README.md CHANGED
@@ -1,3 +1,34 @@
1
  ---
2
  license: gpl-3.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3
  ---
 
1
  ---
2
  license: gpl-3.0
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+ dataset_info:
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+ config_name: voxforge_spanish
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+ features:
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+ - name: audio_id
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+ dtype: string
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+ - name: audio
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+ dtype:
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+ audio:
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+ sampling_rate: 16000
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+ - name: speaker_id
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+ dtype: string
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+ - name: country
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+ dtype: string
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+ - name: gender
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+ dtype: string
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+ - name: duration
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+ dtype: float32
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+ - name: normalized_text
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+ dtype: string
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+ splits:
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+ - name: train
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+ num_bytes: 3796458902.464
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+ num_examples: 21692
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+ download_size: 3441019616
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+ dataset_size: 3796458902.464
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+ configs:
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+ - config_name: voxforge_spanish
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+ data_files:
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+ - split: train
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+ path: voxforge_spanish/train-*
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+ default: true
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  ---
corpus/files/metadata_train.tsv DELETED
The diff for this file is too large to render. See raw diff
 
corpus/files/tars_train.paths DELETED
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- corpus/speech/train/argentina.tar.gz
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- corpus/speech/train/chile.tar.gz
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- corpus/speech/train/latin_america.tar.gz
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- corpus/speech/train/mexico.tar.gz
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- corpus/speech/train/spain.tar.gz
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- corpus/speech/train/unknown.tar.gz
 
 
 
 
 
 
 
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voxforge_spanish.py DELETED
@@ -1,121 +0,0 @@
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- from collections import defaultdict
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- import os
3
- import json
4
- import csv
5
- import datasets
6
-
7
- _NAME="voxforge_spanish"
8
- _VERSION="1.0.0"
9
-
10
- _DESCRIPTION = """
11
- The VOXFORGE SPANISH CORPUS has a duration of 49 hours and it is constituted by read speech
12
- recorded by more than 2 thousand speakers. Most of the speakers contribute with 10 recordings
13
- of approximately 10 seconds of duration each.
14
- """
15
-
16
- _CITATION = """
17
- @misc{menavoxforgespanish2017,
18
- title={VOXFORGE SPANISH CORPUS: Audio and Transcripts in Spanish with a CIEMPIESS Corpus style, taken from voxforge.org},
19
- author={Hernandez Mena, Carlos Daniel},
20
- year={2017},
21
- url={https://huggingface.co/ciempiess/voxforge_spanish},
22
- }
23
- """
24
-
25
- _HOMEPAGE = "https://huggingface.co/ciempiess/voxforge_spanish"
26
-
27
- _LICENSE = "GPLv3, See https://www.gnu.org/licenses/gpl.txt"
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-
29
- _BASE_DATA_DIR = "corpus/"
30
- _METADATA_TRAIN = os.path.join(_BASE_DATA_DIR,"files", "metadata_train.tsv")
31
-
32
- _TARS_TRAIN = os.path.join(_BASE_DATA_DIR,"files", "tars_train.paths")
33
-
34
- class VoxforgeSpanishConfig(datasets.BuilderConfig):
35
- """BuilderConfig for VOXFORGE SPANISH CORPUS"""
36
-
37
- def __init__(self, name, **kwargs):
38
- name=_NAME
39
- super().__init__(name=name, **kwargs)
40
-
41
- class VoxforgeSpanish(datasets.GeneratorBasedBuilder):
42
- """VOXFORGE SPANISH CORPUS"""
43
-
44
- VERSION = datasets.Version(_VERSION)
45
- BUILDER_CONFIGS = [
46
- VoxforgeSpanishConfig(
47
- name=_NAME,
48
- version=datasets.Version(_VERSION),
49
- )
50
- ]
51
-
52
- def _info(self):
53
- features = datasets.Features(
54
- {
55
- "audio_id": datasets.Value("string"),
56
- "audio": datasets.Audio(sampling_rate=16000),
57
- "speaker_id": datasets.Value("string"),
58
- "country": datasets.Value("string"),
59
- "gender": datasets.Value("string"),
60
- "duration": datasets.Value("float32"),
61
- "normalized_text": datasets.Value("string"),
62
- }
63
- )
64
- return datasets.DatasetInfo(
65
- description=_DESCRIPTION,
66
- features=features,
67
- homepage=_HOMEPAGE,
68
- license=_LICENSE,
69
- citation=_CITATION,
70
- )
71
-
72
- def _split_generators(self, dl_manager):
73
-
74
- metadata_train=dl_manager.download_and_extract(_METADATA_TRAIN)
75
-
76
- tars_train=dl_manager.download_and_extract(_TARS_TRAIN)
77
-
78
- hash_tar_files=defaultdict(dict)
79
-
80
- with open(tars_train,'r') as f:
81
- hash_tar_files['train']=[path.replace('\n','') for path in f]
82
-
83
- hash_meta_paths={"train":metadata_train}
84
- audio_paths = dl_manager.download(hash_tar_files)
85
-
86
- splits=["train"]
87
- local_extracted_audio_paths = (
88
- dl_manager.extract(audio_paths) if not dl_manager.is_streaming else
89
- {
90
- split:[None] * len(audio_paths[split]) for split in splits
91
- }
92
- )
93
-
94
- return [
95
- datasets.SplitGenerator(
96
- name=datasets.Split.TRAIN,
97
- gen_kwargs={
98
- "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["train"]],
99
- "local_extracted_archives_paths": local_extracted_audio_paths["train"],
100
- "metadata_paths": hash_meta_paths["train"],
101
- }
102
- ),
103
- ]
104
-
105
- def _generate_examples(self, audio_archives, local_extracted_archives_paths, metadata_paths):
106
-
107
- features = ["speaker_id","country","gender","duration","normalized_text"]
108
-
109
- with open(metadata_paths) as f:
110
- metadata = {x["audio_id"]: x for x in csv.DictReader(f, delimiter="\t")}
111
-
112
- for audio_archive, local_extracted_archive_path in zip(audio_archives, local_extracted_archives_paths):
113
- for audio_filename, audio_file in audio_archive:
114
- audio_id =os.path.splitext(os.path.basename(audio_filename))[0]
115
- path = os.path.join(local_extracted_archive_path, audio_filename) if local_extracted_archive_path else audio_filename
116
-
117
- yield audio_id, {
118
- "audio_id": audio_id,
119
- **{feature: metadata[audio_id][feature] for feature in features},
120
- "audio": {"path": path, "bytes": audio_file.read()},
121
- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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