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import os |
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import pandas as pd |
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from datasets import GeneratorBasedBuilder, DatasetInfo, SplitGenerator, Split, Features, Value, Audio, Version |
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_URLS = {"train": "https://huggingface.co/datasets/aburnazy/hy_wiki_openai_tts/resolve/main/data/dataset.tar.gz"} |
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class HyAsrGrqaser(GeneratorBasedBuilder): |
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"""Armenian Audio-Transcription Dataset""" |
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VERSION = Version("1.0.0") |
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def _info(self): |
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return DatasetInfo( |
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description="This dataset contains Armenian speech and transcriptions.", |
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features=Features({ |
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'audio': Audio(sampling_rate=16_000), |
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'sentence': Value('string') |
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}), |
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supervised_keys=("audio", "sentence"), |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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metadata_path = dl_manager.download_and_extract( |
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"https://huggingface.co/datasets/aburnazy/hy_wiki_openai_tts/resolve/main/metadata.csv") |
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data_dir = dl_manager.download_and_extract(_URLS) |
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print(f"----------data_dir: {data_dir}, \n----------metadata_path: {metadata_path}") |
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return [ |
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SplitGenerator( |
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name=Split.TRAIN, |
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gen_kwargs={"data_dir": data_dir['train'], "metadata_path": metadata_path} |
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), |
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] |
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def _generate_examples(self, data_dir, metadata_path): |
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print(f"data_dir: {data_dir}, metadata_path: {metadata_path}") |
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"""Yields examples.""" |
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metadata = pd.read_csv(metadata_path) |
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for idx, row in metadata.iterrows(): |
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file_path = os.path.join(data_dir, row['file_name']) |
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transcription = row['transcription'] |
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yield idx, { |
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'audio': {'path': file_path}, |
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'sentence': transcription |
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} |
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