Update dataset script
Browse filesI removed the import of `xopen` which is not necessary, and simplified it using the same code style as the other audio datasets
cc
@polinaeterna
@anton-l
This should fix https://huggingface.co/datasets/facebook/multilingual_librispeech/discussions/2
- multilingual_librispeech.py +66 -107
multilingual_librispeech.py
CHANGED
@@ -16,12 +16,9 @@
|
|
16 |
# Lint as: python3
|
17 |
"""Multilingual Librispeech automatic speech recognition dataset."""
|
18 |
|
19 |
-
|
20 |
-
from functools import partial
|
21 |
import os
|
22 |
|
23 |
import datasets
|
24 |
-
from datasets.utils.streaming_download_manager import xopen
|
25 |
|
26 |
|
27 |
_CITATION = """\
|
@@ -62,7 +59,7 @@ class MultilingualLibrispeechConfig(datasets.BuilderConfig):
|
|
62 |
version=datasets.Version("2.1.0", ""), name=name, **kwargs
|
63 |
)
|
64 |
# relative path to full data inside a repo (for example `data/mls_german`)
|
65 |
-
self.
|
66 |
|
67 |
|
68 |
class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
|
@@ -98,46 +95,68 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
|
|
98 |
)
|
99 |
|
100 |
def _split_generators(self, dl_manager):
|
101 |
-
|
102 |
-
|
103 |
-
"
|
104 |
-
|
105 |
-
|
106 |
-
|
107 |
-
|
108 |
-
|
109 |
-
|
110 |
-
|
111 |
-
download_audio_streaming = partial(
|
112 |
-
download_audio_archives, **download_kwargs
|
113 |
-
)
|
114 |
-
download_limited_ids = partial(
|
115 |
-
download_extract_limited_ids, **download_kwargs
|
116 |
)
|
117 |
-
|
118 |
-
|
119 |
-
|
120 |
-
"
|
121 |
-
|
122 |
-
|
123 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
124 |
|
125 |
train_splits = [
|
126 |
datasets.SplitGenerator(
|
127 |
-
name=datasets.Split.TRAIN,
|
|
|
|
|
|
|
|
|
|
|
128 |
),
|
129 |
datasets.SplitGenerator(
|
130 |
name="train.9h",
|
131 |
gen_kwargs={
|
132 |
-
|
133 |
-
"
|
|
|
|
|
134 |
},
|
135 |
),
|
136 |
datasets.SplitGenerator(
|
137 |
name="train.1h",
|
138 |
gen_kwargs={
|
139 |
-
|
140 |
-
"
|
|
|
|
|
141 |
},
|
142 |
),
|
143 |
]
|
@@ -145,23 +164,21 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
|
|
145 |
return train_splits + [
|
146 |
datasets.SplitGenerator(
|
147 |
name=datasets.Split.VALIDATION, gen_kwargs={
|
148 |
-
"transcript_path":
|
149 |
-
"audio_archives":
|
150 |
-
"
|
151 |
-
if not dl_manager.is_streaming else None
|
152 |
}
|
153 |
),
|
154 |
datasets.SplitGenerator(
|
155 |
name=datasets.Split.TEST, gen_kwargs={
|
156 |
-
"transcript_path":
|
157 |
-
"audio_archives":
|
158 |
-
"
|
159 |
-
if not dl_manager.is_streaming else None
|
160 |
}
|
161 |
),
|
162 |
]
|
163 |
|
164 |
-
def _generate_examples(self, transcript_path, audio_archives,
|
165 |
"""Generate examples from a Multilingual LibriSpeech data dir."""
|
166 |
transcripts = dict()
|
167 |
with open(transcript_path, "r", encoding="utf-8") as file:
|
@@ -192,76 +209,18 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
|
|
192 |
# this only can be true in limited supervision sets ("train.9h" and "train.1h")
|
193 |
continue
|
194 |
|
195 |
-
|
196 |
-
|
|
|
|
|
197 |
yield audio_filename, {
|
198 |
-
"file":
|
199 |
-
"audio": {
|
|
|
|
|
|
|
200 |
"text": audio_transcript,
|
201 |
"speaker_id": speaker_id,
|
202 |
"chapter_id": chapter_id,
|
203 |
"id": audio_id
|
204 |
}
|
205 |
-
|
206 |
-
|
207 |
-
def download_extract_limited_ids(dl_manager, root_dir, sub_folder):
|
208 |
-
"""Download handles.txt files containing ids for limited supervision train sets. """
|
209 |
-
|
210 |
-
sub_path = os.path.join(root_dir, "train", sub_folder)
|
211 |
-
|
212 |
-
if sub_folder.endswith("9hr"):
|
213 |
-
limited_ids_paths = [os.path.join(sub_path, "handles.txt")]
|
214 |
-
else: # => sub_folder.endswith("1hr")
|
215 |
-
# in case of 1 hour limited supervision ("train.1h") there are always 6 subfolders like:
|
216 |
-
# "limited_supervision/1h/0/handles.txt", "limited_supervision/1h/1/handles.txt", ...
|
217 |
-
limited_ids_paths = [os.path.join(sub_path, str(i), "handles.txt") for i in range(6)]
|
218 |
-
|
219 |
-
limited_ids_paths = dl_manager.download(limited_ids_paths)
|
220 |
-
|
221 |
-
return limited_ids_paths
|
222 |
-
|
223 |
-
|
224 |
-
def download_extract_transcript(dl_manager, root_dir, split):
|
225 |
-
"""
|
226 |
-
Download file with audio transcriptions.
|
227 |
-
|
228 |
-
Return:
|
229 |
-
path (str): path to locally extracted `transcripts.txt` file
|
230 |
-
"""
|
231 |
-
transcript_path = os.path.join(root_dir, split, "transcripts.txt")
|
232 |
-
return dl_manager.download(transcript_path)
|
233 |
-
|
234 |
-
|
235 |
-
def download_audio_archive_paths(dl_manager, root_dir, split):
|
236 |
-
# each split contains many .tar.gz archives with its audio files
|
237 |
-
# audio_filenames.txt contains the names of these archives
|
238 |
-
split_dir = os.path.join(root_dir, split)
|
239 |
-
audio_filenames_path = dl_manager.download(os.path.join(split_dir, "audio_filenames.txt"))
|
240 |
-
|
241 |
-
with open(audio_filenames_path, "r", encoding="utf-8") as file:
|
242 |
-
audio_filenames = [line.strip() for line in file.readlines()]
|
243 |
-
|
244 |
-
return dl_manager.download([os.path.join(split_dir, "audio", filename) for filename in audio_filenames])
|
245 |
-
|
246 |
-
|
247 |
-
# for non-streaming case
|
248 |
-
def download_extract_audio_archives(dl_manager, root_dir, split):
|
249 |
-
"""
|
250 |
-
Download and extract audio archives locally.
|
251 |
-
|
252 |
-
Return:
|
253 |
-
archive_paths (List `str`): paths to locally extracted archives
|
254 |
-
"""
|
255 |
-
archive_paths = download_audio_archive_paths(dl_manager, root_dir, split)
|
256 |
-
return [dl_manager.extract(archive_path) for archive_path in archive_paths]
|
257 |
-
|
258 |
-
|
259 |
-
# for streaming case
|
260 |
-
def download_audio_archives(dl_manager, root_dir, split):
|
261 |
-
"""Prepare archives with audio files for iterating over them.
|
262 |
-
|
263 |
-
Return:
|
264 |
-
audio_archives (List `Generator`): list of generators to iterate over files in each audio archive.
|
265 |
-
"""
|
266 |
-
archive_paths = download_audio_archive_paths(dl_manager, root_dir, split)
|
267 |
-
return [dl_manager.iter_archive(archive_path) for archive_path in archive_paths]
|
|
|
16 |
# Lint as: python3
|
17 |
"""Multilingual Librispeech automatic speech recognition dataset."""
|
18 |
|
|
|
|
|
19 |
import os
|
20 |
|
21 |
import datasets
|
|
|
22 |
|
23 |
|
24 |
_CITATION = """\
|
|
|
59 |
version=datasets.Version("2.1.0", ""), name=name, **kwargs
|
60 |
)
|
61 |
# relative path to full data inside a repo (for example `data/mls_german`)
|
62 |
+
self.data_root_url = _DL_URL_FORMAT.format(name=name)
|
63 |
|
64 |
|
65 |
class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
|
|
|
95 |
)
|
96 |
|
97 |
def _split_generators(self, dl_manager):
|
98 |
+
|
99 |
+
transcripts = dl_manager.download({
|
100 |
+
"train": self.config.data_root_url + "/train/transcripts.txt",
|
101 |
+
"dev": self.config.data_root_url + "/dev/transcripts.txt",
|
102 |
+
"test": self.config.data_root_url + "/test/transcripts.txt",
|
103 |
+
})
|
104 |
+
|
105 |
+
# Download handles.txt files containing ids for limited supervision train sets
|
106 |
+
limited_supervision_9h = dl_manager.download(
|
107 |
+
[self.config.data_root_url + "/train/limited_supervision/9hr/handles.txt"],
|
|
|
|
|
|
|
|
|
|
|
108 |
)
|
109 |
+
# in our case of 1 hour limited supervision ("train.1h") there are always 6 subfolders like:
|
110 |
+
# "limited_supervision/1h/0/handles.txt", "limited_supervision/1h/1/handles.txt", ...
|
111 |
+
limited_supervision_1h = dl_manager.download([
|
112 |
+
self.config.data_root_url + f"/train/limited_supervision/1hr/{i}/handles.txt" for i in range(6)
|
113 |
+
])
|
114 |
+
|
115 |
+
# each split contains many .tar.gz archives with its audio files
|
116 |
+
# audio_filenames.txt contains the names of these archives
|
117 |
+
audio_filenames_paths = dl_manager.download({
|
118 |
+
"train": self.config.data_root_url + "/train/audio_filenames.txt",
|
119 |
+
"dev": self.config.data_root_url + "/dev/audio_filenames.txt",
|
120 |
+
"test": self.config.data_root_url + "/test/audio_filenames.txt",
|
121 |
+
})
|
122 |
+
|
123 |
+
audio_archives = {}
|
124 |
+
for split in audio_filenames_paths:
|
125 |
+
with open(audio_filenames_paths[split], encoding="utf-8") as f:
|
126 |
+
audio_filenames = [line.strip() for line in f.readlines()]
|
127 |
+
audio_archives[split] = dl_manager.download([
|
128 |
+
self.config.data_root_url + "/" + split + "/audio/" + filename
|
129 |
+
for filename in audio_filenames
|
130 |
+
])
|
131 |
+
|
132 |
+
# (Optional) In non-streaming mode, we can extract the archive locally to have actual local audio files:
|
133 |
+
local_extracted_archives = dl_manager.extract(audio_archives) if not dl_manager.is_streaming else {}
|
134 |
|
135 |
train_splits = [
|
136 |
datasets.SplitGenerator(
|
137 |
+
name=datasets.Split.TRAIN,
|
138 |
+
gen_kwargs={
|
139 |
+
"transcript_path": transcripts["train"],
|
140 |
+
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["train"]],
|
141 |
+
"local_extracted_archive": local_extracted_archives.get("train"),
|
142 |
+
}
|
143 |
),
|
144 |
datasets.SplitGenerator(
|
145 |
name="train.9h",
|
146 |
gen_kwargs={
|
147 |
+
"transcript_path": transcripts["train"],
|
148 |
+
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["train"]],
|
149 |
+
"local_extracted_archive": local_extracted_archives.get("train"),
|
150 |
+
"limited_ids_paths": limited_supervision_9h,
|
151 |
},
|
152 |
),
|
153 |
datasets.SplitGenerator(
|
154 |
name="train.1h",
|
155 |
gen_kwargs={
|
156 |
+
"transcript_path": transcripts["train"],
|
157 |
+
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["train"]],
|
158 |
+
"local_extracted_archive": local_extracted_archives.get("train"),
|
159 |
+
"limited_ids_paths": limited_supervision_1h,
|
160 |
},
|
161 |
),
|
162 |
]
|
|
|
164 |
return train_splits + [
|
165 |
datasets.SplitGenerator(
|
166 |
name=datasets.Split.VALIDATION, gen_kwargs={
|
167 |
+
"transcript_path": transcripts["dev"],
|
168 |
+
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["dev"]],
|
169 |
+
"local_extracted_archive": local_extracted_archives.get("dev"),
|
|
|
170 |
}
|
171 |
),
|
172 |
datasets.SplitGenerator(
|
173 |
name=datasets.Split.TEST, gen_kwargs={
|
174 |
+
"transcript_path": transcripts["test"],
|
175 |
+
"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["test"]],
|
176 |
+
"local_extracted_archive": local_extracted_archives.get("test"),
|
|
|
177 |
}
|
178 |
),
|
179 |
]
|
180 |
|
181 |
+
def _generate_examples(self, transcript_path, audio_archives, local_extracted_archive, limited_ids_paths=None):
|
182 |
"""Generate examples from a Multilingual LibriSpeech data dir."""
|
183 |
transcripts = dict()
|
184 |
with open(transcript_path, "r", encoding="utf-8") as file:
|
|
|
209 |
# this only can be true in limited supervision sets ("train.9h" and "train.1h")
|
210 |
continue
|
211 |
|
212 |
+
local_audio_file_path = os.path.join(
|
213 |
+
local_extracted_archive[archive_idx], audio_filename
|
214 |
+
) if local_extracted_archive else None
|
215 |
+
|
216 |
yield audio_filename, {
|
217 |
+
"file": local_audio_file_path,
|
218 |
+
"audio": {
|
219 |
+
"path": local_audio_file_path if local_audio_file_path else audio_filename,
|
220 |
+
"bytes": file.read()
|
221 |
+
},
|
222 |
"text": audio_transcript,
|
223 |
"speaker_id": speaker_id,
|
224 |
"chapter_id": chapter_id,
|
225 |
"id": audio_id
|
226 |
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|