Datasets:
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/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/folder_based_builder/folder_based_builder.py", line 198, in _split_generators
for pa_metadata_table in self._read_metadata(downloaded_metadata_file, metadata_ext=metadata_ext):
~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 306, in _read_metadata
for df in csv_file_reader:
^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 5, saw 2
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 71, 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.
af_heart_arm_tts_dataset
The distillation corpus used to train dlyog/af_heart_arm_tts — a single-voice TTS model built for Arm inference on NVIDIA DGX Spark.
3.0000 hours · 4,104 clips · 24 kHz mono 16-bit PCM, synthesized by
Kokoro-82M speaking af_heart. This is knowledge distillation: the teacher
generated every clip, so the student can approach it but never exceed it.
The pipeline that produced this — and that reproduces it for any other voice — is at github.com/dlyog/arm-cooperative-tts
Layout
metadata.csv <wav>|<text>, one clip per line
wavs/000001.wav 24 kHz mono 16-bit
wavs/000002.wav
...
metadata.csv is pipe-separated — the format the trainer reads directly:
000001.wav|The quick brown fox jumps over the lazy dog.
000002.wav|Pack my box with five dozen liquor jugs.
Fetch
git clone https://github.com/dlyog/arm-cooperative-tts
cd arm-cooperative-tts
bash 1_SyntheticAudioDataset/manage.sh fetch
Or directly:
from huggingface_hub import snapshot_download
snapshot_download("dlyog/af_heart_arm_tts_dataset", repo_type="dataset",
local_dir="1_SyntheticAudioDataset/output")
How the text was chosen
| source | sentences | why |
|---|---|---|
| word bank | 62 | pangrams, spoken numbers, contractions, punctuation — deliberately the cases a phoneme-level model gets wrong. Every pangram is verified programmatically to contain all 26 letters, not trusted from memory |
| CMU ARCTIC | 1,132 | phonetically balanced prompts selected by CMU's Language Technologies Institute from out-of-copyright Project Gutenberg prose, specifically for single-speaker TTS |
| LLM-generated | remainder | topical variety — small talk, directions, scheduling, customer service — so the voice is not only read-aloud prose |
Deduplicated case-insensitively.
How the audio was made
Kokoro-82M af_heart, run in-process, at 24 kHz to match the student model's
sample rate.
Clips longer than 6.25 s were dropped, not truncated. A cut-off sentence teaches a model to stop mid-phrase. 6.25 s is therefore the longest clip here, and the trained model is not validated beyond that length in a single pass — longer text should be chunked by sentence.
Statistics
| clips | 4,104 |
| total duration | 3.0000 h |
| sample rate | 24,000 Hz |
| channels | mono |
| bit depth | 16-bit PCM |
| longest clip | 6.25 s |
| voice | af_heart (Kokoro-82M) |
| language | English (US) |
Building your own
Nothing downstream is tied to af_heart. One argument changes the speaker:
bash 1_SyntheticAudioDataset/manage.sh all 3.0 am_michael
The text corpus needs no network and no external service — the word bank and CMU ARCTIC prompts are offline. The LLM expansion step is optional and is skipped automatically when no endpoint is configured.
Licensing and provenance
Apache-2.0. The audio was generated by Kokoro-82M (Apache-2.0), so the clips carry no copyleft obligation. CMU ARCTIC prompts derive from out-of-copyright Project Gutenberg text, distributed by CMU for research use.
This dataset is synthetic. It contains no recordings of any real person; the speaker is a synthetic voice from Kokoro-82M. This work is not affiliated with or endorsed by the Kokoro-82M authors.
Intended use: distilling a small single-voice TTS model. Because the teacher is a hard quality ceiling, this corpus is not suitable for training a model intended to surpass Kokoro-82M, nor for speaker-verification or voice-cloning research involving real identities.
Citation
@misc{chawdhury2026afheartdataset,
author = {Chawdhury, Tarun Kumar},
title = {af\_heart\_arm\_tts\_dataset: A 3-hour Synthetic
Single-Voice TTS Distillation Corpus},
year = {2026},
howpublished = {\url{https://huggingface.co/datasets/dlyog/af_heart_arm_tts_dataset}},
organization = {DLYog Lab Research Services LLC}
}
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