Datasets:

ltuncay
/

chime-libricount

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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End of preview.

CHIME · LibriCount

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: LibriCount.
Pinned source release: v1.0.0.
Selection: Full LibriCount10-0dB release, preserving all speaker-count classes 0–10 and source mixture metadata.
Original license/access conditions: CC-BY-4.0 Public HTTPS download without registration or signed agreement. Preserve source attribution and license restrictions.
Source notes:

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 5,720 audio assets, 915,451,680 stored-audio bytes and 915,200,000 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: 5,720 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-libricount", 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: 5720 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)
`libricount-count-qa`	qa	exact_match	1	—	—	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.

Downloads last month: 726

Total file size:

954 MB

json dict	__key__ string	__url__ string
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-0004fb8a412f32d071ae347274b79b89.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "8092184eeb9b901d766c41657a19ece353a2c13151eb5228faef...	libricount-0004fb8a412f32d071ae347274b79b89	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-00066b7b7a7273a4a44d4a8e32027e28.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "b323fd7da3c4a3374c126d770ca10f663d2de38684c00de92401...	libricount-00066b7b7a7273a4a44d4a8e32027e28	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-00084be69d80c02a3cd8f5cef3778d56.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "8c96e328999e7d34655d4f530b03f9c52ab9ea75395037cf5c6b...	libricount-00084be69d80c02a3cd8f5cef3778d56	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-001c21f4ec8d6d7a8345e8b64669dbff.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "11bce63b9d338a005e8f84214b7c0beb6d56b87a3d6861dfbe55...	libricount-001c21f4ec8d6d7a8345e8b64669dbff	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-002ba2266a674a492f74d57c0822341e.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "a4507ac510de106b88fb2a366ad8e65602dad6d4c6241c832bb5...	libricount-002ba2266a674a492f74d57c0822341e	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-0030eb57d73db2e9d6a2d4226d242101.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "62c34b3b5fe16aeb99281278bf83383bc94d6399a11a0201d03a...	libricount-0030eb57d73db2e9d6a2d4226d242101	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-0034a9bdafdc9e10440a7dee70d25e1c.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "a8f7265bce5b32cb1ffdd5517676594360aaca737e9891edf680...	libricount-0034a9bdafdc9e10440a7dee70d25e1c	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-0040b1ddbb7ef58bed9e1ae686e37433.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "357643b23ba6123d71ff9db32e783107b0c1a3e1a50b01718f53...	libricount-0040b1ddbb7ef58bed9e1ae686e37433	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-0053e6fd6c28c61d559a826c5caf3a0d.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "5ef50b0c159e6115e0d74a3fb5c70ced8077cd51f7c0d8a22db9...	libricount-0053e6fd6c28c61d559a826c5caf3a0d	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-005efc61ffff650848c1d8074a8ab878.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "a049f30e9c6bc12ef29c31962ff17457008ff384edb6311d0582...	libricount-005efc61ffff650848c1d8074a8ab878	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-0076029d54f34900e969a4aa6fa8e38c.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "d5e78b9cbe3d167d7f3be46634329611ac8860e37b9cb165d92b...	libricount-0076029d54f34900e969a4aa6fa8e38c	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-007b1f47768407bda5e31c9e44e6e18c.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "71d2bb6c29e1ea5ad44e0cc78c516269147890c35e643bb2bfe7...	libricount-007b1f47768407bda5e31c9e44e6e18c	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-0087d6ebbfbc672eb9e760bb4ac839e6.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "728847d511f688df0330d08e806e75b7430671096d9523e167a6...	libricount-0087d6ebbfbc672eb9e760bb4ac839e6	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-008f1b063693b254c5de2a4ab8fefa5d.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "b72d5cc048ff1dab75eccb2526d3ea0f5e996897bd9f8ac9572d...	libricount-008f1b063693b254c5de2a4ab8fefa5d	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-008fce90f5ad59cc0b10b520f6c6d173.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "a5dbe78e4356db86566b7cdb6d07bae6fa8bb17215638dd6db3e...	libricount-008fce90f5ad59cc0b10b520f6c6d173	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-00a2ac11bc38666cbb1c69f3f354260e.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "9f9d2d6c260746d2eded50f99657d881b8b1670920c8b428f899...	libricount-00a2ac11bc38666cbb1c69f3f354260e	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-00bd0fee0351746ea5a409bd35032e46.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "64d33c85067ee95d2991e8f6d3b056dab3afc2e23ae8a3a865b1...	libricount-00bd0fee0351746ea5a409bd35032e46	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-00d430adde1689f2fbef08f4d911d190.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "e57de43b63c284dbaf576d27b8de0fba4b6ebd0218dcf6c05051...	libricount-00d430adde1689f2fbef08f4d911d190	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-00dfaf94fab373d144ba3296b8436f0a.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "05616a68181d751097fbdfede17c9b473f84dcb31d72d2da4c59...	libricount-00dfaf94fab373d144ba3296b8436f0a	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-00f5da0d25d5e28ffea0613301757510.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "7e9971f15fdcf984823140f09f1d708ad20ad0f5c607090b5076...	libricount-00f5da0d25d5e28ffea0613301757510	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-00f6b40f840ebfc35988c7371e2463e0.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "c1e02129e6f4f0b81258e7c2c2b5888174631d35deef91941bf1...	libricount-00f6b40f840ebfc35988c7371e2463e0	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-010a63ba03747a67b89e1b4289417305.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "2597cf40934a319e9a314f62f38c622b729a48e1521949c15f93...	libricount-010a63ba03747a67b89e1b4289417305	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-0124378b2f97ff8e4b76981a8a8d6c96.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "b7bee689f3af26de482ebc928d6d1dcededd384d0e32700759c9...	libricount-0124378b2f97ff8e4b76981a8a8d6c96	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-012ab79d233e63ec64b396ba3905eb2f.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "2d5088c25e3ff7fb260caeb20d8e62aa73c28e202be018461adf...	libricount-012ab79d233e63ec64b396ba3905eb2f	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
{ "audio": { "channel_order": "source_native", "channels": 1, "format": "WAV", "frames": 80000, "member": "libricount-012caa584e2280778a3253bd4de8632a.wav", "pcm_bytes": 160000, "sample_rate": 16000, "sample_width": 2, "sha256": "2847a8586c0af936bab13d8a19f8b6a2e693eed0b16b3ae39832...	libricount-012caa584e2280778a3253bd4de8632a	hf://datasets/ltuncay/chime-libricount@1223d50710f057fcbeb48c10a9fae37b7d24f14b/data/test/shard-000000.tar
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