polinaeterna HF staff commited on
Commit
b0d2b2b
1 Parent(s): c8869d5

refactor examples generation

Browse files
Files changed (1) hide show
  1. ami.py +180 -187
ami.py CHANGED
@@ -86,181 +86,181 @@ _LICENSE = "CC BY 4.0"
86
  _TRAIN_SAMPLE_IDS = [
87
  "EN2001a",
88
  "EN2001b",
89
- "EN2001d",
90
- "EN2001e",
91
- "EN2003a",
92
- "EN2004a",
93
- "EN2005a",
94
- "EN2006a",
95
- "EN2006b",
96
- "EN2009b",
97
- "EN2009c",
98
- "EN2009d",
99
- "ES2002a",
100
- "ES2002b",
101
- "ES2002c",
102
- "ES2002d",
103
- "ES2003a",
104
- "ES2003b",
105
- "ES2003c",
106
- "ES2003d",
107
- "ES2005a",
108
- "ES2005b",
109
- "ES2005c",
110
- "ES2005d",
111
- "ES2006a",
112
- "ES2006b",
113
- "ES2006c",
114
- "ES2006d",
115
- "ES2007a",
116
- "ES2007b",
117
- "ES2007c",
118
- "ES2007d",
119
- "ES2008a",
120
- "ES2008b",
121
- "ES2008c",
122
- "ES2008d",
123
- "ES2009a",
124
- "ES2009b",
125
- "ES2009c",
126
- "ES2009d",
127
- "ES2010a",
128
- "ES2010b",
129
- "ES2010c",
130
- "ES2010d",
131
- "ES2012a",
132
- "ES2012b",
133
- "ES2012c",
134
- "ES2012d",
135
- "ES2013a",
136
- "ES2013b",
137
- "ES2013c",
138
- "ES2013d",
139
- "ES2014a",
140
- "ES2014b",
141
- "ES2014c",
142
- "ES2014d",
143
- "ES2015a",
144
- "ES2015b",
145
- "ES2015c",
146
- "ES2015d",
147
- "ES2016a",
148
- "ES2016b",
149
- "ES2016c",
150
- "ES2016d",
151
- "IB4005",
152
- "IN1001",
153
- "IN1002",
154
- "IN1005",
155
- "IN1007",
156
- "IN1008",
157
- "IN1009",
158
- "IN1012",
159
- "IN1013",
160
- "IN1014",
161
- "IN1016",
162
- "IS1000a",
163
- "IS1000b",
164
- "IS1000c",
165
- "IS1000d",
166
- "IS1001a",
167
- "IS1001b",
168
- "IS1001c",
169
- "IS1001d",
170
- "IS1002b",
171
- "IS1002c",
172
- "IS1002d",
173
- "IS1003a",
174
- "IS1003b",
175
- "IS1003c",
176
- "IS1003d",
177
- "IS1004a",
178
- "IS1004b",
179
- "IS1004c",
180
- "IS1004d",
181
- "IS1005a",
182
- "IS1005b",
183
- "IS1005c",
184
- "IS1006a",
185
- "IS1006b",
186
- "IS1006c",
187
- "IS1006d",
188
- "IS1007a",
189
- "IS1007b",
190
- "IS1007c",
191
- "IS1007d",
192
- "TS3005a",
193
- "TS3005b",
194
- "TS3005c",
195
- "TS3005d",
196
- "TS3006a",
197
- "TS3006b",
198
- "TS3006c",
199
- "TS3006d",
200
- "TS3007a",
201
- "TS3007b",
202
- "TS3007c",
203
- "TS3007d",
204
- "TS3008a",
205
- "TS3008b",
206
- "TS3008c",
207
- "TS3008d",
208
- "TS3009a",
209
- "TS3009b",
210
- "TS3009c",
211
- "TS3009d",
212
- "TS3010a",
213
- "TS3010b",
214
- "TS3010c",
215
- "TS3010d",
216
- "TS3011a",
217
- "TS3011b",
218
- "TS3011c",
219
- "TS3011d",
220
- "TS3012a",
221
- "TS3012b",
222
- "TS3012c",
223
- "TS3012d",
224
  ]
225
 
226
  _VALIDATION_SAMPLE_IDS = [
227
  "ES2011a",
228
  "ES2011c",
229
- "IB4001",
230
- "IB4003",
231
- "IB4010",
232
- "IS1008a",
233
- "IS1008c",
234
- "TS3004a",
235
- "TS3004c",
236
- "ES2011b",
237
- "ES2011d",
238
- "IB4002",
239
- "IB4004",
240
- "IB4011",
241
- "IS1008b",
242
- "IS1008d",
243
- "TS3004b",
244
- "TS3004d",
245
  ]
246
 
247
  _EVAL_SAMPLE_IDS = [
248
  "EN2002a",
249
  "EN2002b",
250
- "EN2002c",
251
- "EN2002d",
252
- "ES2004a",
253
- "ES2004b",
254
- "ES2004c",
255
- "ES2004d",
256
- "IS1009a",
257
- "IS1009b",
258
- "IS1009c",
259
- "IS1009d",
260
- "TS3003a",
261
- "TS3003b",
262
- "TS3003c",
263
- "TS3003d",
264
  ]
265
 
266
  _SAMPLE_IDS = {
@@ -327,6 +327,7 @@ class AMI(datasets.GeneratorBasedBuilder):
327
  audio_archives_urls[split] = {
328
  m: _AUDIO_ARCHIVE_URL.format(subset=self.config.name, split=split, _id=m) for m in _SAMPLE_IDS[split]
329
  }
 
330
  audio_archives = dl_manager.download(audio_archives_urls)
331
  local_extracted_archives_paths = dl_manager.extract(audio_archives) if not dl_manager.is_streaming else {
332
  split: [None] * len(audio_archives[split]) for split in splits
@@ -339,9 +340,8 @@ class AMI(datasets.GeneratorBasedBuilder):
339
  datasets.SplitGenerator(
340
  name=datasets.Split.TRAIN,
341
  gen_kwargs={
342
- "audio_archives": [dl_manager.iter_archive(archive) for archive in
343
- audio_archives["train"].values()],
344
- "local_extracted_archives_paths": local_extracted_archives_paths["train"],
345
  "annotation": annotations["train"],
346
  "split": "train"
347
  },
@@ -349,9 +349,8 @@ class AMI(datasets.GeneratorBasedBuilder):
349
  datasets.SplitGenerator(
350
  name=datasets.Split.VALIDATION,
351
  gen_kwargs={
352
- "audio_archives": [dl_manager.iter_archive(archive) for archive in
353
- audio_archives["dev"].values()],
354
- "local_extracted_archives_paths": local_extracted_archives_paths["dev"],
355
  "annotation": annotations["dev"],
356
  "split": "dev"
357
  },
@@ -359,9 +358,8 @@ class AMI(datasets.GeneratorBasedBuilder):
359
  datasets.SplitGenerator(
360
  name=datasets.Split.TEST,
361
  gen_kwargs={
362
- "audio_archives": [dl_manager.iter_archive(archive) for archive in
363
- audio_archives["eval"].values()],
364
- "local_extracted_archives_paths": local_extracted_archives_paths["eval"],
365
  "annotation": annotations["eval"],
366
  "split": "eval"
367
  },
@@ -391,21 +389,16 @@ class AMI(datasets.GeneratorBasedBuilder):
391
  "speaker_id": speaker_id,
392
  }
393
 
 
394
  for archive, local_archive_path in zip(audio_archives, local_extracted_archives_paths):
395
- for audio_filename, audio_file in archive:
396
- audio_meta = transcriptions[audio_filename.split("/")[-1]]
 
397
 
398
- yield audio_filename, {
399
- "segment_id": audio_meta["segment_id"],
400
- "audio_id": audio_meta["audio_id"],
401
  "audio": {
402
- "path": os.path.join(local_archive_path,
403
- audio_filename) if local_archive_path else audio_filename,
404
  "bytes": audio_file.read(),
405
  },
406
- "text": audio_meta["text"],
407
- "begin_time": audio_meta["begin_time"],
408
- "end_time": audio_meta["end_time"],
409
- "microphone_id": audio_meta["microphone_id"],
410
- "speaker_id": audio_meta["speaker_id"],
411
- }
 
86
  _TRAIN_SAMPLE_IDS = [
87
  "EN2001a",
88
  "EN2001b",
89
+ # "EN2001d",
90
+ # "EN2001e",
91
+ # "EN2003a",
92
+ # "EN2004a",
93
+ # "EN2005a",
94
+ # "EN2006a",
95
+ # "EN2006b",
96
+ # "EN2009b",
97
+ # "EN2009c",
98
+ # "EN2009d",
99
+ # "ES2002a",
100
+ # "ES2002b",
101
+ # "ES2002c",
102
+ # "ES2002d",
103
+ # "ES2003a",
104
+ # "ES2003b",
105
+ # "ES2003c",
106
+ # "ES2003d",
107
+ # "ES2005a",
108
+ # "ES2005b",
109
+ # "ES2005c",
110
+ # "ES2005d",
111
+ # "ES2006a",
112
+ # "ES2006b",
113
+ # "ES2006c",
114
+ # "ES2006d",
115
+ # "ES2007a",
116
+ # "ES2007b",
117
+ # "ES2007c",
118
+ # "ES2007d",
119
+ # "ES2008a",
120
+ # "ES2008b",
121
+ # "ES2008c",
122
+ # "ES2008d",
123
+ # "ES2009a",
124
+ # "ES2009b",
125
+ # "ES2009c",
126
+ # "ES2009d",
127
+ # "ES2010a",
128
+ # "ES2010b",
129
+ # "ES2010c",
130
+ # "ES2010d",
131
+ # "ES2012a",
132
+ # "ES2012b",
133
+ # "ES2012c",
134
+ # "ES2012d",
135
+ # "ES2013a",
136
+ # "ES2013b",
137
+ # "ES2013c",
138
+ # "ES2013d",
139
+ # "ES2014a",
140
+ # "ES2014b",
141
+ # "ES2014c",
142
+ # "ES2014d",
143
+ # "ES2015a",
144
+ # "ES2015b",
145
+ # "ES2015c",
146
+ # "ES2015d",
147
+ # "ES2016a",
148
+ # "ES2016b",
149
+ # "ES2016c",
150
+ # "ES2016d",
151
+ # "IB4005",
152
+ # "IN1001",
153
+ # "IN1002",
154
+ # "IN1005",
155
+ # "IN1007",
156
+ # "IN1008",
157
+ # "IN1009",
158
+ # "IN1012",
159
+ # "IN1013",
160
+ # "IN1014",
161
+ # "IN1016",
162
+ # "IS1000a",
163
+ # "IS1000b",
164
+ # "IS1000c",
165
+ # "IS1000d",
166
+ # "IS1001a",
167
+ # "IS1001b",
168
+ # "IS1001c",
169
+ # "IS1001d",
170
+ # "IS1002b",
171
+ # "IS1002c",
172
+ # "IS1002d",
173
+ # "IS1003a",
174
+ # "IS1003b",
175
+ # "IS1003c",
176
+ # "IS1003d",
177
+ # "IS1004a",
178
+ # "IS1004b",
179
+ # "IS1004c",
180
+ # "IS1004d",
181
+ # "IS1005a",
182
+ # "IS1005b",
183
+ # "IS1005c",
184
+ # "IS1006a",
185
+ # "IS1006b",
186
+ # "IS1006c",
187
+ # "IS1006d",
188
+ # "IS1007a",
189
+ # "IS1007b",
190
+ # "IS1007c",
191
+ # "IS1007d",
192
+ # "TS3005a",
193
+ # "TS3005b",
194
+ # "TS3005c",
195
+ # "TS3005d",
196
+ # "TS3006a",
197
+ # "TS3006b",
198
+ # "TS3006c",
199
+ # "TS3006d",
200
+ # "TS3007a",
201
+ # "TS3007b",
202
+ # "TS3007c",
203
+ # "TS3007d",
204
+ # "TS3008a",
205
+ # "TS3008b",
206
+ # "TS3008c",
207
+ # "TS3008d",
208
+ # "TS3009a",
209
+ # "TS3009b",
210
+ # "TS3009c",
211
+ # "TS3009d",
212
+ # "TS3010a",
213
+ # "TS3010b",
214
+ # "TS3010c",
215
+ # "TS3010d",
216
+ # "TS3011a",
217
+ # "TS3011b",
218
+ # "TS3011c",
219
+ # "TS3011d",
220
+ # "TS3012a",
221
+ # "TS3012b",
222
+ # "TS3012c",
223
+ # "TS3012d",
224
  ]
225
 
226
  _VALIDATION_SAMPLE_IDS = [
227
  "ES2011a",
228
  "ES2011c",
229
+ # "IB4001",
230
+ # "IB4003",
231
+ # "IB4010",
232
+ # "IS1008a",
233
+ # "IS1008c",
234
+ # "TS3004a",
235
+ # "TS3004c",
236
+ # "ES2011b",
237
+ # "ES2011d",
238
+ # "IB4002",
239
+ # "IB4004",
240
+ # "IB4011",
241
+ # "IS1008b",
242
+ # "IS1008d",
243
+ # "TS3004b",
244
+ # "TS3004d",
245
  ]
246
 
247
  _EVAL_SAMPLE_IDS = [
248
  "EN2002a",
249
  "EN2002b",
250
+ # "EN2002c",
251
+ # "EN2002d",
252
+ # "ES2004a",
253
+ # "ES2004b",
254
+ # "ES2004c",
255
+ # "ES2004d",
256
+ # "IS1009a",
257
+ # "IS1009b",
258
+ # "IS1009c",
259
+ # "IS1009d",
260
+ # "TS3003a",
261
+ # "TS3003b",
262
+ # "TS3003c",
263
+ # "TS3003d",
264
  ]
265
 
266
  _SAMPLE_IDS = {
 
327
  audio_archives_urls[split] = {
328
  m: _AUDIO_ARCHIVE_URL.format(subset=self.config.name, split=split, _id=m) for m in _SAMPLE_IDS[split]
329
  }
330
+
331
  audio_archives = dl_manager.download(audio_archives_urls)
332
  local_extracted_archives_paths = dl_manager.extract(audio_archives) if not dl_manager.is_streaming else {
333
  split: [None] * len(audio_archives[split]) for split in splits
 
340
  datasets.SplitGenerator(
341
  name=datasets.Split.TRAIN,
342
  gen_kwargs={
343
+ "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["train"].values()],
344
+ "local_extracted_archives_paths": local_extracted_archives_paths["train"].values(),
 
345
  "annotation": annotations["train"],
346
  "split": "train"
347
  },
 
349
  datasets.SplitGenerator(
350
  name=datasets.Split.VALIDATION,
351
  gen_kwargs={
352
+ "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["dev"].values()],
353
+ "local_extracted_archives_paths": local_extracted_archives_paths["dev"].values(),
 
354
  "annotation": annotations["dev"],
355
  "split": "dev"
356
  },
 
358
  datasets.SplitGenerator(
359
  name=datasets.Split.TEST,
360
  gen_kwargs={
361
+ "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["eval"].values()],
362
+ "local_extracted_archives_paths": local_extracted_archives_paths["eval"].values(),
 
363
  "annotation": annotations["eval"],
364
  "split": "eval"
365
  },
 
389
  "speaker_id": speaker_id,
390
  }
391
 
392
+ features = ["segment_id", "audio_id", "text", "begin_time", "end_time", "microphone_id", "speaker_id"]
393
  for archive, local_archive_path in zip(audio_archives, local_extracted_archives_paths):
394
+ for audio_path, audio_file in archive:
395
+ # audio_path is like 'EN2001a/train_ami_en2001a_h00_mee068_0414915_0415078.wav'
396
+ audio_meta = transcriptions[audio_path.split("/")[-1]]
397
 
398
+ yield audio_path, {
 
 
399
  "audio": {
400
+ "path": os.path.join(local_archive_path, audio_path) if local_archive_path else audio_path,
 
401
  "bytes": audio_file.read(),
402
  },
403
+ **{feature: audio_meta[feature] for feature in features}
404
+ }