albertvillanova HF staff commited on
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7525156
1 Parent(s): 063f48e

Revert "Convert dataset to Parquet (#5)"

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This reverts commit 063f48e28abda80b2fdc4d4433af8a99e71bfe16.

README.md CHANGED
@@ -9,6 +9,7 @@ license:
9
  - cc-by-4.0
10
  multilinguality:
11
  - monolingual
 
12
  size_categories:
13
  - 10K<n<100K
14
  source_datasets:
@@ -19,9 +20,21 @@ task_categories:
19
  - text-to-audio
20
  task_ids: []
21
  paperswithcode_id: vctk
22
- pretty_name: VCTK
 
 
 
 
 
 
 
 
 
 
 
 
 
23
  dataset_info:
24
- config_name: main
25
  features:
26
  - name: speaker_id
27
  dtype: string
@@ -45,32 +58,13 @@ dataset_info:
45
  dtype: string
46
  - name: comment
47
  dtype: string
 
48
  splits:
49
  - name: train
50
- num_bytes: 13246600829.632
51
  num_examples: 88156
52
- download_size: 11715680639
53
- dataset_size: 13246600829.632
54
- configs:
55
- - config_name: main
56
- data_files:
57
- - split: train
58
- path: main/train-*
59
- default: true
60
- train-eval-index:
61
- - config: main
62
- task: automatic-speech-recognition
63
- task_id: speech_recognition
64
- splits:
65
- train_split: train
66
- col_mapping:
67
- file: path
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- text: text
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- metrics:
70
- - type: wer
71
- name: WER
72
- - type: cer
73
- name: CER
74
  ---
75
 
76
  # Dataset Card for VCTK
 
9
  - cc-by-4.0
10
  multilinguality:
11
  - monolingual
12
+ pretty_name: VCTK
13
  size_categories:
14
  - 10K<n<100K
15
  source_datasets:
 
20
  - text-to-audio
21
  task_ids: []
22
  paperswithcode_id: vctk
23
+ train-eval-index:
24
+ - config: main
25
+ task: automatic-speech-recognition
26
+ task_id: speech_recognition
27
+ splits:
28
+ train_split: train
29
+ col_mapping:
30
+ file: path
31
+ text: text
32
+ metrics:
33
+ - type: wer
34
+ name: WER
35
+ - type: cer
36
+ name: CER
37
  dataset_info:
 
38
  features:
39
  - name: speaker_id
40
  dtype: string
 
58
  dtype: string
59
  - name: comment
60
  dtype: string
61
+ config_name: main
62
  splits:
63
  - name: train
64
+ num_bytes: 40103111
65
  num_examples: 88156
66
+ download_size: 11747302977
67
+ dataset_size: 40103111
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
68
  ---
69
 
70
  # Dataset Card for VCTK
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vctk.py ADDED
@@ -0,0 +1,133 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2021 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+
16
+ # Lint as: python3
17
+ """VCTK dataset."""
18
+
19
+
20
+ import os
21
+ import re
22
+
23
+ import datasets
24
+ from datasets.tasks import AutomaticSpeechRecognition
25
+
26
+
27
+ _CITATION = """\
28
+ @inproceedings{Veaux2017CSTRVC,
29
+ title = {CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit},
30
+ author = {Christophe Veaux and Junichi Yamagishi and Kirsten MacDonald},
31
+ year = 2017
32
+ }
33
+ """
34
+
35
+ _DESCRIPTION = """\
36
+ The CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents.
37
+ """
38
+
39
+ _URL = "https://datashare.ed.ac.uk/handle/10283/3443"
40
+ _DL_URL = "https://datashare.is.ed.ac.uk/bitstream/handle/10283/3443/VCTK-Corpus-0.92.zip"
41
+
42
+
43
+ class VCTK(datasets.GeneratorBasedBuilder):
44
+ """VCTK dataset."""
45
+
46
+ VERSION = datasets.Version("0.9.2")
47
+
48
+ BUILDER_CONFIGS = [
49
+ datasets.BuilderConfig(name="main", version=VERSION, description="VCTK dataset"),
50
+ ]
51
+
52
+ def _info(self):
53
+ return datasets.DatasetInfo(
54
+ description=_DESCRIPTION,
55
+ features=datasets.Features(
56
+ {
57
+ "speaker_id": datasets.Value("string"),
58
+ "audio": datasets.features.Audio(sampling_rate=48_000),
59
+ "file": datasets.Value("string"),
60
+ "text": datasets.Value("string"),
61
+ "text_id": datasets.Value("string"),
62
+ "age": datasets.Value("string"),
63
+ "gender": datasets.Value("string"),
64
+ "accent": datasets.Value("string"),
65
+ "region": datasets.Value("string"),
66
+ "comment": datasets.Value("string"),
67
+ }
68
+ ),
69
+ supervised_keys=("file", "text"),
70
+ homepage=_URL,
71
+ citation=_CITATION,
72
+ task_templates=[AutomaticSpeechRecognition(audio_column="audio", transcription_column="text")],
73
+ )
74
+
75
+ def _split_generators(self, dl_manager):
76
+ root_path = dl_manager.download_and_extract(_DL_URL)
77
+
78
+ return [
79
+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"root_path": root_path}),
80
+ ]
81
+
82
+ def _generate_examples(self, root_path):
83
+ """Generate examples from the VCTK corpus root path."""
84
+
85
+ meta_path = os.path.join(root_path, "speaker-info.txt")
86
+ txt_root = os.path.join(root_path, "txt")
87
+ wav_root = os.path.join(root_path, "wav48_silence_trimmed")
88
+ # NOTE: "comment" is handled separately in logic below
89
+ fields = ["speaker_id", "age", "gender", "accent", "region"]
90
+
91
+ key = 0
92
+ with open(meta_path, encoding="utf-8") as meta_file:
93
+ _ = next(iter(meta_file))
94
+ for line in meta_file:
95
+ data = {}
96
+ line = line.strip()
97
+ search = re.search(r"\(.*\)", line)
98
+ if search is None:
99
+ data["comment"] = ""
100
+ else:
101
+ start, _ = search.span()
102
+ data["comment"] = line[start:]
103
+ line = line[:start]
104
+ values = line.split()
105
+ for i, field in enumerate(fields):
106
+ if field == "region":
107
+ data[field] = " ".join(values[i:])
108
+ else:
109
+ data[field] = values[i] if i < len(values) else ""
110
+ speaker_id = data["speaker_id"]
111
+ speaker_txt_path = os.path.join(txt_root, speaker_id)
112
+ speaker_wav_path = os.path.join(wav_root, speaker_id)
113
+ # NOTE: p315 does not have text
114
+ if not os.path.exists(speaker_txt_path):
115
+ continue
116
+ for txt_file in sorted(os.listdir(speaker_txt_path)):
117
+ filename, _ = os.path.splitext(txt_file)
118
+ _, text_id = filename.split("_")
119
+ for i in [1, 2]:
120
+ wav_file = os.path.join(speaker_wav_path, f"{filename}_mic{i}.flac")
121
+ # NOTE: p280 does not have mic2 files
122
+ if not os.path.exists(wav_file):
123
+ continue
124
+ with open(os.path.join(speaker_txt_path, txt_file), encoding="utf-8") as text_file:
125
+ text = text_file.readline().strip()
126
+ more_data = {
127
+ "file": wav_file,
128
+ "audio": wav_file,
129
+ "text": text,
130
+ "text_id": text_id,
131
+ }
132
+ yield key, {**data, **more_data}
133
+ key += 1