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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.
wav audio | __key__ string | __url__ string |
|---|---|---|
100-121674-0010_defend | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-121674-0010_defend_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-121674-0010_defend_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-121674-0010_defend_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-121674-0010_defend_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0008_discuss | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0008_discuss_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0008_discuss_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0008_discuss_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0008_discuss_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0015_extend | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0015_extend_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0015_extend_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0015_extend_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0015_extend_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0020_reward | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0020_reward_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0020_reward_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0020_reward_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0020_reward_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0038_become | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0038_become_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0038_become_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0038_become_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
100-122655-0038_become_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1002_become | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1002_become_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1002_become_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1002_become_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1002_become_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1008_suggest | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1008_suggest_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1008_suggest_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1008_suggest_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1008_suggest_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1014_suggest | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1014_suggest_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1014_suggest_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1014_suggest_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1014_suggest_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1033_refer | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1033_refer_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1033_refer_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1033_refer_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1033_refer_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1046_involve | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1046_involve_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1046_involve_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1046_involve_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1046_involve_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-132821-0034_receive | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-132821-0034_receive_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-132821-0034_receive_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-132821-0034_receive_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-132821-0034_receive_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0014_exists | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0014_exists_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0014_exists_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0014_exists_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0014_exists_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0027_forgive | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0027_forgive_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0027_forgive_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0027_forgive_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0027_forgive_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0029_forgives | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0029_forgives_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0029_forgives_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0029_forgives_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1053-289242-0029_forgives_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0033_complete | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0033_complete_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0033_complete_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0033_complete_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0033_complete_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0048_results | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0048_results_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0048_results_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0048_results_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1054-143005-0048_results_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0030_enable | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0030_enable_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0030_enable_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0030_enable_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0030_enable_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0032_result | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0032_result_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0032_result_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0032_result_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0032_result_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_becomes | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_becomes_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_becomes_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_becomes_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_becomes_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_begin | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_begin_10db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_begin_20db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_begin_3db_noise | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar | |
1061-142358-0037_begin_filterd | hf://datasets/MLSpeech/lexical_stress_dataset@3cbd510528a5ce980f2f541ce481084bb9b1b9c2/train/FS_tar/00000.tar |
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@article{allouche2026does, title={How does a deep neural network look at lexical stress in English words?}, author={Allouche, Itai and Asael, Itay and Rousso, Rotem and Dassa, Vered and Bradlow, Ann and Kim, Seung-Eun and Goldrick, Matthew and Keshet, Joseph}, journal={The Journal of the Acoustical Society of America}, volume={159}, number={2}, pages={1348--1358}, year={2026}, publisher={AIP Publishing} }
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