"path": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=16_000),
"sentence": datasets.Value("string"),
}
),
supervised_keys=None,
)
def _split_generators(self, dl_manager):
prompts_paths = dl_manager.download_and_extract(_PROMPTS_URLS)
archive = dl_manager.download(_DATA_URL)
train_dir = "vivos_noisy/train"
test_dir = "vivos_noisy/test"
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"prompts_path": prompts_paths["train"],
"path_to_clips": train_dir + "/waves",
"audio_files": dl_manager.iter_archive(archive),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"prompts_path": prompts_paths["test"],
"path_to_clips": test_dir + "/waves",
"audio_files": dl_manager.iter_archive(archive),
},
),
]
def _generate_examples(self, prompts_path, path_to_clips, audio_files):
"""Yields examples as (key, example) tuples."""
# This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
# The `key` is here for legacy reason (tfds) and is not important in itself.
examples = {}
with open(prompts_path, encoding="utf-8") as f:
for row in f:
data = row.strip().split(" ", 1)
# Extract speaker_id from the full filename
# For example: VIVOS_NOISY_VIVOSDEV01_R002_001 -> VIVOS_NOISY_VIVOSDEV01
filename_parts = data[0].split("_")
if len(filename_parts) >= 3:
# Join the first 3 parts to get the speaker_id (VIVOS_NOISY_VIVOSDEV01)
speaker_id = "_".join(filename_parts[:3])
else:
# Fallback if the naming convention is different
speaker_id = filename_parts[0]
audio_path = "/".join([path_to_clips, speaker_id, data[0] + ".wav"])
examples[audio_path] = {
"speaker_id": speaker_id,
"path": audio_path,
"sentence": data[1],
}
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 |