| import glob | |
| import os | |
| from functools import partial | |
| import datasets | |
| LANGS = [ | |
| "he" | |
| ] | |
| VERSION = datasets.Version("0.0.1") | |
| class PublicSpeech(datasets.GeneratorBasedBuilder): | |
| """Public Speech dataset.""" | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig(name=lang, version=VERSION, description=f"Public Speech {lang} dataset") | |
| for lang in LANGS | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description="youtube audio of kan digital samples", | |
| features=datasets.Features( | |
| { | |
| "audio": datasets.Audio(sampling_rate=16000), | |
| "sentence": datasets.Value("string"), | |
| } | |
| ), | |
| supervised_keys=("audio", "sentence"), | |
| homepage="https://huggingface.co/datasets/imvladikon/hebrew_speech_kan", | |
| citation="TODO", | |
| ) | |
| def _split_generators(self, dl_manager): | |
| downloader = partial( | |
| lambda split: dl_manager.download_and_extract(f"data/{self.config.name}/{split}.tar.gz"), | |
| ) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"root_path": downloader("train"), "split": "train"}, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={"root_path": downloader("dev"), "split": "dev"}, | |
| ), | |
| ] | |
| def _generate_examples(self, root_path, split): | |
| split_path = os.path.join(root_path, split) | |
| for wav in glob.glob(split_path + "/*.wav"): | |
| uid = os.path.splitext(os.path.basename(wav))[0] | |
| with open(os.path.join(split_path, f"{uid}.txt"), encoding="utf-8") as fin: | |
| text = fin.read() | |
| example = { | |
| "audio": wav, | |
| "sentence": text, | |
| } | |
| yield uid, example | |