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import os |
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import numpy as np |
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import datasets |
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_DATA_URL = "https://huggingface.co/datasets/Matthijs/cmu-arctic-xvectors/resolve/main/spkrec-xvect.zip" |
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class ArcticXvectors(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="default", |
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version=datasets.Version("0.0.1", ""), |
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description="", |
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) |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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features=datasets.Features( |
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{ |
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"filename": datasets.Value("string"), |
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"xvector": datasets.Sequence(feature=datasets.Value(dtype="float32"), length=512), |
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} |
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), |
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) |
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def _split_generators(self, dl_manager): |
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archive = os.path.join(dl_manager.download_and_extract(_DATA_URL), "spkrec-xvect") |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, gen_kwargs={"files": dl_manager.iter_files(archive)} |
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), |
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] |
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def _generate_examples(self, files): |
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for i, file in enumerate(sorted(files)): |
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if os.path.basename(file).endswith(".npy"): |
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yield str(i), { |
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"filename": os.path.basename(file)[:-4], |
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"xvector": np.load(file), |
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} |
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