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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    TypeError
Message:      int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1539, in _prepare_split_single
                  for key, record in generator:
                                     ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 131, in _generate_examples
                  for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
                                              ~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  for filename, f in tar_iterator:
                                     ^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
                  for x in self.generator(*self.args):
                           ~~~~~~~~~~~~~~^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1419, in _iter_from_urlpath
                  with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
                       ~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 976, in xopen
                  file_obj = fs.open(paths[0], mode)
                File "<string>", line 3, in open
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
                  return self._mock_call(*args, **kwargs)
                         ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
                  return self._execute_mock_call(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
                  result = effect(*args, **kwargs)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 794, in wrapped
                  tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
                                                               ~~~^^^^^^^^
              TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1401, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1579, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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wav
audio
json
dict
__key__
string
__url__
string
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 779200, "member": "realdesed-0006a8bc3187652c12fa85e11728bd61.wav", "pcm_bytes": 1558400, "sample_rate": 48000, "sample_width": 2, "sha256": "30d0a2d5ae8df5874175bc3d1f716d9923a104b52dc20d91cf2...
realdesed-0006a8bc3187652c12fa85e11728bd61
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 910272, "member": "realdesed-0011e5e00bbd511c242e31749f5308c2.wav", "pcm_bytes": 1820544, "sample_rate": 48000, "sample_width": 2, "sha256": "0ce6f74bb14686c1d31d9c52bbd755df15d81e7b18bd1d9d05e...
realdesed-0011e5e00bbd511c242e31749f5308c2
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1003520, "member": "realdesed-0028fa178cbdc412c81b41b69776efea.wav", "pcm_bytes": 2007040, "sample_rate": 48000, "sample_width": 2, "sha256": "6242245cb6c9dec12e8526f0e3e82c7753a7234bb80aa795c3...
realdesed-0028fa178cbdc412c81b41b69776efea
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1029056, "member": "realdesed-002b7ec840b961cb74f93a826e4c4514.wav", "pcm_bytes": 2058112, "sample_rate": 48000, "sample_width": 2, "sha256": "49069a32525e5fc9868ff0406db9bc646419ef09fe8dd46eb6...
realdesed-002b7ec840b961cb74f93a826e4c4514
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1209280, "member": "realdesed-002ca728fdbfb2a037fe1daa0d49fe49.wav", "pcm_bytes": 2418560, "sample_rate": 48000, "sample_width": 2, "sha256": "bd1e91b98a1314b61b371c0321faefe03704f941e4fecc2f89...
realdesed-002ca728fdbfb2a037fe1daa0d49fe49
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 887040, "member": "realdesed-00662eed8edb2fbfa2de84f24db24c02.wav", "pcm_bytes": 1774080, "sample_rate": 48000, "sample_width": 2, "sha256": "a9aeaf922cc25b0c38a8403a547a60b955c294c50dd0d112401...
realdesed-00662eed8edb2fbfa2de84f24db24c02
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1086400, "member": "realdesed-0073b934d483aa69744bb217554bde7c.wav", "pcm_bytes": 2172800, "sample_rate": 48000, "sample_width": 2, "sha256": "0e462520b3b7508da9bf334fb2c6796bba99737172e458f6da...
realdesed-0073b934d483aa69744bb217554bde7c
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1135616, "member": "realdesed-00cc9c2a09752b33b62d505b39f4407c.wav", "pcm_bytes": 2271232, "sample_rate": 48000, "sample_width": 2, "sha256": "7cbc4bcfe757d2b7c267607c930079a97d00576d7fa2d922d6...
realdesed-00cc9c2a09752b33b62d505b39f4407c
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1329408, "member": "realdesed-00eaf4bf0ef05b42e22605a68a96b289.wav", "pcm_bytes": 2658816, "sample_rate": 48000, "sample_width": 2, "sha256": "5404d400c4b551b4e3db9c60851b740730d0addf07405552ee...
realdesed-00eaf4bf0ef05b42e22605a68a96b289
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1631168, "member": "realdesed-01037668618d7f9e72c370e1495fb76a.wav", "pcm_bytes": 3262336, "sample_rate": 48000, "sample_width": 2, "sha256": "9303d07a7fc50c12f5cc88d5e9eb49a0ea14a988c1e04d9c6c...
realdesed-01037668618d7f9e72c370e1495fb76a
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1028096, "member": "realdesed-011efc06f3180e6dbef2232f1a1a79c6.wav", "pcm_bytes": 2056192, "sample_rate": 48000, "sample_width": 2, "sha256": "196ba1872d3dceff5160cfa4cf80987eff40c3ba07bb7d05d5...
realdesed-011efc06f3180e6dbef2232f1a1a79c6
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 748544, "member": "realdesed-012378b09c986568e205c153ea3466d7.wav", "pcm_bytes": 1497088, "sample_rate": 32000, "sample_width": 2, "sha256": "9cbea2f66e8ef647f13ea86cc2e6eacabd3df0af23bdc81a8ee...
realdesed-012378b09c986568e205c153ea3466d7
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 826304, "member": "realdesed-014c2c7a460bb53820f76ae2a59ef2ab.wav", "pcm_bytes": 1652608, "sample_rate": 44100, "sample_width": 2, "sha256": "fa2b06fb228e8e005dde2b27cdf94bbea7871081bde3f0d9aaf...
realdesed-014c2c7a460bb53820f76ae2a59ef2ab
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 760991, "member": "realdesed-0159716e4235c02366a69ee23714082c.wav", "pcm_bytes": 1521982, "sample_rate": 48000, "sample_width": 2, "sha256": "9753f141722f658535d1c6cf2b18dda9aace06c637667654db8...
realdesed-0159716e4235c02366a69ee23714082c
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1326080, "member": "realdesed-015ee728442117306f61c2a517a44639.wav", "pcm_bytes": 2652160, "sample_rate": 48000, "sample_width": 2, "sha256": "670deedeaafc90d3c15f3df2b365c413fbb9e05c8d42eedfb8...
realdesed-015ee728442117306f61c2a517a44639
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1070016, "member": "realdesed-017bf0320d187958155ce2219c591432.wav", "pcm_bytes": 2140032, "sample_rate": 48000, "sample_width": 2, "sha256": "0267cafd057e79141b05c7c1a6f9b14b0328b03b0431f6d37d...
realdesed-017bf0320d187958155ce2219c591432
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 783360, "member": "realdesed-017dfb2ec95110aa58cdfebb28b26e52.wav", "pcm_bytes": 1566720, "sample_rate": 48000, "sample_width": 2, "sha256": "df2e13bd6793de426606e3e8b9837360f1ace1f816cfe0b5f87...
realdesed-017dfb2ec95110aa58cdfebb28b26e52
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1009664, "member": "realdesed-0187a41d21d756d08003325c3972a4c3.wav", "pcm_bytes": 2019328, "sample_rate": 48000, "sample_width": 2, "sha256": "28c53b7a09ff2bf443ed1d8e6684b8c52f9c0628331c628d84...
realdesed-0187a41d21d756d08003325c3972a4c3
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 955328, "member": "realdesed-0197f4c3874778e973dfb901b669f676.wav", "pcm_bytes": 1910656, "sample_rate": 48000, "sample_width": 2, "sha256": "f3857180ecafd0e2de6ea1c1f974849ab30cf4c85f78420fc3b...
realdesed-0197f4c3874778e973dfb901b669f676
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1430464, "member": "realdesed-01a1aa0e43d04ca90f75f28086962190.wav", "pcm_bytes": 2860928, "sample_rate": 48000, "sample_width": 2, "sha256": "a6daec450bd1bfdf8a29fe3ffca4a112e1d9b613cfb3084461...
realdesed-01a1aa0e43d04ca90f75f28086962190
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1098688, "member": "realdesed-01aec6ef10190fb64160989fdec27708.wav", "pcm_bytes": 2197376, "sample_rate": 48000, "sample_width": 2, "sha256": "7c32744fa46362ca1f8a348cf65ecb2e5d4c880eaa7facbe23...
realdesed-01aec6ef10190fb64160989fdec27708
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1012672, "member": "realdesed-01d40e972a30a019e7816d61635b10fd.wav", "pcm_bytes": 2025344, "sample_rate": 48000, "sample_width": 2, "sha256": "0b59798dbe7e8a69b33f09d6250f78c0ddb0ddb1b262eb4500...
realdesed-01d40e972a30a019e7816d61635b10fd
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 820160, "member": "realdesed-01ff92eaecf61bf810666f0c0d286eb7.wav", "pcm_bytes": 1640320, "sample_rate": 48000, "sample_width": 2, "sha256": "c6a07fe278e8ccec4caa559ecfb82b9933799275ffc17db4a2e...
realdesed-01ff92eaecf61bf810666f0c0d286eb7
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 992192, "member": "realdesed-0208b58d9e65e1a61f2162f11bbba0c2.wav", "pcm_bytes": 1984384, "sample_rate": 48000, "sample_width": 2, "sha256": "bd3f57e5544ecfa70f687c4334b07ed45c939514e3b57e8e2d9...
realdesed-0208b58d9e65e1a61f2162f11bbba0c2
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 1005568, "member": "realdesed-0235bf1e0e618e48d2d5c5f5e22a8fcc.wav", "pcm_bytes": 2011136, "sample_rate": 48000, "sample_width": 2, "sha256": "12a9b5c1b82460ac93ec14f2006e1b68f8be36f3d5ace190eb...
realdesed-0235bf1e0e618e48d2d5c5f5e22a8fcc
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 802816, "member": "realdesed-02583d60d3bd8a02c39117fbe5b25517.wav", "pcm_bytes": 1605632, "sample_rate": 48000, "sample_width": 2, "sha256": "391ba814bd875abd5200146667f248b0a6aa04397189c55d6df...
realdesed-02583d60d3bd8a02c39117fbe5b25517
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 772096, "member": "realdesed-02625c8914d3e533fb1bdf0575f2e7de.wav", "pcm_bytes": 1544192, "sample_rate": 44100, "sample_width": 2, "sha256": "bfef65870876f6f1bba1b5a7b945efc7d27c4a9f22ac227d16e...
realdesed-02625c8914d3e533fb1bdf0575f2e7de
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 946176, "member": "realdesed-028d5c6e941816dcac2bef1aa3279902.wav", "pcm_bytes": 1892352, "sample_rate": 44100, "sample_width": 2, "sha256": "939f6442e7ef12b7170590cdf46e1dce8e85443ae395f67ae55...
realdesed-028d5c6e941816dcac2bef1aa3279902
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 988096, "member": "realdesed-028e1de12361ac4149e4fde9f6734ca7.wav", "pcm_bytes": 1976192, "sample_rate": 48000, "sample_width": 2, "sha256": "069187152d5a4b480cb6cf5a29ba3a9aa2f18e91c9e166b9c08...
realdesed-028e1de12361ac4149e4fde9f6734ca7
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 930816, "member": "realdesed-02b51c4f94a0a1fb082abbcbc32fb947.wav", "pcm_bytes": 1861632, "sample_rate": 48000, "sample_width": 2, "sha256": "e7b20850694d5604b49f5dda6e8e60e5e52387f35dff4387077...
realdesed-02b51c4f94a0a1fb082abbcbc32fb947
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 819200, "member": "realdesed-02c2355b580cc61b59b877f74de83d4f.wav", "pcm_bytes": 1638400, "sample_rate": 48000, "sample_width": 2, "sha256": "6862b065ce797358c891497087a1d6f0df2a2aad26c8eab44a9...
realdesed-02c2355b580cc61b59b877f74de83d4f
hf://datasets/ltuncay/chime-realdesed@87f6b63ce3f1ddee52adcf670d9d3e9437806523/data/train/shard-000003.tar
End of preview.

CHIME · RealDESED

This is a source-preserving prepared candidate, not a scientifically admitted CHIME benchmark release. It repackages the selected upstream release into split-specific WebDataset TAR shards with native audio and per-example JSON. A Parquet index permits metadata filtering without downloading audio shards.

Source and selected scope

  • Upstream: RealDESED.
  • Pinned source release: 20056072.
  • Selection: Author release includes native real recordings and public temporal annotations with reviewed validation/test targets.
  • Original license/access conditions: CC-BY-4.0; retain per-record metadata, authors and collection/annotation notices. Public direct HTTPS; preserve all attribution and license notices. No access account or signed agreement.
  • Source notes: Acquire only pinned objects. Preserve native audio and raw source labels. Subset and quality rules are in the matching decision; scientific admission is pending.

Original authors, licensors and recording contributors retain their rights. This preparation was assembled for public noncommercial research access; this repository does not grant broader rights than the original sources. Preserve per-recording attribution and notices. provenance/ contains original annotations/docs/licenses, source provenance and the redistribution audit. FSD50K/Clotho audio has per-recording terms; Clotho captions retain the complete custom Tampere experimental/noncommercial license. The CHIME code license does not apply to these data.

Representation and preservation

There are 4,491 audio assets, 10,091,983,408 stored-audio bytes and 10,091,633,110 decoded-PCM-equivalent bytes. Native sample rate, duration and channel count are retained. No loudness normalization, silence trimming, resampling or downmixing is applied.

Each sample retains its native audio codec (WAV/FLAC/MP3/OGG or another supported native container). Each payload is accompanied by <key>.json in an ordinary TAR. The JSON contains split, stored audio metadata, provenance, source groups and source targets. manifest.jsonl also records shard/member offsets and checksums. metadata.parquet provides audio and shard columns, common source/group/license columns, and exact arbitrary annotations in metadata_json (decode with json.loads). It does not duplicate audio payloads. Keeping heterogeneous annotations as JSON preserves empty objects and differing target schemas without Arrow type coercion. release.json hashes the audio shards and record manifest, and publication.json inventories all published files including attribution assets.

CHiME-3 background recordings interleave six synchronized native mono PCM16 channels into one six-channel PCM16 WAV per session, with exact decoded-sample checks and an explicit channel map. The excluded CHiME speech corpus is not included. Other audio payloads are copied byte for byte.

Source splits

  • test: 1,007 original audio assets.
  • train: 2,686 original audio assets.
  • validation: 798 original audio assets.

These are original source partitions or explicitly unspecified/background partitions. ESC-50 retains five official folds; no fixed benchmark train/test assignment is invented. VocalSet's split is the supplied technique-classification singer protocol, not a universal task protocol. Background noise is not converted into artificial word or silence examples. Linked views/channels share provenance groups.

Scientific limitations

Scientific admission remains pending. Native file integrity and packaging checks do not establish label correctness, perceptual deduplication, contamination freedom or benchmark validity. Existing upstream annotation errata and ambiguity are retained/documented. The source audit found declared Freesound ID overlaps within some official folds/partitions and across ESC-50, FSD50K and Clotho; FSD50K train/validation also share uploaders. Use the supplied source IDs, group metadata and provenance/source-audit.json when defining an evaluation protocol. Do not claim these candidate splits are universally leakage-free. Scores from this repository alone are not official CHIME scores.

Loading

Pin an immutable Hub commit revision in experiments. A generic Hugging Face WebDataset loader can read the shard configurations:

from datasets import load_dataset
samples = load_dataset("ltuncay/chime-realdesed", revision="<commit-sha>", streaming=True)

For local source-native decoding and checksum verification, use CHIME's iter_release(path, split=..., verify_hashes=True). Its audio arrays have shape [frames, channels]; the evaluated model owns its preprocessing. Download only selected shards/index files when appropriate; benchmark execution must not silently fetch data.

Provenance and citation

Cite the upstream dataset and recording authors as specified in the original documentation under provenance/. This preparation does not claim authorship of the source recordings or annotations. Exact upstream objects, checksums, release selection, preparation metadata and source URLs are recorded in release.json. Source Zenodo metadata/citations are retained when available. See the CHIME project implementation brief and scientific paper for the evolving evaluation protocol.

CHIME v1 benchmark usage

Do not train on CHIME evaluation data: 1007 records in the release split(s) test, listed one key per line in provenance/benchmark-v1/eval-keys.txt. Models submitted to CHIME must not see these recordings (or their source recordings) during pretraining or fine-tuning.

Task Family Metric Folds Train Validation Test (eval)
realdesed-sed frame_multilabel segment_f1 1 train validation test
realdesed-tagging multilabel macro_ap 1 train validation test

Exact per-record partition assignments (including records excluded from training because they share a source with evaluation data, and digitally silent assets) are in provenance/benchmark-v1/<task>.jsonl; the frozen task definitions are in provenance/benchmark-v1/usage.json. Splits never depend on the evaluation seed.

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