Datasets:
File size: 5,014 Bytes
71942ac fe4401d 71942ac 04259c3 71942ac 0635d66 71942ac 0635d66 71942ac ecf512e 71942ac |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 |
# coding=utf-8
# Copyright 2021 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
""" Common Language Dataset"""
import os
import datasets
_DATA_URL = "data/CommonLanguage.zip"
_CITATION = """\
@dataset{ganesh_sinisetty_2021_5036977,
author = {Ganesh Sinisetty and
Pavlo Ruban and
Oleksandr Dymov and
Mirco Ravanelli},
title = {CommonLanguage},
month = jun,
year = 2021,
publisher = {Zenodo},
version = {0.1},
doi = {10.5281/zenodo.5036977},
url = {https://doi.org/10.5281/zenodo.5036977}
}
"""
_DESCRIPTION = """\
This dataset is composed of speech recordings from languages that were carefully selected from the CommonVoice database.
The total duration of audio recordings is 45.1 hours (i.e., 1 hour of material for each language).
The dataset has been extracted from CommonVoice to train language-id systems.
"""
_HOMEPAGE = "https://zenodo.org/record/5036977"
_LICENSE = "https://creativecommons.org/licenses/by/4.0/legalcode"
_LANGUAGES = [
"Arabic",
"Basque",
"Breton",
"Catalan",
"Chinese_China",
"Chinese_Hongkong",
"Chinese_Taiwan",
"Chuvash",
"Czech",
"Dhivehi",
"Dutch",
"English",
"Esperanto",
"Estonian",
"French",
"Frisian",
"Georgian",
"German",
"Greek",
"Hakha_Chin",
"Indonesian",
"Interlingua",
"Italian",
"Japanese",
"Kabyle",
"Kinyarwanda",
"Kyrgyz",
"Latvian",
"Maltese",
"Mangolian",
"Persian",
"Polish",
"Portuguese",
"Romanian",
"Romansh_Sursilvan",
"Russian",
"Sakha",
"Slovenian",
"Spanish",
"Swedish",
"Tamil",
"Tatar",
"Turkish",
"Ukranian",
"Welsh",
]
class CommonLanguage(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("0.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="full", version=VERSION, description="The entire Common Language dataset"),
]
def _info(self):
features = datasets.Features(
{
"client_id": datasets.Value("string"),
"path": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=48_000),
"sentence": datasets.Value("string"),
"age": datasets.Value("string"),
"gender": datasets.Value("string"),
"language": datasets.ClassLabel(names=_LANGUAGES),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
dl_path = dl_manager.download_and_extract(_DATA_URL)
archive_path = os.path.join(dl_path, "common_voice_kpd")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"archive_path": archive_path, "split": "train"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"archive_path": archive_path, "split": "dev"},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"archive_path": archive_path, "split": "test"},
),
]
def _generate_examples(self, archive_path, split):
"""Yields examples."""
key = 0
for language in _LANGUAGES:
csv_path = os.path.join(archive_path, language, f"{split}.csv")
with open(csv_path, encoding="utf-16") as fin:
next(fin) # skip the header
for line in fin:
client_id, wav_name, sentence, age, gender = line.strip().split("\t")[1:]
path = os.path.join(archive_path, language, split, client_id, wav_name)
yield key, {
"client_id": client_id,
"path": path,
"audio": path,
"sentence": sentence,
"age": age,
"gender": gender,
"language": language,
}
key += 1
|