Datasets:
Tasks:
Audio Classification
Sub-tasks:
keyword-spotting
Languages:
English
Size:
10K - 100K
ArXiv:
License:
soeren
commited on
Commit
•
c624b60
1
Parent(s):
72d08a5
ensure correct alignment between metadata and raw data
Browse files
data/clip_metadata.py
CHANGED
@@ -7,4 +7,5 @@ df = pd.read_parquet("data/dataset_audio_" + _SPLIT +".parquet.gzip")
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clipped_df = df.filter(["label_string", "probability", "probability_vector", "prediction",
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"prediction_string", "embedding_reduced"], axis=1)
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clipped_df.to_parquet("data/dataset_audio_" + _SPLIT +"_clipped.parquet.gzip")
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clipped_df = df.filter(["label_string", "probability", "probability_vector", "prediction",
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"prediction_string", "embedding_reduced"], axis=1)
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clipped_df = clipped_df.sort_values(by=["label_string"])
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clipped_df.to_parquet("data/dataset_audio_" + _SPLIT +"_clipped.parquet.gzip")
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data/dataset_audio_test_clipped.parquet.gzip
CHANGED
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:f547f9d8c86950a42baf9ddf1a5a52cd04a8edc9200529ddf61cea4902dca30c
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size 659677
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data/dataset_audio_train_clipped.parquet.gzip
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:434345cc785bb9d400d8764edbe413df27c5ade323ce7f4545372f6e7932106c
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size 8172206
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data/dataset_audio_validation_clipped.parquet.gzip
CHANGED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:58aecf14451ee7a32c6723c9954e79324ff7c937ed8b739eb6f2ff277f9f8285
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size 1482039
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speech_commands_enriched.py
CHANGED
@@ -229,11 +229,13 @@ class SpeechCommands(datasets.GeneratorBasedBuilder):
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# HINT: metadata should already be the split-specific metadata
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pathlist = Path(archive_path).glob('**/*.wav')
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for path, row in zip(pathlist, metadata.iterrows()):
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# row is a tuple containg an index and a pandas series
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pathcomponents = str(path).split("/")
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word = pathcomponents[-2]
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audio_filename = pathcomponents[-1]
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@@ -268,6 +270,6 @@ class SpeechCommands(datasets.GeneratorBasedBuilder):
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}
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#for debugging, comment out after
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if __name__ == "__main__":
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ds = datasets.load_dataset("speech_commands_enriched.py", 'v0.01', split="test",
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streaming=False)
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# HINT: metadata should already be the split-specific metadata
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pathlist = Path(archive_path).glob('**/*.wav')
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# sort _silence_ after all the other paths; aligns metadata to data as data is not sorted by #
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# ascending order
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pathlist = sorted(pathlist, key=lambda d: str(d).lower().replace("_", "{"))
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for path, row in zip(pathlist, metadata.iterrows()):
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# row is a tuple containg an index and a pandas series
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pathcomponents = str(path).split("/")
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word = pathcomponents[-2]
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audio_filename = pathcomponents[-1]
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}
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#for debugging, comment out after
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#if __name__ == "__main__":
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#ds = datasets.load_dataset("speech_commands_enriched.py", 'v0.01', split="test",
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#streaming=False)
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