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Datasets:
LennartKeller
/
SpeechTaxi

Tasks:
Text Classification
Audio Classification
Languages:
Assamese
Haryanvi
Bhattiyali
Size:
10K<n<100K
ArXiv:
Dataset card Files Community
Lennart Keller commited on
Commit
96a54e3
•
1 Parent(s): b5824c6

add zipped data

Browse files
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Files changed (50) hide show
  1. README.md +1 -0
  2. SpeechTaxi.py +6 -30
  3. create_release.py +7 -1
  4. data/039316d8ba074002-rev4/039316d8ba074002-rev4-1CO/001/Verse__10.mp3 → data.zip +2 -2
  5. data/039316d8ba074002-rev4/039316d8ba074002-rev4-1CO/001/Verse__21.mp3 +0 -3
  6. data/039316d8ba074002-rev4/039316d8ba074002-rev4-1CO/001/Verse__30.mp3 +0 -3
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  18. data/039316d8ba074002-rev4/039316d8ba074002-rev4-1CO/004/Verse_10.mp3 +0 -3
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README.md CHANGED
@@ -6,6 +6,7 @@ TODO
6
 
7
  ```python
8
  # pip install datasets pandas
 
9
  dataset = load_dataset(
10
  "LennartKeller/SpeechTaxi",
11
  name="fra",
 
6
 
7
  ```python
8
  # pip install datasets pandas
9
+ from datasets import load_dataset
10
  dataset = load_dataset(
11
  "LennartKeller/SpeechTaxi",
12
  name="fra",
SpeechTaxi.py CHANGED
@@ -6,39 +6,14 @@ from datasets import (
6
  )
7
  import pandas as pd
8
 
9
- DATA_DIR = "data"
10
- TABLE_DIR = "tables"
11
 
12
  NAMES = [
13
  "all",
14
  "asm",
15
  "bgc",
16
  "bht",
17
- "ckb",
18
- "eng",
19
- "ewe",
20
- "fra",
21
- "guj",
22
- "ibo",
23
- "kan",
24
- "lin",
25
- "luo",
26
- "mal",
27
- "mar",
28
- "nag",
29
- "nde",
30
- "nlx",
31
- "pan",
32
- "peg",
33
- "rus",
34
- "tam",
35
- "tel",
36
- "tw-akuapem",
37
- "tw-asante",
38
- "ukr",
39
- "urd",
40
- "vie",
41
- "yor",
42
 
43
  ]
44
 
@@ -74,6 +49,7 @@ class SpeechTaxi(datasets.GeneratorBasedBuilder):
74
  {
75
  "verse_ref": datasets.features.Value("string"),
76
  "text_en": datasets.features.Value("string"),
 
77
  "transcription": datasets.features.Value("string"),
78
  "transcription_romanized": datasets.features.Value("string"),
79
  "label": datasets.features.ClassLabel(
@@ -86,10 +62,10 @@ class SpeechTaxi(datasets.GeneratorBasedBuilder):
86
  "Violence",
87
  ]
88
  ),
 
89
  "transription_mms-zeroshot-300m": datasets.features.Value("string"),
90
  "transription_mms": datasets.features.Value("string"),
91
  "transription_whisper-large-v3": datasets.features.Value("string"),
92
- "audio": datasets.features.Audio(sampling_rate=16_000)
93
  }
94
  ),
95
  supervised_keys=None,
@@ -97,9 +73,9 @@ class SpeechTaxi(datasets.GeneratorBasedBuilder):
97
  citation=CITATION,
98
  )
99
  def _split_generators(self, dl_manager):
100
- table_dir = dl_manager.download(TABLE_DIR)
101
  # Make sure data is downloaded
102
- data_dir = dl_manager.download(DATA_DIR)
103
  return [
104
  SplitGenerator(name="train", gen_kwargs={"split": "train", "table_dir": table_dir, "data_dir": data_dir}),
105
  SplitGenerator(name="test", gen_kwargs={"split": "test", "table_dir": table_dir, "data_dir": data_dir}),
 
6
  )
7
  import pandas as pd
8
 
9
+ DATA_ARCHIVE = "data.zip"
10
+ TABLE_ARCHIVE = "tables.zip"
11
 
12
  NAMES = [
13
  "all",
14
  "asm",
15
  "bgc",
16
  "bht",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
17
 
18
  ]
19
 
 
49
  {
50
  "verse_ref": datasets.features.Value("string"),
51
  "text_en": datasets.features.Value("string"),
52
+ "language": datasets.features.Value("string"),
53
  "transcription": datasets.features.Value("string"),
54
  "transcription_romanized": datasets.features.Value("string"),
55
  "label": datasets.features.ClassLabel(
 
62
  "Violence",
63
  ]
64
  ),
65
+ "audio": datasets.features.Audio(sampling_rate=16_000),
66
  "transription_mms-zeroshot-300m": datasets.features.Value("string"),
67
  "transription_mms": datasets.features.Value("string"),
68
  "transription_whisper-large-v3": datasets.features.Value("string"),
 
69
  }
70
  ),
71
  supervised_keys=None,
 
73
  citation=CITATION,
74
  )
75
  def _split_generators(self, dl_manager):
76
+ table_dir = dl_manager.download_and_extract(TABLE_ARCHIVE)
77
  # Make sure data is downloaded
78
+ data_dir = dl_manager.download_and_extract(DATA_ARCHIVE)
79
  return [
80
  SplitGenerator(name="train", gen_kwargs={"split": "train", "table_dir": table_dir, "data_dir": data_dir}),
81
  SplitGenerator(name="test", gen_kwargs={"split": "test", "table_dir": table_dir, "data_dir": data_dir}),
create_release.py CHANGED
@@ -299,7 +299,7 @@ if __name__ == "__main__":
299
  # Load and filter alignment tables
300
  language_tables = sorted(
301
  [f for f in ALIGNED_TABLES_DIR.glob("*.tsv") if f.stem not in SKIP_LANGUAGES]
302
- )
303
 
304
  # Write code file
305
  success_languages = []
@@ -366,3 +366,9 @@ if __name__ == "__main__":
366
  citation=CITATION,
367
  )
368
  code_file.write_text(code_file_content)
 
 
 
 
 
 
 
299
  # Load and filter alignment tables
300
  language_tables = sorted(
301
  [f for f in ALIGNED_TABLES_DIR.glob("*.tsv") if f.stem not in SKIP_LANGUAGES]
302
+ )[:3]
303
 
304
  # Write code file
305
  success_languages = []
 
366
  citation=CITATION,
367
  )
368
  code_file.write_text(code_file_content)
369
+
370
+ # Zip data and tables dir
371
+ shutil.make_archive(dataset_root / "tables", "zip", table_dir)
372
+ shutil.rmtree(table_dir)
373
+ shutil.make_archive(dataset_root / "data", "zip", data_dir)
374
+ shutil.rmtree(data_dir)
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