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Mikolaj Pudo commited on
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67ea4e6
1 Parent(s): 13497d8

MOCKS.py refactoring

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  1. MOCKS.py +143 -380
MOCKS.py CHANGED
@@ -41,401 +41,164 @@ audio testset for evaluation and benchmarking Open-Vocabulary Keyword Spotting (
41
 
42
 
43
  _BASE_URL = "https://huggingface.co/datasets/voiceintelligenceresearch/MOCKS/tree/main"
44
- _DL_URLS = {
45
- "de.MCV": {
46
- "offline": "de/MCV/test/offline/data.tar.gz",
47
- "online": "de/MCV/test/online/data.tar.gz",
48
- "offline_transcription" : "de/MCV/test/data_offline_transcription.tsv",
49
- "online_transcription" : "de/MCV/test/data_online_transcription.tsv",
50
- },
51
- "en.LS-clean": {
52
- "offline": "en/LS-clean/test/offline/data.tar.gz",
53
- "online": "en/LS-clean/test/online/data.tar.gz",
54
- "offline_transcription" : "en/LS-clean/test/data_offline_transcription.tsv",
55
- "online_transcription" : "en/LS-clean/test/data_online_transcription.tsv",
56
- },
57
- "en.LS-other": {
58
- "offline": "en/LS-other/test/offline/data.tar.gz",
59
- "online": "en/LS-other/test/online/data.tar.gz",
60
- "offline_transcription" : "en/LS-other/test/data_offline_transcription.tsv",
61
- "online_transcription" : "en/LS-other/test/data_online_transcription.tsv",
62
- },
63
- "en.MCV": {
64
- "offline": "en/MCV/test/offline/data.tar.gz",
65
- "online": "en/MCV/test/online/data.tar.gz",
66
- "offline_transcription" : "en/MCV/test/data_offline_transcription.tsv",
67
- "online_transcription" : "en/MCV/test/data_online_transcription.tsv",
68
- },
69
- "es.MCV": {
70
- "offline": "es/MCV/test/offline/data.tar.gz",
71
- "online": "es/MCV/test/online/data.tar.gz",
72
- "offline_transcription" : "es/MCV/test/data_offline_transcription.tsv",
73
- "online_transcription" : "es/MCV/test/data_online_transcription.tsv",
74
- },
75
- "fr.MCV": {
76
- "offline": "fr/MCV/test/offline/data.tar.gz",
77
- "online": "fr/MCV/test/online/data.tar.gz",
78
- "offline_transcription": "fr/MCV/test/data_offline_transcription.tsv",
79
- "online_transcription": "fr/MCV/test/data_online_transcription.tsv",
80
- },
81
- "it.MCV": {
82
- "offline": "it/MCV/test/offline/data.tar.gz",
83
- "online": "it/MCV/test/online/data.tar.gz",
84
- "offline_transcription": "it/MCV/test/data_offline_transcription.tsv",
85
- "online_transcription": "it/MCV/test/data_online_transcription.tsv",
86
- },
87
- "all": {
88
- "de.MCV.offline": "de/MCV/test/offline/data.tar.gz",
89
- "de.MCV.online": "de/MCV/test/online/data.tar.gz",
90
- "en.LS-clean.offline": "en/LS-clean/test/offline/data.tar.gz",
91
- "en.LS-clean.online": "en/LS-clean/test/online/data.tar.gz",
92
- "en.LS-other.offline": "en/LS-other/test/offline/data.tar.gz",
93
- "en.LS-other.online": "en/LS-other/test/online/data.tar.gz",
94
- "en.MCV.offline": "en/MCV/test/offline/data.tar.gz",
95
- "en.MCV.online": "en/MCV/test/online/data.tar.gz",
96
- "es.MCV.offline": "es/MCV/test/offline/data.tar.gz",
97
- "es.MCV.online": "es/MCV/test/online/data.tar.gz",
98
- "fr.MCV.offline": "fr/MCV/test/offline/data.tar.gz",
99
- "fr.MCV.online": "fr/MCV/test/online/data.tar.gz",
100
- "it.MCV.offline": "it/MCV/test/offline/data.tar.gz",
101
- "it.MCV.online": "it/MCV/test/online/data.tar.gz",
102
- "de.MCV.offline_transcription": "de/MCV/test/data_offline_transcription.tsv",
103
- "de.MCV.online_transcription": "de/MCV/test/data_online_transcription.tsv",
104
- "en.LS-clean.offline_transcription": "en/LS-clean/test/data_offline_transcription.tsv",
105
- "en.LS-clean.online_transcription": "en/LS-clean/test/data_online_transcription.tsv",
106
- "en.LS-other.offline_transcription": "en/LS-other/test/data_offline_transcription.tsv",
107
- "en.LS-other.online_transcription": "en/LS-other/test/data_online_transcription.tsv",
108
- "en.MCV.offline_transcription": "en/MCV/test/data_offline_transcription.tsv",
109
- "en.MCV.online_transcription": "en/MCV/test/data_online_transcription.tsv",
110
- "es.MCV.offline_transcription": "es/MCV/test/data_offline_transcription.tsv",
111
- "es.MCV.online_transcription": "es/MCV/test/data_online_transcription.tsv",
112
- "fr.MCV.offline_transcription": "fr/MCV/test/data_offline_transcription.tsv",
113
- "fr.MCV.online_transcription": "fr/MCV/test/data_online_transcription.tsv",
114
- "it.MCV.offline_transcription": "it/MCV/test/data_offline_transcription.tsv",
115
- "it.MCV.online_transcription": "it/MCV/test/data_online_transcription.tsv",
116
- }
117
  }
118
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
119
 
120
  class Mocks(datasets.GeneratorBasedBuilder):
121
  """Mocks Dataset."""
122
- DEFAULT_CONFIG_NAME = "all"
123
-
124
- BUILDER_CONFIGS = [
125
- datasets.BuilderConfig(name="de.MCV", description="German Mozilla Common Voice."),
126
- datasets.BuilderConfig(name="en.LS-clean", description="English LibriSpeech 'Clean'."),
127
- datasets.BuilderConfig(name="en.LS-other", description="English LibriSpeech 'Other'."),
128
- datasets.BuilderConfig(name="en.MCV", description="English Mozilla Common Voice."),
129
- datasets.BuilderConfig(name="es.MCV", description="Spanish Mozilla Common Voice."),
130
- datasets.BuilderConfig(name="fr.MCV", description="French Mozilla Common Voice."),
131
- datasets.BuilderConfig(name="it.MCV", description="Italian Mozilla Common Voice."),
132
- datasets.BuilderConfig(name="all", description="All test set."),
133
- ]
134
 
135
  def _info(self):
136
  return datasets.DatasetInfo(
137
  description=_DESCRIPTION,
138
- features=datasets.Features(
139
- {
140
- "audio_id": datasets.Value("string"),
141
- "audio": datasets.Audio(sampling_rate=16_000),
142
- "transcription": datasets.Value("string"),
 
 
143
  }
144
  ),
145
  homepage=_BASE_URL,
146
  citation=_CITATION
147
  )
148
 
 
149
  def _split_generators(self, dl_manager):
150
- archive_path = dl_manager.download(_DL_URLS[self.config.name])
151
-
152
- if self.config.name == "de.MCV":
153
- offline_split = [
154
- datasets.SplitGenerator(
155
- name="offline",
156
- gen_kwargs={
157
- "audio_files": dl_manager.iter_archive(archive_path["offline"]),
158
- "transcription": archive_path["offline_transcription"],
159
- "s_type": "offline"
160
- }
161
- )
162
- ]
163
- online_split = [
164
- datasets.SplitGenerator(
165
- name="online",
166
- gen_kwargs={
167
- "audio_files": dl_manager.iter_archive(archive_path["online"]),
168
- "transcription": archive_path["online_transcription"],
169
- "s_type": "online"
170
- }
171
- )
172
- ]
173
-
174
- elif self.config.name == "en.LS-clean":
175
- offline_split = [
176
- datasets.SplitGenerator(
177
- name="offline",
178
- gen_kwargs={
179
- "audio_files": dl_manager.iter_archive(archive_path["offline"]),
180
- "transcription": archive_path["offline_transcription"],
181
- "s_type": "offline"
182
- }
183
- )
184
- ]
185
- online_split = [
186
- datasets.SplitGenerator(
187
- name="online",
188
- gen_kwargs={
189
- "audio_files": dl_manager.iter_archive(archive_path["online"]),
190
- "transcription": archive_path["online_transcription"],
191
- "s_type": "online"
192
- }
193
- )
194
- ]
195
-
196
- elif self.config.name == "en.LS-other":
197
- offline_split = [
198
- datasets.SplitGenerator(
199
- name="offline",
200
- gen_kwargs={
201
- "audio_files": dl_manager.iter_archive(archive_path["offline"]),
202
- "transcription": archive_path["offline_transcription"],
203
- "s_type": "offline"
204
- }
205
- )
206
- ]
207
- online_split = [
208
- datasets.SplitGenerator(
209
- name="online",
210
- gen_kwargs={
211
- "audio_files": dl_manager.iter_archive(archive_path["online"]),
212
- "transcription": archive_path["online_transcription"],
213
- "s_type": "online"
214
- }
215
- )
216
- ]
217
-
218
- elif self.config.name == "en.MCV":
219
- offline_split = [
220
- datasets.SplitGenerator(
221
- name="offline",
222
- gen_kwargs={
223
- "audio_files": dl_manager.iter_archive(archive_path["offline"]),
224
- "transcription": archive_path["offline_transcription"],
225
- "s_type": "offline"
226
- }
227
- )
228
- ]
229
- online_split = [
230
- datasets.SplitGenerator(
231
- name="online",
232
- gen_kwargs={
233
- "audio_files": dl_manager.iter_archive(archive_path["online"]),
234
- "transcription": archive_path["online_transcription"],
235
- "s_type": "online"
236
- }
237
- )
238
- ]
239
-
240
- elif self.config.name == "es.MCV":
241
- offline_split = [
242
- datasets.SplitGenerator(
243
- name="offline",
244
- gen_kwargs={
245
- "audio_files": dl_manager.iter_archive(archive_path["offline"]),
246
- "transcription": archive_path["offline_transcription"],
247
- "s_type": "offline"
248
- }
249
- )
250
- ]
251
- online_split = [
252
- datasets.SplitGenerator(
253
- name="online",
254
- gen_kwargs={
255
- "audio_files": dl_manager.iter_archive(archive_path["online"]),
256
- "transcription": archive_path["online_transcription"],
257
- "s_type": "online"
258
- }
259
- )
260
- ]
261
-
262
- elif self.config.name == "fr.MCV":
263
- offline_split = [
264
- datasets.SplitGenerator(
265
- name="offline",
266
- gen_kwargs={
267
- "audio_files": dl_manager.iter_archive(archive_path["offline"]),
268
- "transcription": archive_path["offline_transcription"],
269
- "s_type": "offline"
270
- }
271
- )
272
- ]
273
- online_split = [
274
- datasets.SplitGenerator(
275
- name="online",
276
- gen_kwargs={
277
- "audio_files": dl_manager.iter_archive(archive_path["online"]),
278
- "transcription": archive_path["online_transcription"],
279
- "s_type": "online"
280
- }
281
- )
282
- ]
283
-
284
- elif self.config.name == "it.MCV":
285
- offline_split = [
286
- datasets.SplitGenerator(
287
- name="offline",
288
- gen_kwargs={
289
- "audio_files": dl_manager.iter_archive(archive_path["offline"]),
290
- "transcription": archive_path["offline_transcription"],
291
- "s_type": "offline"
292
- }
293
- )
294
- ]
295
- online_split = [
296
- datasets.SplitGenerator(
297
- name="online",
298
- gen_kwargs={
299
- "audio_files": dl_manager.iter_archive(archive_path["online"]),
300
- "transcription": archive_path["online_transcription"],
301
- "s_type": "online"
302
- }
303
- )
304
- ]
305
-
306
- elif self.config.name == "all":
307
- offline_split = [
308
- datasets.SplitGenerator(
309
- name="de.MCV.offline",
310
- gen_kwargs={
311
- "audio_files": dl_manager.iter_archive(archive_path["de.MCV.offline"]),
312
- "transcription": archive_path["de.MCV.offline_transcription"],
313
- "s_type": "offline"
314
- }
315
- ),
316
- datasets.SplitGenerator(
317
- name="en.LS-clean.offline",
318
- gen_kwargs={
319
- "audio_files": dl_manager.iter_archive(archive_path["en.LS-clean.offline"]),
320
- "transcription": archive_path["en.LS-clean.offline_transcription"],
321
- "s_type": "offline"
322
- }
323
- ),
324
- datasets.SplitGenerator(
325
- name="en.LS-other.offline",
326
- gen_kwargs={
327
- "audio_files": dl_manager.iter_archive(archive_path["en.LS-other.offline"]),
328
- "transcription": archive_path["en.LS-other.offline_transcription"],
329
- "s_type": "offline"
330
- }
331
- ),
332
- datasets.SplitGenerator(
333
- name="en.MCV.offline",
334
- gen_kwargs={
335
- "audio_files": dl_manager.iter_archive(archive_path["en.MCV.offline"]),
336
- "transcription": archive_path["en.MCV.offline_transcription"],
337
- "s_type": "offline"
338
- }
339
- ),
340
- datasets.SplitGenerator(
341
- name="es.MCV.offline",
342
- gen_kwargs={
343
- "audio_files": dl_manager.iter_archive(archive_path["es.MCV.offline"]),
344
- "transcription": archive_path["es.MCV.offline_transcription"],
345
- "s_type": "offline"
346
- }
347
- ),
348
- datasets.SplitGenerator(
349
- name="fr.MCV.offline",
350
- gen_kwargs={
351
- "audio_files": dl_manager.iter_archive(archive_path["fr.MCV.offline"]),
352
- "transcription": archive_path["fr.MCV.offline_transcription"],
353
- "s_type": "offline"
354
- }
355
- ),
356
- datasets.SplitGenerator(
357
- name="it.MCV.offline",
358
- gen_kwargs={
359
- "audio_files": dl_manager.iter_archive(archive_path["it.MCV.offline"]),
360
- "transcription": archive_path["it.MCV.offline_transcription"],
361
- "s_type": "offline"
362
- }
363
- )
364
- ]
365
- online_split = [
366
- datasets.SplitGenerator(
367
- name="de.MCV.online",
368
- gen_kwargs={
369
- "transcription": archive_path["de.MCV.offline_transconline"],
370
- "s_type": "online"
371
- }
372
- ),
373
- datasets.SplitGenerator(
374
- name="en.LS-clean.online",
375
- gen_kwargs={
376
- "audio_files": dl_manager.iter_archive(archive_path["en.LS-clean.online"]),
377
- "transcription": archive_path["en.LS-clean.online_transcription"],
378
- "s_type": "online"
379
- }
380
- ),
381
- datasets.SplitGenerator(
382
- name="en.LS-other.online",
383
- gen_kwargs={
384
- "audio_files": dl_manager.iter_archive(archive_path["en.LS-other.online"]),
385
- "transcription": archive_path["en.LS-other.online_transcription"],
386
- "s_type": "online"
387
- }
388
- ),
389
- datasets.SplitGenerator(
390
- name="en.MCV.online",
391
- gen_kwargs={
392
- "audio_files": dl_manager.iter_archive(archive_path["en.MCV.online"]),
393
- "transcription": archive_path["en.MCV.online_transcription"],
394
- "s_type": "online"
395
- }
396
- ),
397
- datasets.SplitGenerator(
398
- name="es.MCV.online",
399
- gen_kwargs={
400
- "audio_files": dl_manager.iter_archive(archive_path["es.MCV.online"]),
401
- "transcription": archive_path["es.MCV.online_transcription"],
402
- "s_type": "online"
403
- }
404
- ),
405
- datasets.SplitGenerator(
406
- name="fr.MCV.online",
407
- gen_kwargs={
408
- "audio_files": dl_manager.iter_archive(archive_path["fr.MCV.online"]),
409
- "transcription": archive_path["fr.MCV.online_transcription"],
410
- "s_type": "online"
411
- }
412
- ),
413
- datasets.SplitGenerator(
414
- name="it.MCV.online",
415
- gen_kwargs={
416
- "audio_files": dl_manager.iter_archive(archive_path["it.MCV.online"]),
417
- "transcription": archive_path["it.MCV.online_transcription"],
418
- "s_type": "online"
419
- }
420
- )
421
- ]
422
-
423
- return online_split + offline_split
424
-
425
- def _generate_examples(self, audio_files, transcription, s_type):
426
- """Lorem ipsum."""
427
- metadata = {}
428
- with open(transcription, encoding="utf-8") as f:
429
- f = csv.reader(f, delimiter="\t")
430
- for row in f:
431
- audio_id = row[0].split("/")[-1]
432
- keyword_transcription = row[1]
433
- metadata[audio_id] = {"audio_id": audio_id, "transcription": keyword_transcription}
434
 
435
  id_ = 0
436
- for path, f in audio_files:
437
- _, audio_name = os.path.split(path)
438
- if audio_name in metadata:
439
- audio = {"bytes": f.read()}
440
- yield id_, {**metadata[audio_name], "audio": audio}
441
- id_ +=1
 
 
 
 
 
 
 
 
 
41
 
42
 
43
  _BASE_URL = "https://huggingface.co/datasets/voiceintelligenceresearch/MOCKS/tree/main"
44
+ _DL_URLS_TEMPLATE = {
45
+ "data": "%s/%s/test/%s/data.tar.gz",
46
+ "transcription" : "%s/%s/test/data_%s_transcription.tsv",
47
+ "positive" : "%s/%s/test/%s/all.pair.positive.tsv",
48
+ "similar" : "%s/%s/test/%s/all.pair.similar.tsv",
49
+ "different" : "%s/%s/test/%s/all.pair.different.tsv",
50
+ "positive_subset" : "%s/%s/test/%s/subset.pair.positive.tsv",
51
+ "similar_subset" : "%s/%s/test/%s/subset.pair.similar.tsv",
52
+ "different_subset" : "%s/%s/test/%s/subset.pair.different.tsv",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
53
  }
54
 
55
+ _MOCKS_SETS = [
56
+ "en.LS-clean",
57
+ "en.LS-other",
58
+ "en.MCV",
59
+ "de.MCV",
60
+ "es.MCV",
61
+ "fr.MCV",
62
+ "it.MCV"]
63
+
64
+ _MOCKS_SUFFIXES = [
65
+ "",
66
+ ".positive",
67
+ ".similar",
68
+ ".different",
69
+ ".subset",
70
+ ".positive_subset",
71
+ ".similar_subset",
72
+ ".different_subset"]
73
+
74
 
75
  class Mocks(datasets.GeneratorBasedBuilder):
76
  """Mocks Dataset."""
77
+ DEFAULT_CONFIG_NAME = "en.LS-clean"
78
+
79
+ BUILDER_CONFIGS = [datasets.BuilderConfig(name=subset+suffix, description=subset+suffix)
80
+ for subset in _MOCKS_SETS for suffix in _MOCKS_SUFFIXES]
 
 
 
 
 
 
 
 
81
 
82
  def _info(self):
83
  return datasets.DatasetInfo(
84
  description=_DESCRIPTION,
85
+ features=datasets.Features({
86
+ "keyword_id": datasets.Value("string"),
87
+ "keyword_transcription": datasets.Value("string"),
88
+ "test_id": datasets.Value("string"),
89
+ "test_transcription": datasets.Value("string"),
90
+ "test_audio": datasets.Audio(sampling_rate=16000),
91
+ "label": datasets.Value("bool"),
92
  }
93
  ),
94
  homepage=_BASE_URL,
95
  citation=_CITATION
96
  )
97
 
98
+
99
  def _split_generators(self, dl_manager):
100
+ logger.info("split_generator")
101
+ name_split = self.config.name.split(".")
102
+ subset_lang = name_split[0]
103
+ subset_name = name_split[1]
104
+
105
+ if len(name_split) == 2:
106
+ pairs_types = ["positive", "similar", "different"]
107
+ elif name_split[2] == "subset":
108
+ pairs_types = ["positive_subset", "similar_subset", "different_subset"]
109
+ else:
110
+ pairs_types = [name_split[2]]
111
+
112
+ offline_archive_path = dl_manager.download({
113
+ k: v%(subset_lang, subset_name, "offline")
114
+ for k, v in _DL_URLS_TEMPLATE.items()
115
+ })
116
+ online_archive_path = dl_manager.download({
117
+ k: v%(subset_lang, subset_name, "online")
118
+ for k, v in _DL_URLS_TEMPLATE.items()
119
+ })
120
+
121
+ split_offline = [datasets.SplitGenerator(
122
+ name="offline",
123
+ gen_kwargs={
124
+ "audio_files": dl_manager.iter_archive(offline_archive_path["data"]),
125
+ "transcription_keyword": offline_archive_path["transcription"],
126
+ "transcription_test": offline_archive_path["transcription"],
127
+ "pairs": [offline_archive_path[pair_type] for pair_type in pairs_types],
128
+ }
129
+ )
130
+ ]
131
+
132
+ split_online = [datasets.SplitGenerator(
133
+ name="online",
134
+ gen_kwargs={
135
+ "audio_files": dl_manager.iter_archive(online_archive_path["data"]),
136
+ "transcription_keyword": offline_archive_path["transcription"],
137
+ "transcription_test": online_archive_path["transcription"],
138
+ "pairs": [online_archive_path[pair_type] for pair_type in pairs_types],
139
+ }
140
+ )
141
+ ]
142
+
143
+ return split_offline + split_online
144
+
145
+
146
+ def _read_transcription(self, transcription_path):
147
+ transcription_metadata = {}
148
+
149
+ with open(transcription_path, encoding="utf-8") as f:
150
+ reader = csv.reader(f, delimiter="\t")
151
+ next(reader, None)
152
+
153
+ for row in reader:
154
+ _, audio_id = os.path.split(row[0])
155
+ transcription = row[1]
156
+ transcription_metadata[audio_id] = {
157
+ "audio_id": audio_id,
158
+ "transcription": transcription}
159
+
160
+ return transcription_metadata
161
+
162
+
163
+ def _generate_examples(self, audio_files, transcription_keyword, transcription_test, pairs):
164
+ transcription_keyword_metadata = self._read_transcription(transcription_keyword)
165
+
166
+ transcription_test_metadata = self._read_transcription(transcription_test)
167
+
168
+ pair_metadata = {}
169
+ for pair in pairs:
170
+ with open(pair, encoding="utf-8") as f:
171
+ reader = csv.reader(f, delimiter="\t")
172
+ next(reader, None)
173
+
174
+ for row in reader:
175
+ _, keyword_id = os.path.split(row[0])
176
+ _, test_id = os.path.split(row[1])
177
+
178
+ if keyword_id not in transcription_keyword_metadata:
179
+ logger.error("No transcription and audio for keyword %s"%(keyword_id))
180
+ continue
181
+ if test_id not in transcription_test_metadata:
182
+ logger.error("No transcription and audio for test case %s"%(test_id))
183
+ continue
184
+
185
+ if test_id not in pair_metadata:
186
+ pair_metadata[test_id] = []
187
+
188
+ pair_metadata[test_id].append([keyword_id, int(row[-1])])
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
189
 
190
  id_ = 0
191
+ for test_path, test_f in audio_files:
192
+ _, test_id = os.path.split(test_path)
193
+ if test_id in pair_metadata:
194
+ test_audio = {"bytes": test_f.read()}
195
+ for keyword_id, label in pair_metadata[test_id]:
196
+ yield id_, {
197
+ "keyword_id": keyword_id,
198
+ "keyword_transcription": transcription_keyword_metadata[keyword_id]["transcription"],
199
+ "test_id": test_id,
200
+ "test_transcription": transcription_test_metadata[test_id]["transcription"],
201
+ "test_audio": test_audio,
202
+ "label": label}
203
+ id_ += 1
204
+