| import glob |
| import os |
| from functools import partial |
| import datasets |
| import codecs |
|
|
| 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="", |
| features=datasets.Features( |
| { |
| "audio": datasets.Audio(sampling_rate=16000), |
| "sentence": datasets.Value("string"), |
| } |
| ), |
| supervised_keys=("audio", "sentence"), |
|
|
| homepage="https://huggingface.co/datasets/BenShermaister/VTTFPBS", |
| 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] |
| txt_file = os.path.join(split_path, f"{uid}.txt") |
| try: |
| with codecs.open(txt_file, "r", encoding="utf-8", errors="replace") as fin: |
| text = fin.read() |
| except UnicodeDecodeError as e: |
| print(f"Error reading {txt_file}: {e}") |
| with open(txt_file, "rb") as fin: |
| byte_sequence = fin.read() |
| text = byte_sequence.decode("utf-8", errors="replace") |
|
|
| example = { |
| "audio": wav, |
| "sentence": text, |
| } |
| yield uid, example |
|
|
