AuditoryHuM: Auditory Scene Label Generation and Clustering using Human-MLLM Collaboration
Paper • 2602.19409 • Published
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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 new columns ({'00022.wav'}) and 1 missing columns ({'The scene features a male voice speaking over a radio; with a background of a low hum and a distant rumble.'}).
This happened while the csv dataset builder was generating data using
hf://datasets/hzhongresearch/auditoryhum_supplementary/advance_file_list.csv (at revision 7a8d1491b524314e615cd70f24474a81e3266fe3), [/tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_captions.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_captions.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_file_list.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_file_list.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_gemma3n_e2b_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_gemma3n_e2b_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_gemma3n_e2b_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_gemma3n_e2b_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_provided_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_provided_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_human_strat.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_human_strat.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2a_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2a_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2a_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2a_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_captions.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_captions.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_file_list.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_file_list.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_gemma3n_e2b_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_gemma3n_e2b_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_gemma3n_e2b_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_gemma3n_e2b_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_qwen2_5o_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_qwen2_5o_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_qwen2_5o_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_qwen2_5o_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_qwen2a_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_qwen2a_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_qwen2a_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead-ds_qwen2a_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/ahead_ds_provided_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/ahead_ds_provided_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_captions.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_captions.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_file_list.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_file_list.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_gemma3n_e2b_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_gemma3n_e2b_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_gemma3n_e2b_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_gemma3n_e2b_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_provided_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_provided_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_qwen2_5o_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_qwen2_5o_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_qwen2_5o_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_qwen2_5o_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_qwen2a_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_qwen2a_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_qwen2a_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/tau2019_qwen2a_labels_annotations.csv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
00022.wav: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 380
to
{'The scene features a male voice speaking over a radio; with a background of a low hum and a distant rumble.': Value('string')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1348, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 890, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 951, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 new columns ({'00022.wav'}) and 1 missing columns ({'The scene features a male voice speaking over a radio; with a background of a low hum and a distant rumble.'}).
This happened while the csv dataset builder was generating data using
hf://datasets/hzhongresearch/auditoryhum_supplementary/advance_file_list.csv (at revision 7a8d1491b524314e615cd70f24474a81e3266fe3), [/tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_captions.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_captions.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_file_list.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_file_list.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_gemma3n_e2b_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_gemma3n_e2b_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_gemma3n_e2b_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_gemma3n_e2b_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_provided_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_provided_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_human_strat.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_human_strat.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2_5o_labels_annotations.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2a_labels.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2a_labels.csv), /tmp/hf-datasets-cache/medium/datasets/31159790902375-config-parquet-and-info-hzhongresearch-auditoryhu-ffb0f8d7/hub/datasets--hzhongresearch--auditoryhum_supplementary/snapshots/7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2a_labels_annotations.csv (origin=hf://datasets/hzhongresearch/auditoryhum_supplementary@7a8d1491b524314e615cd70f24474a81e3266fe3/advance_qwen2a_labels_annotations.csv), 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Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)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.
The scene features a male voice speaking over a radio; with a background of a low hum and a distant rumble. string |
|---|
The scene is characterized by a constant; low-level hum of a machine; which is the main sound. There are also intermittent; brief instances of a male voice speaking; likely over a radio or similar communication device. |
The scene features a conversation between two men; with a background of a low hum and a faint; distant rumble. |
The scene is characterized by a blend of a low rumbling engine sound and intermittent radio chatter. |
The scene is characterized by a continuous background noise; likely from a radio; and intermittent speech from a man; possibly a pilot; speaking in a radio communication. |
The scene features a background of ocean waves crashing; accompanied by the sounds of children playing and talking; with a distant train horn blowing. |
The scene features a large crowd of people talking; with the sound of waves crashing in the background. |
The scene is characterized by a thunderstorm; with the sound of rain and wind; and the presence of birds chirping. |
The scene features the sound of waves crashing; birds chirping; and a distant thunderstorm. |
The scene is characterized by a blend of natural and man-made sounds. The prominent sound is the continuous sound of waves crashing; which is the primary source of the sound. Additionally; there are sounds of birds chirping and tweeting; which contribute to the natural ambiance. There are also sounds of people talking ... |
The audio features a bird chirping; which is the main sound; and a background of white noise. |
The scene is characterized by a low; dark; and ambient sound; with a blend of electronic and industrial elements. It has a suspenseful and mysterious atmosphere; with a touch of horror. The sound is described as a dark ambient drone; with a low; dark; and mysterious tone. It is also characterized as a |
The scene features a car passing by in the distance; accompanied by the sound of wind blowing; and a distant train horn. |
The scene features a slow; steady rhythm of footsteps on a hard surface; likely a sidewalk or concrete path; accompanied by the sound of a zipper being pulled. |
The scene is characterized by a blend of natural and urban sounds; featuring the chirping of birds; the barking of dogs; and the distant rumble of a passing train. |
The scene features a lively gathering of people; with a woman speaking and laughing; and the sound of birds chirping in the background. |
The scene is characterized by a steady; low hum that gradually rises in pitch; accompanied by the distant sound of a bird chirping. |
The scene is characterized by a background of children playing and laughing; with the sound of fireworks in the distance. |
The scene features a tennis match with the sound of a ball bouncing and a racket hitting it; along with the background noise of people talking. |
The scene is characterized by a blend of a steady; low-frequency hum and a high-pitched; sharp sound; accompanied by the distant sound of a child's voice. |
The audio features a lively scene with children playing and shouting; accompanied by the sound of a ball bouncing and a distant car horn. |
The audio features a background of crowd noise; which is then interrupted by the sound of a skateboard rolling on a hard surface. |
The scene is characterized by a sound that starts with a high-pitched; white noise; which then transitions into a low; continuous hum. |
The scene features a continuous; high-pitched; and loud sound that starts at the beginning and lasts for the entire duration of the audio. |
The scene features a large; continuous sound of waves crashing; accompanied by a distant; low-frequency rumbling. |
The audio features a sound that starts with a loud; high-pitched noise; which then transitions into a lower; more muffled tone. |
The audio features a sound that starts with a low; muffled noise; then transitions to a high-pitched; sharp noise; and finally to a low; muffled noise again. |
The scene features a loud; high-pitched sound that starts with a whooshing noise; followed by a whoosh and a whoosh again; and then a whoosh and a whoosh. |
The scene is dominated by the sound of a car engine revving up and down; accompanied by the sound of tires screeching. |
The scene is characterized by a loud explosion followed by a whoop; and then a long; sustained whoop. |
The scene features a large crowd of people clapping and cheering; with a distant; low; and rumbling sound of a large engine. |
The scene is characterized by a sudden explosion followed by a whooshing sound; then a series of whooshes and whooshes; and finally a whoosh sound. |
The audio features a rooster crowing; accompanied by the sounds of birds chirping and insects buzzing in the background. |
The audio features a rooster crowing; which is a distinct sound; and the background is filled with the noise of a machine. |
The audio features a rooster crowing; which is a clear and distinct sound. |
The audio features a rooster crowing in the background; accompanied by a distant; low hum. |
The audio features a rooster crowing; which is a common sound in rural settings; and a background noise that is described as a low; steady hum. |
The audio features a background of birds chirping and a distant train horn; with the sound of footsteps in shallow water throughout the clip. |
The scene features a man walking through water; accompanied by the sound of birds chirping in the background. |
The scene is characterized by a slow; steady rhythm of footsteps in wet sand; accompanied by the distant chirping of birds. |
The audio features a sound of footsteps on a wet surface; accompanied by the chirping of birds. |
The scene features a person walking on a wet surface; likely a sidewalk; with the sound of their footsteps and the sound of water splashing around them. The background is filled with the chirping of birds; creating a peaceful and natural atmosphere. |
The audio features a sound of a large wave crashing; which is described as a low; rumbling; and thunderous noise. |
The audio features a sound of a large body of water; like a river or a lake; with a continuous; low-frequency sound that gradually fades out. |
The scene features a soothing sound of waves crashing; which is then followed by a high-pitched; electronic tone that gradually fades out. |
The audio features a sound of a large wave crashing; which lasts for about 10 seconds. |
The audio features a sound of a large wave crashing; accompanied by the sound of wind blowing. |
The scene features a synthesizer playing a slow; dark; and eerie melody; accompanied by a deep; resonant bass. |
The audio features a background of nature sounds; including bird chirping and a distant dog barking; which are present throughout the entire clip. |
The audio features a sound that starts with a loud; thunderous noise; then transitions to a high-pitched; shrill tone. |
The scene features a lively outdoor gathering where a crowd is engaged in conversation; punctuated by shouts and a whistle. The sounds of footsteps and a faint motor vehicle are also present; suggesting the presence of a nearby road or park. |
The audio features a male singing a mantra; which is then followed by a fade out. |
The scene features a background of white noise; which is then followed by the sound of water dripping. |
The audio contains a sound of water dripping into a metal container; which is then followed by a low; dark; and mysterious tone. |
The scene is dominated by the sound of a car engine idling; which lasts for the entire duration of the audio clip. |
The audio features a zipper sound; followed by a whooshing sound; and then a low; sustained; and resonant tone. |
The scene is characterized by a serene atmosphere; featuring the chirping of birds and the sound of waves crashing against the shore. |
The audio features a bird chirping in the background; with a low; dark; and tense atmosphere. |
The audio features a bird chirping in the background; which is then followed by a series of electronic beeps. |
The audio features a background of birds chirping and singing; creating a peaceful atmosphere. |
The audio features a bird chirping in the background; followed by a low hum and a high hum. |
The audio features a background of birds chirping and singing; creating a lively atmosphere. |
The scene features the sound of water splashing; which is accompanied by the distant shouts of children. |
The audio features a sound that starts with a high-pitched; vibrating noise; which then transitions to a lower; more resonant tone. |
The scene is characterized by the sound of water flowing; which is described as a continuous and steady sound; and a digital hum; which is described as a high-pitched and sharp sound. |
The audio features a fast-paced; intense electronic music piece with a strong beat; a prominent bassline; and a synthesizer. It has a lively; energetic; and exciting mood. |
The audio features a blend of music and video game sounds; with a dominant electronic music track in the background. |
The scene features a lively pop song with a male vocalist; accompanied by a strong beat; synthesizer; and bass. The song is in the key of Bb minor with a 4/4 time signature and a tempo of 120.0 bpm. The lyrics are in English and the song has a |
The scene features a lively background music track with a fast tempo; a male singer; and a guitar; all in the key of C major. The music has a 4/4 time signature and a tempo of 176.0 bpm. |
The audio features a male singing in English with a soulful tone; accompanied by a background music that starts at 0.00 seconds and ends at 40.00 seconds. The music is in the key of C# minor with a 4/4 time signature and a tempo of 16 |
The audio features a sound of a wave crashing; which is then followed by a whooshing sound. |
The audio features a thunderstorm with rain and birds chirping in the background. |
The audio features a thunderstorm with rain and birds chirping; and a low rumbling sound. |
The audio features a thunderstorm in the background; with birds chirping and a distant train horn. |
The audio features a thunderstorm with rain and birds chirping; and a low; rumbling sound in the background. |
The audio features a thunderstorm in the background; with the sound of rain and birds chirping. |
The audio features a blend of a drum loop and a synth pad. The drum loop has a tempo of 120.0 bpm and a 4/4 time signature; with a chord progression that alternates between C major and G major. The synth pad has a duration of 10 seconds and is |
The audio features a background music track that plays throughout the entire clip. |
The audio features a blend of electronic and ambient sounds; including a synthesizer playing a melodic tune; a drum machine providing a steady rhythm; and a keyboard adding a layer of harmony. The overall atmosphere is calm and soothing; with a touch of mystery. |
The audio features a lively atmosphere with a fast-paced; upbeat music track playing in the background. The music is characterized by a fast tempo; a 4/4 time signature; and a chord progression that includes C major; G major; and A major. The music is played by a synthesizer; and the overall |
The scene features a background of music that is described as being in the key of G major; with a tempo of 136.0 bpm; and a 4/4 time signature. The music is characterized by a chord progression that alternates between G major and C major. |
The audio features a series of whoosh sounds; followed by a high-pitched tone; and then a low-pitched tone. |
The scene features a whoosh sound that starts at 0.00 seconds and lasts until 20.00 seconds; accompanied by a low hum that begins at 20.00 seconds and continues until 40.00 seconds. |
The scene features a whoosh sound followed by a cat meowing; then a whoosh sound again; and finally a whoosh sound with a low frequency and a long release. |
The scene features a slow; steady; and rhythmic sound of a clock ticking. |
The scene features a child's voice in the background; followed by the sound of a whip cracking; and then a low hum that transitions into a high-pitched tone. |
The scene features a door opening and closing; accompanied by the sound of a squeaky hinge; and the background is filled with the distant chirping of birds. |
The scene features a car engine running; with a squeaking sound and a low hum in the background. |
The scene features a squeaky door opening and closing; accompanied by a low hum and a distant; low-frequency sound. |
The audio features a door opening and closing; accompanied by squeaking and creaking sounds; and a low hum in the background. |
The scene is characterized by the sound of a door creaking and squeaking; which is accompanied by a low hum. |
The audio features a thunderstorm; with birds chirping in the background. |
The audio features a thunderstorm with a low rumble; accompanied by a high-pitched; eerie sound that gradually increases in volume. |
The audio features a thunderstorm with thunder and rain; accompanied by birds chirping and a distant train horn. |
The scene features a thunderstorm with a low rumble; accompanied by the sound of rain and wind. |
The scene is characterized by a thunderstorm; with the sound of thunder and birds chirping in the background. |
The scene features a loud; high-pitched; and eerie sound; likely a siren; that is accompanied by a distant; low-frequency; and more ominous sound. |
The scene is characterized by a blend of natural and synthetic sounds. The natural sounds include the sound of a thunderstorm; which is described as a deep; rumbling thunder. The synthetic sounds are a series of electronic beeps and a high-pitched; pulsing sound that resembles a heartbeat. These sounds are played in |
The scene features a siren sound that starts off loud and then gradually fades away; accompanied by a soft; distant background noise. |
The audio features a sound of a passing train; which is described as a loud; high-pitched; and somewhat eerie noise. |
The scene features a sound that starts with a whooshing noise; followed by a siren; and then a series of clicks. |
End of preview.
AuditoryHuM supplementary data
AuditoryHuM: Auditory Scene Label Generation and Clustering using Human-MLLM Collaboration. This is the supplementary material used to generate the results in the paper.
Description of data
| Files | Description |
|---|---|
| advance_file_list.csv | List of files and the order with which they are processed. |
| ahead-ds_file_list.csv | |
| tau2019_file_list.csv | |
| advance_provided_labels.csv | Labels provided by the creators of each dataset. |
| ahead-ds_provided_labels.csv | |
| tau2019_provided_labels.csv | |
| advance_gemma3n_e2b_labels.csv | Labels generated by MLLMs. |
| advance_qwen2a_labels.csv | |
| advance_qwen2_5o_labels.csv | |
| ahead-ds_gemma3n_e2b_labels.csv | |
| ahead-ds_qwen2a_labels.csv | |
| ahead-ds_qwen2_5o_labels.csv | |
| tau2019_gemma3n_e2b_labels.csv | |
| tau2019_qwen2a_labels.csv | |
| tau2019_qwen2_5o_labels.csv | |
| advance_gemma3n_e2b_labels_annotations.csv | Human provided labels. |
| advance_qwen2a_labels_annotations.csv | |
| advance_qwen2_5o_labels_annotations.csv | |
| ahead-ds_gemma3n_e2b_labels_annotations.csv | |
| ahead-ds_qwen2a_labels_annotations.csv | |
| ahead-ds_qwen2_5o_labels_annotations.csv | |
| tau2019_gemma3n_e2b_labels_annotations.csv | |
| tau2019_qwen2a_labels_annotations.csv | |
| tau2019_qwen2_5o_labels_annotations.csv | |
| advance_captions.csv | Captions generated by MLLM. |
| ahead-ds_captions.csv | |
| tau2019_captions.csv | |
| advance_qwen2_5o_human_strat.csv | More labels for testing human labelling strategy. |
Licence
Licenced under CC-BY-4.0. See LICENCE.txt.
Attribution.
@misc{zhong2026auditoryhumauditoryscenelabel,
title={AuditoryHuM: Auditory Scene Label Generation and Clustering using Human-MLLM Collaboration},
author={Henry Zhong and Jörg M. Buchholz and Julian Maclaren and Simon Carlile and Richard F. Lyon},
year={2026},
eprint={2602.19409},
archivePrefix={arXiv},
primaryClass={cs.SD},
url={https://arxiv.org/abs/2602.19409},
}
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