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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 datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
mp3 audio | json dict | __key__ string | __url__ string |
|---|---|---|---|
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c028.mp3",
"block": "emotion",
"cand": 28,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c028 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__de.c016.mp3",
"block": "emotion",
"cand": 16,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__de__c016 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c041.mp3",
"block": "emotion",
"cand": 41,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c041 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c047.mp3",
"block": "emotion",
"cand": 47,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c047 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c043.mp3",
"block": "emotion",
"cand": 43,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c043 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__de.c011.mp3",
"block": "emotion",
"cand": 11,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__de__c011 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c040.mp3",
"block": "emotion",
"cand": 40,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c040 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__de.c012.mp3",
"block": "emotion",
"cand": 12,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__de__c012 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__de.c017.mp3",
"block": "emotion",
"cand": 17,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__de__c017 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c046.mp3",
"block": "emotion",
"cand": 46,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c046 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c042.mp3",
"block": "emotion",
"cand": 42,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c042 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c044.mp3",
"block": "emotion",
"cand": 44,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c044 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c030.mp3",
"block": "emotion",
"cand": 30,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c030 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c031.mp3",
"block": "emotion",
"cand": 31,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c031 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar | |
{
"adapters": "{\"char_human\": 1.0, \"emo_Impatience_and_Irritability\": 1.9, \"vn_VULN__high\": 0.22}",
"audio_key": "anime_000__E__Impatience_and_Irritability__A__en.c045.mp3",
"block": "emotion",
"cand": 45,
"caption": "GENERAL: A voice utterly expressing impatience and irritability, a tense, irritable vo... | anime_000__E__Impatience_and_Irritability__A__en__c045 | hf://datasets/laion/moss-voice-identity-repairs@7e7c50996c69ec46a28ebdfd971b85b668f63fe2/anime_000/part-00-0000.tar |
End of preview.
MOSS voice-acting v2 -- repaired takes
For each voice profile, every take whose ECAPA speaker similarity to the voice's reference fell
below 0.40, regenerated with that voice's identity LoRA (see
laion/moss-voice-identity-loras) merged at scale 1.0 on top of the identical condition
adapters at the identical lambdas.
Nothing here replaces anything. The original takes are untouched and remain part of the corpus; low-similarity takes are kept deliberately, because they are useful for training without reference audio, which is a different and legitimate use.
Layout
<voice>/part-<shard>-<chunk>.tar WebDataset: <key>.mp3 (160 kbps, 48 kHz) + <key>.json
<voice>/annotations.parquet one row per repaired take
<voice>/report.json the voice's before/after and cost report
Columns
Every row carries three groups of columns, and none of them is derived from another:
src_*-- the corpus's own stored annotation of the original take, complete: every score component (strength_raw,w_blend,z_containment,contained,dur,wer,spk_sim, the z-terms, the multiplicative factors), so any later re-ranking needs zero regeneration.org_*-- the original audio re-scored here through the same sensor stack as the repair (ECAPA, WavLM-tbr, Whisper-large-v3-turbo, the corpus's fast scorer). Stored WER came from Parakeet and is not comparable to Whisper WER, which is why the before side is re-measured rather than inherited.rep_*-- the repaired take, measured identically.
Plus src_spk_emb / rep_spk_emb (ECAPA, float16) and rep_tbr_emb (WavLM-tbr, float16), and
repair_adapter, repair_adapter_sha, repair_scale, repair_epoch so every take records
exactly which weights produced it.
audio_key is <gid>.cNNN.mp3 and is not unique across runs; run_dir is stored beside it
and every join must use both.
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