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