The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 761, in hf_raise_for_status
response.raise_for_status()
~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/httpx/_models.py", line 829, in raise_for_status
raise HTTPStatusError(message, request=request, response=self)
httpx.HTTPStatusError: Client error '404 Not Found' for url 'https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/fd/a2/fda246acc06b384d782d15c08f8fd9b7e99e5d7e8e5ce301e0abadb6c2d3fc3c/2d936ac6130beb7d5a0ce756251f03c1ca08eefa0aba89d12b04d0f89a33e907?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQOYY2AAUF%2F20260813%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20260813T142626Z&X-Amz-Expires=3600&X-Amz-Signature=e6fc282134172d10a826ca520901022d605906ea4029add1f5f00790bada4940&X-Amz-SignedHeaders=host&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27train-00000-of-00029.parquet%3B%20filename%3D%22train-00000-of-00029.parquet%22%3B&x-amz-checksum-mode=ENABLED&x-id=GetObject'
For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/404
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 127, in _split_generators
self.info.features = datasets.Features.from_arrow_schema(pq.read_schema(f))
~~~~~~~~~~~~~~^^^
File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 2393, in read_schema
file = ParquetFile(
where, memory_map=memory_map,
decryption_properties=decryption_properties)
File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 328, in __init__
self.reader.open(
~~~~~~~~~~~~~~~~^
source, use_memory_map=memory_map,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
...<8 lines>...
arrow_extensions_enabled=arrow_extensions_enabled,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "pyarrow/_parquet.pyx", line 1656, in pyarrow._parquet.ParquetReader.open
File "pyarrow/error.pxi", line 89, in pyarrow.lib.check_status
RestorePyError(status)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 844, in read_with_retries
out = read(*args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 1238, in read
return super().read(length)
~~~~~~~~~~~~^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/spec.py", line 1897, in read
out = self.cache._fetch(self.loc, self.loc + length)
File "/usr/local/lib/python3.14/site-packages/fsspec/caching.py", line 234, in _fetch
self.cache = self.fetcher(start, end) # new block replaces old
~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 1195, in _fetch_range
hf_raise_for_status(r)
~~~~~~~~~~~~~~~~~~~^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 877, in hf_raise_for_status
raise _format(HfHubHTTPError, str(e), response) from e
huggingface_hub.errors.HfHubHTTPError: Client error '404 Not Found' for url 'https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/fd/a2/fda246acc06b384d782d15c08f8fd9b7e99e5d7e8e5ce301e0abadb6c2d3fc3c/2d936ac6130beb7d5a0ce756251f03c1ca08eefa0aba89d12b04d0f89a33e907?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQOYY2AAUF%2F20260813%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20260813T142626Z&X-Amz-Expires=3600&X-Amz-Signature=e6fc282134172d10a826ca520901022d605906ea4029add1f5f00790bada4940&X-Amz-SignedHeaders=host&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27train-00000-of-00029.parquet%3B%20filename%3D%22train-00000-of-00029.parquet%22%3B&x-amz-checksum-mode=ENABLED&x-id=GetObject'
For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/404
<?xml version="1.0" encoding="UTF-8"?>
<Error><Code>NoSuchKey</Code><Message>The specified key does not exist.</Message><Key>repos/fd/a2/fda246acc06b384d782d15c08f8fd9b7e99e5d7e8e5ce301e0abadb6c2d3fc3c/2d936ac6130beb7d5a0ce756251f03c1ca08eefa0aba89d12b04d0f89a33e907</Key><RequestId>4DFCVMHGZSE0D1FE</RequestId><HostId>O51ZWS6KTJKSEg7Sz0WtliJ5TnbsYh0biuZrC8wLOg0iJh4G4pXnd7k0wo05iVB1H2LxnZLZdfs=</HostId></Error>
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/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
Ghanaian English Speech — Audio with IPA Transcripts
Speech with both transcript forms: the original orthography and the IPA phoneme
sequence read off the audio by ASR. Each language is a subset, with real
train/validation splits.
from datasets import load_dataset
ds = load_dataset("ghanaopendata/ghana-english-speech-ipa", "English_eng", split="train")
ds[0]["audio"] # decoded waveform, 16 kHz
ds[0]["text"] # original orthography
ds[0]["ipa"] # IPA phonemes
- 52,855 clips · ~201 h across 1 subsets
- Ghanaian English (
English_eng) - audio: FLAC, 16 kHz mono (lossless re-encode of the source WAV)
Subsets (config_name = language code)
English_eng
Format
| column | type | notes |
|---|---|---|
id |
string | clip id (a few source shards repeat ids, so it is not a unique key) |
audio |
audio | FLAC, 16 kHz mono — decodes to a waveform |
text |
string | original written transcript in the language's orthography |
ipa |
string | IPA phonemes, space-separated, punctuation kept |
duration |
float64 | seconds |
language |
string | config code |
dataset_id |
int32 | language id, shared with the latent datasets |
Relationship to the latent datasets
This is the audio twin of
ghanaopendata/voxcpm2-ghana-speech-ipa-latents
and
ghanaopendata/voxcpm2-ghana-english-ipa-latents:
the same clips, the same per-language ids, and the same train/dev assignment — those
carry precomputed VoxCPM-2 AudioVAE latents instead of audio, for training without a
decode step. Use this one to listen, to check transcripts, or to train anything that needs
real audio.
Source
Audio from ghanaopendata/ghana-english-tts-clean2 (first 200 h). The 42 Ghanaian languages are at ghanaopendata/ghana-speech-ipa.
How the IPA was produced
Read off the audio by ghananlpcommunity/ghana-english-phoneme-asr,
a CTC recogniser finetuned from the 42-language Ghanaian model on ghana-english-g2p targets.
That detail matters for anyone synthesising from this data. An earlier version of this dataset
used the Ghanaian recogniser directly, which transcribes English in its own convention —
76% UER against ghana-english-g2p, with symbols like ð and iː largely absent. Since
inference has no ASR, only a g2p, those labels could not be reproduced at synthesis time. The
English recogniser was built specifically to close that gap: it reads what the speaker
actually said, but writes it in the g2p convention, reaching 16.7% UER against g2p on
held-out clips. The residual is mostly genuine pronunciation difference rather than
convention mismatch, which is the point.
Transcription used per-utterance input normalisation and 6-second windowing (the encoder collapses silently on long audio; these clips average 13.8 s).
Pipeline:
GhanaNLP/ghana-speech-english-ipa-latents-data-prep
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