The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: RuntimeError
Message: Failed to open input buffer: Invalid data found when processing input
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2543, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2061, in __iter__
batch = formatter.format_batch(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 472, in format_batch
batch = self.python_features_decoder.decode_batch(batch)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 234, in decode_batch
return self.features.decode_batch(batch, token_per_repo_id=self.token_per_repo_id) if self.features else batch
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2161, in decode_batch
decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1419, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/audio.py", line 211, in decode_example
audio = AudioDecoder(
^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/torchcodec/decoders/_audio_decoder.py", line 64, in __init__
self._decoder = create_decoder(source=source, seek_mode="approximate")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/torchcodec/decoders/_decoder_utils.py", line 45, in create_decoder
return core.create_from_file_like(source, seek_mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/torchcodec/_core/ops.py", line 151, in create_from_file_like
return _convert_to_tensor(_pybind_ops.create_from_file_like(file_like, seek_mode))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Failed to open input buffer: Invalid data found when processing inputNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MultiAPI Spoof: Multi-Source Audio Anti-Spoofing Dataset
Introduction
MultiAPI-Spoof is a multi-source audio anti-spoofing dataset that contains approximately 230 hours of spoofed audio. It includes synthetic audio generated by commercial TTS services, open-source models, and Chinese TTS websites. An equal amount of bonafide speech from CommonVoice is included for a 1:1 balance between genuine and spoofed samples. This dataset is designed to support research and model training for audio anti-spoofing.
Spoofed Audio Data Sources
Our new dataset, MultiAPI Spoof, contains speech samples generated from a variety of API sources, including:
- Commercial TTS APIs – speech generated by commercial services.
- Open-Source Model Generation – speech generated by open-source models.
- TTS Websites – speech on TTS web platforms.
The dataset is organized into 30 API, labeled A0–A29, with each group corresponding to a unique speech generation API source. The duration of speech in each API ranges from 0.2 to 12 hours.
Dataset Split
| API NO. | train | dev | eval |
|---|---|---|---|
| A0-A20 | 70% | 10% | 20% |
| A21-A23 | / | 100% | / |
| A24-A29 | / | / | 100% |
Metadata
The dataset includes three metadata files: MultiAPI_train.txt, MultiAPI_dev.txt, and MultiAPI_eval.txt.
Each line has four fields:
audio_path api class_label
XXX.mp3 A0 spoofed
XXX.mp3 - bonafide
📖 Citation
If you use this code or dataset, please cite:
Anonymous
📧 Contact
Anonymous
🔏 License
The dataset is released under CC BY-NC 4.0 license. Users must comply with the license terms. The authors do not claim ownership of the original audio content.
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