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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 |
|---|---|---|
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accent/GB/ultrachat_976376 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
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accent/GB/ultrachat_367291 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
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accent/GB/ultrachat_777230 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
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accent/GB/ultrachat_386909 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_1047234 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_920330 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_858954 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_1069172 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
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accent/GB/ultrachat_179782 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_1013896 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_580364 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_171736 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_207984 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_279758 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_157519 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_551250 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_13544 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_592314 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_66359 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_37949 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_727118 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_858000 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_782733 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar | |
accent/GB/ultrachat_661017 | hf://datasets/leungtianle/Expressiveness@eeb08072c33b939f478f36b2ab1cd525f60cc440/wav/accent.tar |
End of preview.
Expressiveness — UltraVoice 指令语音合成数据集
基于 UltraVoice 的 instruction_text 字段,
使用 IndexTTS-2.5 零样本音色克隆合成的语音数据集。
- 55,352 条音频,共 166.71 小时,22050 Hz 单声道 WAV (PCM16)
- 平均时长 10.84 秒
- 参考音色随机取自 865 个说话人片段,每个音色被使用 41–93 次
- 仅合成 instruction(提问)部分,response 未合成
数据构成
| 大类 | 条数 | 时长(小时) | 小类 |
|---|---|---|---|
| accent | 6,000 | 22.64 | AU, CA, GB, IN, SG, ZA |
| composite | 4,143 | 10.23 | en |
| emotion | 21,209 | 64.81 | angry, disgusted, fearful, happy, neutral, sad, surprised |
| generalqa | 6,000 | 9.89 | en |
| language | 6,000 | 20.70 | chinese, japanese, korean |
| speed | 6,000 | 19.17 | fast, normal, slow |
| volume | 6,000 | 19.27 | high, low, normal |
| 合计 | 55,352 | 166.71 | 24 个小类 |
完整的小类级统计(含各类最短/最长时长)见 ultravoice_stats.md。
文件说明
ultravoice.jsonl— 元数据,每行一条记录:{ "key": "ultrachat_586644", "split_type": "accent", "sub_type": "AU", "instruction_text": "Could you share some insights on ...", "response_text": "G'day mate! Substance abuse in teenagers ...", "instruction_wav_path": "wav/instructions/accent/AU/ultrachat_586644.wav", "response_wav_path": "wav/responses/accent/AU/ultrachat_586644_0.wav", "dataset_split": "train" }instruction_wav_path指向本仓库中的合成音频。response_text/response_wav_path为原始数据集字段,本仓库未合成 response 音频。wav/*.tar— 按大类打包的音频,共 7 个分片。解包后目录结构为instructions/<大类>/<小类>/<key>.wav,与instruction_wav_path去掉wav/前缀后对应。
使用方式
# 下载
hf download leungtianle/Expressiveness --repo-type=dataset --local-dir .
# 解包(还原为 wav/instructions/<大类>/<小类>/<key>.wav)
mkdir -p wav_extracted
for f in wav/*.tar; do tar -xf "$f" -C wav_extracted; done
解包后把 wav_extracted 重命名为 wav,即可直接用 instruction_wav_path 索引音频。
合成配置
| 项 | 值 |
|---|---|
| 模型 | IndexTTS-2.5 |
| 精度 | bfloat16 |
| 语言标签 | lang="EN"(所有 instruction_text 均为英文) |
| 音色选择 | 按样本 key 派生随机种子,可复现 |
| 情感/语速控制 | 未启用(duration_factor 保持默认 1.0) |
注意事项
sub_type描述的是文本内容的风格要求,不是合成音频的实际声学属性。 例如speed=slow的样本,其 instruction 文本要求"用缓慢的语速回答",但合成时未启用duration_factor,音频语速由参考音色决定。同理emotion、volume、accent等标签也不反映合成音频本身的情感、音量或口音。generalqa的平均时长(5.93 秒)明显短于其他类(11–14 秒),因为它的 instruction 是纯问句,而其他类的文本额外附带了风格指令,文本更长。composite类 4,143 条即原数据集该类的全部数量,已取尽。dataset_split字段沿用原数据集(train 53,874 / test 1,478),抽样时未按此字段分层。
许可
音频由 IndexTTS-2.5 合成,请遵守 IndexTTS 模型许可。 文本内容来自 UltraVoice 数据集,请遵守其原始许可。
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