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Use chunk size in feature extraction.

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This commit is contained in:
Fangjun Kuang 2021-11-29 07:07:13 +08:00
parent 632098e0c1
commit 52a306297c
3 changed files with 3 additions and 2 deletions
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2
MANIFEST.in
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@ -1,3 +1,5 @@
include LICENSE
include README.md
include CMakeLists.txt
exclude pyproject.toml
recursive-include kaldifeat *.*

2
kaldifeat/python/kaldifeat/offline_feature.py
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@ -72,7 +72,7 @@ class OfflineFeature(nn.Module):
strided = [self.convert_samples_to_frames(w) for w in waves]
strided = torch.cat(strided, dim=0)
features = self.compute(strided, vtln_warp)
features = self.compute(strided, vtln_warp, chunk_size=chunk_size)
if is_list:
return list(features.split(num_frames_per_wave))

1
setup.py
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@ -34,7 +34,6 @@ setuptools.setup(
version=get_package_version(),
author="Fangjun Kuang",
author_email="csukuangfj@gmail.com",
data_files=[("", ["LICENSE", "README.md"])],
package_dir={package_name: "kaldifeat/python/kaldifeat"},
packages=[package_name],
url="https://github.com/csukuangfj/kaldifeat",