Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ReadTimeout
Message: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 9d6b5b21-ff76-4d3d-8301-1f1d2fa5d853)')
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
File "/src/libs/libcommon/src/libcommon/utils.py", line 271, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 61, in get_rows
ds = load_dataset(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 2061, in load_dataset
builder_instance = load_dataset_builder(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1781, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1663, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1620, in dataset_module_factory
return HubDatasetModuleFactoryWithoutScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1018, in get_module
data_files = DataFilesDict.from_patterns(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 690, in from_patterns
else DataFilesList.from_patterns(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 593, in from_patterns
origin_metadata = _get_origin_metadata(data_files, download_config=download_config)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 507, in _get_origin_metadata
return thread_map(
File "/src/services/worker/.venv/lib/python3.9/site-packages/tqdm/contrib/concurrent.py", line 69, in thread_map
return _executor_map(ThreadPoolExecutor, fn, *iterables, **tqdm_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/tqdm/contrib/concurrent.py", line 51, in _executor_map
return list(tqdm_class(ex.map(fn, *iterables, chunksize=chunksize), **kwargs))
File "/src/services/worker/.venv/lib/python3.9/site-packages/tqdm/std.py", line 1169, in __iter__
for obj in iterable:
File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 609, in result_iterator
yield fs.pop().result()
File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 439, in result
return self.__get_result()
File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 391, in __get_result
raise self._exception
File "/usr/local/lib/python3.9/concurrent/futures/thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 486, in _get_single_origin_metadata
resolved_path = fs.resolve_path(data_file)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 198, in resolve_path
repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 125, in _repo_and_revision_exist
self._api.repo_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2704, in repo_info
return method(
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2561, in dataset_info
r = get_session().get(path, headers=headers, timeout=timeout, params=params)
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 602, in get
return self.request("GET", url, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 589, in request
resp = self.send(prep, **send_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 703, in send
r = adapter.send(request, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 93, in send
return super().send(request, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/adapters.py", line 635, in send
raise ReadTimeout(e, request=request)
requests.exceptions.ReadTimeout: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 9d6b5b21-ff76-4d3d-8301-1f1d2fa5d853)')Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for CORAAL
Dataset Summary
This dataset comprises audio files, text files, and audio segments sourced from the Corpus of Regional African American Language (CORAAL).
CORAAL is a subset of the Online Resources for African American Language (ORAAL) project, initiated by a team of linguistics researchers at the University of Oregon.
The original CORAAL dataset encompasses over 220 sociolinguistic interviews featuring African American Language (AAL) speakers born between 1888 and 2005. Each interview includes accompanying audio files and human-transcribed transcripts.
While many large language models excel at automatic speech recognition, they often fall short when confronted with speech containing linguistic variations they haven't been trained on. Since CORAAL's initial release in January 2018 as the first public corpus of AAL data, it is highly probable that recent automatic speech recognition models struggle with AAL transcription.
The primary aim of this dataset is to facilitate developers in training or fine-tuning their ASR models specifically for AAL, "a language spoken by more than 30 million working-class African Americans across North America" (Wolfram). This effort ultimately seeks to enhance the inclusivity of everyday ASR technology.
For additional information regarding the original CORAAL dataset, please refer to the following links:
Supported Tasks and Leaderboards
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Languages
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Dataset Structure
Data Instances
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Data Fields
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Data Splits
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Dataset Creation
Curation Rationale
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Source Data
Initial Data Collection and Normalization
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Who are the source language producers?
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Annotations
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
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Discussion of Biases
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Other Known Limitations
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Additional Information
Dataset Curators
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Licensing Information
Citation Information
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Contributions
Kendall, Tyler and Charlie Farrington. 2023. The Corpus of Regional African American Language. Version 2023.06. Eugene, OR: The Online Resources for African American Language Project. [https://doi.org/10.7264/1ad5-6t35].
Walt Wolfram. 2020. Urban African American Vernacular English. In: Kortmann, Bernd & Lunkenheimer, Kerstin & Ehret, Katharina (eds.) The Electronic World Atlas of Varieties of English. None: None. (Available online at http://ewave-atlas.org/languages/15, Accessed on 2023-09-26.)
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