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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 1531, in _prepare_split_single
                  for key, record in generator:
                                     ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, 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 1405, 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 982, 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 786, 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 1369, 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 948, 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 1393, 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 1571, 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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asr.json
dict
events.json
dict
mel.safetensors
unknown
__key__
string
__url__
string
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"ac8165bbcf4ce6f6c6b1e716e4b02ad35b67e61f(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0000.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTQwOV0sImRhdGFfb2Zmc2V0cyI6WzAsNDUwODgwXX1(...TRUNCATED)
103-1240-0000
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"fc5efce26e028fc325091a2385f0b01b02fc6913(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0001.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTU5NV0sImRhdGFfb2Zmc2V0cyI6WzAsNTEwNDAwXX1(...TRUNCATED)
103-1240-0001
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"b4a9033271acf830a549e85a0d629d38e9844126(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0002.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTM5NV0sImRhdGFfb2Zmc2V0cyI6WzAsNDQ2NDAwXX1(...TRUNCATED)
103-1240-0002
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"4dfc8996ea33799cc4c50ab40e30ab5ff2917304(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0003.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTQ3Ml0sImRhdGFfb2Zmc2V0cyI6WzAsNDcxMDQwXX1(...TRUNCATED)
103-1240-0003
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"a364d1c82947399b037b2e3e65dc2403fd248ba6(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0004.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTI1Ml0sImRhdGFfb2Zmc2V0cyI6WzAsNDAwNjQwXX1(...TRUNCATED)
103-1240-0004
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"bfa59f344fe9bf5c716a59c48229327dced20391(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0005.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTUxOF0sImRhdGFfb2Zmc2V0cyI6WzAsNDg1NzYwXX1(...TRUNCATED)
103-1240-0005
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"f33f008427f3712b4c77c271e6ccf234100db267(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0006.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsOTU5XSwiZGF0YV9vZmZzZXRzIjpbMCwzMDY4ODBdfX0(...TRUNCATED)
103-1240-0006
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"3a2805c08fa90fdf6047b99a52055f40de1adac9(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0007.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTUwNF0sImRhdGFfb2Zmc2V0cyI6WzAsNDgxMjgwXX1(...TRUNCATED)
103-1240-0007
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"a53e7da359bc400afe468bdfc3ed323608c4e5d5(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0008.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTU0NF0sImRhdGFfb2Zmc2V0cyI6WzAsNDk0MDgwXX1(...TRUNCATED)
103-1240-0008
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
{"audio_identity":{"mtime_ns":1404808591000000000,"sha256":"42fc71aae9ace0b92c2e0e560aec0b4df27e7466(...TRUNCATED)
{"asr_cache_path":"asr/103-1240-0009.json","asr_provenance":{"audio_identity":{"mtime_ns":1404808591(...TRUNCATED)
"SAAAAAAAAAB7Im1lbCI6eyJkdHlwZSI6IkYzMiIsInNoYXBlIjpbODAsMTAwNF0sImRhdGFfb2Zmc2V0cyI6WzAsMzIxMjgwXX1(...TRUNCATED)
103-1240-0009
"hf://datasets/jay-junjiewu/side-transformer-librispeech-460-features@6871b307ff55a0d6dd4b842fabec72(...TRUNCATED)
End of preview.

LibriSpeech train-clean-460 ASR, Mel, and retrieval-event features

Public derived-feature release for the canonical LibriSpeech train-clean-100 and train-clean-360 splits. It contains Whisper ASR word/timestamp JSON, schema-v2 retrieval-event metadata, and packed 80-bin log-Mel tensors. It contains no clinical material, model weights, private paths, or source audio.

Layout

  • data/train-clean-100/ and data/train-clean-360/: WebDataset-style tar shards.
  • manifests/train-clean-100.csv and manifests/train-clean-360.csv: portable public recording manifests.
  • provenance/dataset.json: source, exclusion, validation, and manifest hashes.
  • provenance/shards.json: canonical record counts, byte counts, and SHA-256 checksums for every uploaded shard.

Each tar contains three members per recording: .asr.json, .events.json, and .mel.safetensors. Absolute source/cache paths were removed and internal references were rewritten to portable member names.

LibriSpeech is distributed under CC BY 4.0; users remain responsible for the upstream license and attribution requirements.

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