Delete common-voice-13-fa.py

common-voice-13-fa.py

@@ -1,136 +0,0 @@
-import csv
-import os
-
-import datasets
-from tqdm import tqdm
-
-
-_DESCRIPTION = """\
-Persian portion of the common voice 13 dataset, gathered and maintained by Hezar AI.
-"""
-
-_CITATION = """\
-@inproceedings{commonvoice:2020,
-  author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
-  title = {Common Voice: A Massively-Multilingual Speech Corpus},
-  booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
-  pages = {4211--4215},
-  year = 2020
-}
-"""
-
-_HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets"
-
-_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
-
-_BASE_URL = "https://huggingface.co/datasets/hezarai/common-voice-13-fa/resolve/main/"
-
-_AUDIO_URL = _BASE_URL + "audio/{split}.zip"
-
-_TRANSCRIPT_URL = _BASE_URL + "transcripts/{split}.tsv"
-
-
-class CommonVoiceFaConfig(datasets.BuilderConfig):
-    """BuilderConfig for CommonVoice."""
-
-    def __init__(self, **kwargs):
-        super(CommonVoiceFaConfig, self).__init__(**kwargs)
-
-
-class CommonVoice(datasets.GeneratorBasedBuilder):
-    DEFAULT_WRITER_BATCH_SIZE = 1000
-
-    BUILDER_CONFIGS = [
-        CommonVoiceFaConfig(
-            name="commonvoice-13-fa",
-            version="1.0.0",
-            description=_DESCRIPTION,
-        )
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "client_id": datasets.Value("string"),
-                "path": datasets.Value("string"),
-                "audio": datasets.features.Audio(sampling_rate=48_000),
-                "sentence": datasets.Value("string"),
-                "up_votes": datasets.Value("int64"),
-                "down_votes": datasets.Value("int64"),
-                "age": datasets.Value("string"),
-                "gender": datasets.Value("string"),
-                "accent": datasets.Value("string"),
-                "locale": datasets.Value("string"),
-                "segment": datasets.Value("string"),
-                "variant": datasets.Value("string"),
-            }
-        )
-
-        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):
-        splits = ("train", "validation", "test")
-        audio_urls = {split: _AUDIO_URL.format(split=split) for split in splits}
-
-        archive_paths = dl_manager.download(audio_urls)
-        local_extracted_archive_paths = dl_manager.extract(archive_paths) if not dl_manager.is_streaming else {}
-
-        transcript_urls = {split: _TRANSCRIPT_URL.format(split=split) for split in splits}
-        transcript_paths = dl_manager.download_and_extract(transcript_urls)
-
-        split_generators = []
-        split_names = {
-            "train": datasets.Split.TRAIN,
-            "validation": datasets.Split.VALIDATION,
-            "test": datasets.Split.TEST,
-        }
-        for split in splits:
-            split_generators.append(
-                datasets.SplitGenerator(
-                    name=split_names.get(split, split),
-                    gen_kwargs={
-                        "local_extracted_archive_paths": local_extracted_archive_paths.get(split),
-                        "archives": [dl_manager.iter_archive(archive_paths.get(split))],
-                        "transcript_path": transcript_paths[split],
-                    },
-                ),
-            )
-
-        return split_generators
-
-    def _generate_examples(self, local_extracted_archive_paths, archives, transcript_path):
-        data_fields = list(self._info().features.keys())
-        metadata = {}
-        with open(transcript_path, encoding="utf-8") as f:
-            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
-            for row in tqdm(reader, desc="Reading metadata..."):
-                if not row["path"].endswith(".mp3"):
-                    row["path"] += ".mp3"
-                # accent -> accents in CV 8.0
-                if "accents" in row:
-                    row["accent"] = row["accents"]
-                    del row["accents"]
-                # if data is incomplete, fill with empty values
-                for field in data_fields:
-                    if field not in row:
-                        row[field] = ""
-                metadata[row["path"]] = row
-
-        for i, audio_archive in enumerate(archives):
-            for path, file in audio_archive:
-                _, filename = os.path.split(path)
-                if filename in metadata:
-                    result = dict(metadata[filename])
-                    # set the audio feature and the path to the extracted file
-                    path = os.path.join(local_extracted_archive_paths[i], path) if local_extracted_archive_paths else path
-                    result["audio"] = {"path": path, "bytes": file.read()}
-                    result["path"] = path
-                    yield path, result