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| """ LibriVox-Indonesia Dataset""" |
|
|
|
|
| import csv |
| import os |
|
|
| import datasets |
| from datasets.utils.py_utils import size_str |
|
|
| from .languages import LANGUAGES |
| from .release_stats import STATS |
|
|
| _CITATION = """\ |
| """ |
|
|
| _HOMEPAGE = "https://huggingface.co/indonesian-nlp/librivox-indonesia" |
|
|
| _LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/" |
|
|
| _AUDIO_URL = "https://huggingface.co/datasets/cahya/test01/resolve/main/audio.tgz" |
|
|
|
|
| class Test01Config(datasets.BuilderConfig): |
| """BuilderConfig for Test01.""" |
|
|
| def __init__(self, name, version, **kwargs): |
| print("## Kwargs", kwargs) |
| self.language = kwargs.pop("language", None) |
| self.release_date = kwargs.pop("release_date", None) |
| self.num_clips = kwargs.pop("num_clips", None) |
| self.num_speakers = kwargs.pop("num_speakers", None) |
| self.total_hr = kwargs.pop("total_hr", None) |
| self.size_bytes = kwargs.pop("size_bytes", None) |
| self.size_human = size_str(self.size_bytes) |
| description = ( |
| f"LibriVox-Indonesia speech to text dataset in {self.language} released on {self.release_date}. " |
| f"The dataset comprises {self.total_hr} hours of transcribed speech data" |
| ) |
| super(Test01Config, self).__init__( |
| name=name, |
| version=datasets.Version(version), |
| description=description, |
| **kwargs, |
| ) |
|
|
|
|
| class Test01(datasets.GeneratorBasedBuilder): |
| DEFAULT_CONFIG_NAME = "all" |
|
|
| BUILDER_CONFIGS = [ |
| Test01Config( |
| name=lang, |
| version=STATS["version"], |
| language=LANGUAGES[lang], |
| release_date=STATS["date"], |
| num_clips=lang_stats["clips"], |
| num_speakers=lang_stats["users"], |
| total_hr=float(lang_stats["totalHrs"]) if lang_stats["totalHrs"] else None, |
| size_bytes=int(lang_stats["size"]) if lang_stats["size"] else None, |
| ) |
| for lang, lang_stats in STATS["locales"].items() |
| ] |
|
|
| def _info(self): |
| total_languages = len(STATS["locales"]) |
| total_hours = self.config.total_hr |
| description = ( |
| "LibriVox-Indonesia is a speech dataset generated from LibriVox with only languages from Indonesia." |
| f"The dataset currently consists of {total_hours} hours of speech " |
| f" in {total_languages} languages, but more voices and languages are always added." |
| ) |
| features = datasets.Features( |
| { |
| "path": datasets.Value("string"), |
| "language": datasets.Value("string"), |
| "reader": datasets.Value("string"), |
| "sentence": datasets.Value("string"), |
| "audio": datasets.features.Audio(sampling_rate=48_000) |
| } |
| ) |
|
|
| return datasets.DatasetInfo( |
| description=description, |
| features=features, |
| supervised_keys=None, |
| homepage=_HOMEPAGE, |
| license=_LICENSE, |
| citation=_CITATION, |
| version=self.config.version, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| """Returns SplitGenerators.""" |
| dl_manager.download_config.ignore_url_params = True |
|
|
| archive_path = dl_manager.download(_AUDIO_URL) |
| local_extracted_archive = dl_manager.extract(archive_path) if not dl_manager.is_streaming else None |
| path_to_clips = "audio" |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "local_extracted_archive": local_extracted_archive, |
| "archive_iterator": dl_manager.iter_archive(archive_path), |
| "metadata_filepath": "audio_transcription.csv", |
| "path_to_clips": path_to_clips, |
| }, |
| ), |
| ] |
|
|
| def _generate_examples( |
| self, |
| local_extracted_archive, |
| archive_iterator, |
| metadata_filepath, |
| path_to_clips, |
| ): |
| """Yields examples.""" |
| data_fields = list(self._info().features.keys()) |
| metadata = {} |
| filepath = local_extracted_archive + "/audio/audio_transcription.csv" |
| with open(filepath, "r") as f: |
| lines = (line for line in f) |
| utterances = csv.DictReader(lines) |
| for row in utterances: |
| if self.config.name == "all" or self.config.name == row["language"]: |
| row["path"] = os.path.join(path_to_clips, row["path"]) |
| |
| for field in data_fields: |
| if field not in row: |
| row[field] = "" |
| metadata[row["path"]] = row |
| for path, f in archive_iterator: |
| if path in metadata: |
| result = dict(metadata[path]) |
| |
| path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path |
| result["audio"] = {"path": path, "bytes": f.read()} |
| |
| result["path"] = path if local_extracted_archive else None |
|
|
| yield path, result |
|
|
