| import datasets | |
| import collections | |
| import gzip | |
| import textwrap | |
| _DESCRIPTION = "tba" | |
| _URL = "tba" | |
| _CITATION = "tba" | |
| _LICENSE = "tba" | |
| class VoxLinguaConfig(datasets.BuilderConfig): | |
| """VoxLingua107 corpus.""" | |
| def __init__( | |
| self, | |
| features, | |
| url, | |
| data_url=None, | |
| supervised_keys=None, | |
| shuffled=False, | |
| deduplicated=False, | |
| task_templates=None, | |
| **kwargs, | |
| ): | |
| super(VoxLinguaConfig, self).__init__(version=datasets.Version("1.9.0", ""), **kwargs) | |
| self.features = features | |
| self.data_url = data_url | |
| self.url = url | |
| self.supervised_keys = supervised_keys | |
| self.task_templates = task_templates | |
| def _languages(): | |
| """Create the sorted dictionary of language codes, and language names. | |
| Returns: | |
| The sorted dictionary as an instance of `collections.OrderedDict`. | |
| """ | |
| langs = { | |
| "af":"", | |
| "am":"", | |
| "ar":"", | |
| "as":"", | |
| "az":"", | |
| "ba":"", | |
| "be":"", | |
| "bg":"", | |
| "bn":"", | |
| "bo":"", | |
| "br":"", | |
| "bs":"", | |
| "ca":"", | |
| "ceb":"", | |
| "cs":"", | |
| "cy":"", | |
| "da":"", | |
| "de":"", | |
| "el":"", | |
| "en":"", | |
| "eo":"", | |
| "es":"", | |
| "et":"", | |
| "eu":"", | |
| "fa":"", | |
| "fi":"", | |
| "fo":"", | |
| "fr":"", | |
| "gl":"", | |
| "gn":"", | |
| "gu":"", | |
| "gv":"", | |
| "ha":"", | |
| "haw":"", | |
| "hi":"", | |
| "hr":"", | |
| "ht":"", | |
| "hu":"", | |
| "hy":"", | |
| "ia":"", | |
| "id":"", | |
| "is":"", | |
| "it":"", | |
| "iw":"", | |
| "ja":"", | |
| "jw":"", | |
| "ka":"", | |
| "kk":"", | |
| "km":"", | |
| "kn":"", | |
| "ko":"", | |
| "la":"", | |
| "lb":"", | |
| "ln":"", | |
| "lo":"", | |
| "lt":"", | |
| "lv":"", | |
| "mg":"", | |
| "mi":"", | |
| "mk":"", | |
| "ml":"", | |
| "mn":"", | |
| "mr":"", | |
| "ms":"", | |
| "mt":"", | |
| "my":"", | |
| "ne":"", | |
| "nl":"", | |
| "nn":"", | |
| "no":"", | |
| "oc":"", | |
| "pa":"", | |
| "pl":"", | |
| "ps":"", | |
| "pt":"", | |
| "ro":"", | |
| "ru":"", | |
| "sa":"", | |
| "sco":"", | |
| "sd":"", | |
| "si":"", | |
| "sk":"", | |
| "sl":"", | |
| "sn":"", | |
| "so":"", | |
| "sq":"", | |
| "sr":"", | |
| "su":"", | |
| "sv":"", | |
| "sw":"", | |
| "ta":"", | |
| "te":"", | |
| "tg":"", | |
| "th":"", | |
| "tk":"", | |
| "tl":"", | |
| "tr":"", | |
| "tt":"", | |
| "uk":"", | |
| "ur":"", | |
| "uz":"", | |
| "vi":"", | |
| "war":"", | |
| "yi":"", | |
| "yo":"", | |
| "zh":"" | |
| } | |
| return collections.OrderedDict(sorted(langs.items())) | |
| class VoxLingua(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| VoxLinguaConfig( | |
| name = language, | |
| description=textwrap.dedent( | |
| """ tbd """ | |
| ), | |
| shuffled=False, | |
| deduplicated=False, | |
| features=datasets.Features( | |
| { | |
| "file": datasets.Value("string"), | |
| "audio": datasets.Audio(sampling_rate=16_000), | |
| "label": datasets.ClassLabel( | |
| names=[f"{i}" for i in range(107)] | |
| ), | |
| } | |
| ), | |
| supervised_keys=("file", "label"), | |
| url="http://bark.phon.ioc.ee/voxlingua107/", | |
| data_url="http://bark.phon.ioc.ee/voxlingua107/{language}.zip" | |
| ) | |
| for language in _languages() | |
| ] | |
| BUILDER_CONFIG_CLASS = VoxLinguaConfig | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=self.config.features, | |
| supervised_keys=self.config.supervised_keys, | |
| homepage=self.config.url, | |
| citation=_CITATION, | |
| task_templates=self.config.task_templates, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| train_data_urls = [self.config.url + f"{key}.zip" for key in _languages().keys()] | |
| downloaded_files_train = dl_manager.download(train_data_urls) | |
| dev_data_url = [self.config.url + f"dev.zip"] | |
| downloaded_files_dev = dl_manager.download(dev_data_url) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"archive_path": downloaded_files_train}), | |
| datasets.SplitGenerator(name=datasets.Split.DEV, gen_kwargs={"archive_path": downloaded_files_dev}), | |
| ] | |
| def _generate_examples(self, archive_path, split=None): | |
| return "" | |