Datasets:
Tasks:
Audio Classification
Sub-tasks:
speaker-identification
Multilinguality:
multilingual
Size Categories:
100K<n<1M
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
extended|common_voice
Tags:
License:
# 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 | |