Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<res_ms: int64, seg_eer: double, eer_threshold: double, polarity: string, mean_iou: double, median_iou: double, iou_ge_07: double, iou_ge_09: double, n_spoof_utterances: int64>
to
{'frame_shift_ms': Value('int64'), 'n_utterances': Value('int64'), 'n_processed': Value('int64'), 'utt_eer': Value('float64'), 'utt_eer_threshold': Value('float64'), 'seg_eer_20ms': Value('float64'), 'seg_eer_40ms': Value('float64'), 'seg_eer_80ms': Value('float64'), 'seg_eer_160ms': Value('float64'), 'seg_eer_320ms': Value('float64'), 'seg_eer_640ms': Value('float64'), 'seg_f1_20ms': Value('float64')}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2149, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<res_ms: int64, seg_eer: double, eer_threshold: double, polarity: string, mean_iou: double, median_iou: double, iou_ge_07: double, iou_ge_09: double, n_spoof_utterances: int64>
to
{'frame_shift_ms': Value('int64'), 'n_utterances': Value('int64'), 'n_processed': Value('int64'), 'utt_eer': Value('float64'), 'utt_eer_threshold': Value('float64'), 'seg_eer_20ms': Value('float64'), 'seg_eer_40ms': Value('float64'), 'seg_eer_80ms': Value('float64'), 'seg_eer_160ms': Value('float64'), 'seg_eer_320ms': Value('float64'), 'seg_eer_640ms': Value('float64'), 'seg_f1_20ms': Value('float64')}Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Partial-Spoof Cross-Domain Audit: detector score outputs
Per-utterance and per-frame score outputs of three detectors (MRM, BAM, CFPRF) on
PartialSpoof, LlamaPartialSpoof, PartialEdit, and HQ-MPSD. These reproduce every
number in the cross-domain operational audit when used with the code repository
(partial-spoof-cross-domain-audit-reproducibility).
Usage
From the code repo root, download these files into data/:
hf download sukhdeveyash/partial-spoof-cross-domain-audit-data --repo-type dataset --local-dir data
Then run the analysis scripts in code/analysis/.
Contents
raw_e1_baseline/PartialSpoof in-domain:{bam,cfprf,mrm}_utt_*.npy,*_frame_*.npy,results.jsonraw_e5_cross_dataset/LlamaPS / PartialEdit / HQ-MPSD: same per-detector arrays +results.json
Score outputs are derived from the respective evaluation datasets, which carry
their own licenses (see the code repo's CHECKPOINTS.md).
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