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| import csv |
| import os |
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| import datasets |
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| logger = datasets.logging.get_logger(__name__) |
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| _DESCRIPTION = "Custom dataset for extracting audio files and matching sentences." |
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| _DATA_URL = "https://huggingface.co/datasets/kingjambal/dataset/resolve/main" |
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| class CustomDataset(datasets.GeneratorBasedBuilder): |
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| VERSION = datasets.Version("1.0.0") |
|
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| def _info(self): |
| features = datasets.Features( |
| { |
| "audio": datasets.Audio(sampling_rate=48_000), |
| "sentence": datasets.Value("string"), |
| } |
| ) |
|
|
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=features, |
| supervised_keys=("audio", "sentence"), |
| homepage=None, |
| citation=None, |
| ) |
|
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| def _split_generators(self, dl_manager): |
| audio_path = dl_manager.download_and_extract(_DATA_URL+"/takeout_639_pt_0.zip") |
| csv_path = dl_manager.download_and_extract(_DATA_URL+"/takeout_639_metadata.csv") |
| |
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={"audio_path": audio_path, "csv_path": csv_path}, |
| ) |
| ] |
|
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| def _generate_examples(self, audio_path, csv_path): |
| print(audio_path) |
| print(csv_path) |
| key = 0 |
| print(os.listdir(audio_path)) |
| |
| with open(csv_path, encoding="utf-8") as csv_file: |
| csv_reader = csv.DictReader(csv_file) |
| for row in csv_reader: |
| original_sentence_id, sentence, locale = row.values() |
| audio_file = f"{original_sentence_id}.mp3" |
| audio_file_path = os.path.join(audio_path, audio_file) |
| yield key, { |
| "audio": audio_file_path, |
| "sentence": sentence, |
| } |
| key += 1 |
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