Voice Note Audio And Training
Collection
Datasets for STT training, classification fine-tuning - especially voice notes
•
2 items
•
Updated
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 4 new columns ({'version', 'updated', 'description', 'schema'}) and 6 missing columns ({'text_metrics', 'audio_metadata', 'temporal', 'original_id', 'export_id', 'annotations'}).
This happened while the json dataset builder was generating data using
hf://datasets/danielrosehill/Voice-Note-Audio/schema/annotation_schema_v1.json (at revision 79e629e6a2d8eb5aca97cefc31eb1199efa2e33a)
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 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
version: string
updated: timestamp[s]
description: string
schema: struct<classification: struct<description: string, type: string, categories: list<item: struct<id: s (... 652 chars omitted)
child 0, classification: struct<description: string, type: string, categories: list<item: struct<id: string, label: string, d (... 21 chars omitted)
child 0, description: string
child 1, type: string
child 2, categories: list<item: struct<id: string, label: string, description: string>>
child 0, item: struct<id: string, label: string, description: string>
child 0, id: string
child 1, label: string
child 2, description: string
child 1, audio_defects: struct<description: string, type: string, categories: list<item: struct<id: string, label: string, d (... 21 chars omitted)
child 0, description: string
child 1, type: string
child 2, categories: list<item: struct<id: string, label: string, description: string>>
child 0, item: struct<id: string, label: string, description: string>
child 0, id: string
child 1, label: string
child 2, description: string
child 2, content_issues: struct<description: string, type: string, categories: list<item: struct<id: string, label: string, d (... 21 chars omitted)
child 0, description: string
child 1, type: string
child 2, categories: list<item: struct<id: string, label: string, description: string>>
child 0, item: struct<id: string, label: string, description: string>
child 0, id: string
child 1, label: string
child 2, description: string
child 3, languages: struct<description: string, type: string, categories: list<item: struct<id: string, label: string, d (... 21 chars omitted)
child 0, description: string
child 1, type: string
child 2, categories: list<item: struct<id: string, label: string, description: string>>
child 0, item: struct<id: string, label: string, description: string>
child 0, id: string
child 1, label: string
child 2, description: string
child 4, transcription_quality: struct<description: string, type: string, categories: list<item: struct<id: string, label: string, d (... 21 chars omitted)
child 0, description: string
child 1, type: string
child 2, categories: list<item: struct<id: string, label: string, description: string>>
child 0, item: struct<id: string, label: string, description: string>
child 0, id: string
child 1, label: string
child 2, description: string
child 5, notes: struct<description: string, type: string>
child 0, description: string
child 1, type: string
to
{'original_id': Value('int64'), 'export_id': Value('int64'), 'audio_metadata': {'duration_seconds': Value('float64'), 'duration_formatted': Value('string'), 'bitrate': Value('int64'), 'sample_rate': Value('int64'), 'channels': Value('int64'), 'file_size_mb': Value('float64'), 'audio_codec': Value('null')}, 'text_metrics': {'word_count': Value('int64'), 'character_count': Value('int64'), 'unique_word_count': Value('int64'), 'lexical_diversity': Value('float64'), 'sentence_count': Value('int64'), 'wpm': Value('float64')}, 'temporal': {'upload_timestamp': Value('string'), 'recording_date': Value('timestamp[s]'), 'recording_time_of_day': Value('string')}, 'annotations': List(Value('null'))}
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 1455, 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 1054, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, 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 1833, 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 4 new columns ({'version', 'updated', 'description', 'schema'}) and 6 missing columns ({'text_metrics', 'audio_metadata', 'temporal', 'original_id', 'export_id', 'annotations'}).
This happened while the json dataset builder was generating data using
hf://datasets/danielrosehill/Voice-Note-Audio/schema/annotation_schema_v1.json (at revision 79e629e6a2d8eb5aca97cefc31eb1199efa2e33a)
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.
original_id
int64 | export_id
int64 | audio_metadata
dict | text_metrics
dict | temporal
dict | annotations
list |
|---|---|---|---|---|---|
101
| 1
|
{
"duration_seconds": 65.74,
"duration_formatted": "1:05",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 1.51,
"audio_codec": null
}
|
{
"word_count": 108,
"character_count": 710,
"unique_word_count": 72,
"lexical_diversity": 0.667,
"sentence_count": 4,
"wpm": 98.6
}
|
{
"upload_timestamp": "2025-10-27T01:49:44.006780",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
92
| 10
|
{
"duration_seconds": 54.78,
"duration_formatted": "0:54",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 1.25,
"audio_codec": null
}
|
{
"word_count": 121,
"character_count": 655,
"unique_word_count": 85,
"lexical_diversity": 0.702,
"sentence_count": 5,
"wpm": 132.5
}
|
{
"upload_timestamp": "2025-10-27T01:47:04.155863",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
2
| 100
|
{
"duration_seconds": 117.26,
"duration_formatted": "1:57",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 2.68,
"audio_codec": null
}
|
{
"word_count": 150,
"character_count": 877,
"unique_word_count": 84,
"lexical_diversity": 0.56,
"sentence_count": 7,
"wpm": 76.8
}
|
{
"upload_timestamp": "2025-10-27T02:21:23.107047",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
1
| 101
|
{
"duration_seconds": 182.66,
"duration_formatted": "3:02",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 4.18,
"audio_codec": null
}
|
{
"word_count": 296,
"character_count": 1804,
"unique_word_count": 161,
"lexical_diversity": 0.544,
"sentence_count": 12,
"wpm": 97.2
}
|
{
"upload_timestamp": "2025-10-27T02:07:57.426277",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
91
| 11
|
{
"duration_seconds": 66.61,
"duration_formatted": "1:06",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 1.53,
"audio_codec": null
}
|
{
"word_count": 95,
"character_count": 567,
"unique_word_count": 63,
"lexical_diversity": 0.663,
"sentence_count": 5,
"wpm": 85.6
}
|
{
"upload_timestamp": "2025-10-27T01:46:45.655990",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
90
| 12
|
{
"duration_seconds": 53.58,
"duration_formatted": "0:53",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 1.23,
"audio_codec": null
}
|
{
"word_count": 94,
"character_count": 564,
"unique_word_count": 62,
"lexical_diversity": 0.66,
"sentence_count": 4,
"wpm": 105.3
}
|
{
"upload_timestamp": "2025-10-27T01:46:17.731230",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
89
| 13
|
{
"duration_seconds": 55.78,
"duration_formatted": "0:55",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 1.28,
"audio_codec": null
}
|
{
"word_count": 92,
"character_count": 548,
"unique_word_count": 57,
"lexical_diversity": 0.62,
"sentence_count": 5,
"wpm": 99
}
|
{
"upload_timestamp": "2025-10-27T01:46:01.221828",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
88
| 14
|
{
"duration_seconds": 44.9,
"duration_formatted": "0:44",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 1.03,
"audio_codec": null
}
|
{
"word_count": 114,
"character_count": 641,
"unique_word_count": 69,
"lexical_diversity": 0.605,
"sentence_count": 5,
"wpm": 152.3
}
|
{
"upload_timestamp": "2025-10-27T01:45:46.065039",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
87
| 15
|
{
"duration_seconds": 39.94,
"duration_formatted": "0:39",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 0.91,
"audio_codec": null
}
|
{
"word_count": 90,
"character_count": 473,
"unique_word_count": 59,
"lexical_diversity": 0.656,
"sentence_count": 5,
"wpm": 135.2
}
|
{
"upload_timestamp": "2025-10-27T01:45:30.648655",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
86
| 16
|
{
"duration_seconds": 35.78,
"duration_formatted": "0:35",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 0.82,
"audio_codec": null
}
|
{
"word_count": 70,
"character_count": 413,
"unique_word_count": 55,
"lexical_diversity": 0.786,
"sentence_count": 3,
"wpm": 117.4
}
|
{
"upload_timestamp": "2025-10-27T01:45:16.694906",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
85
| 17
|
{
"duration_seconds": 168.65,
"duration_formatted": "2:48",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 3.86,
"audio_codec": null
}
|
{
"word_count": 355,
"character_count": 1870,
"unique_word_count": 181,
"lexical_diversity": 0.51,
"sentence_count": 15,
"wpm": 126.3
}
|
{
"upload_timestamp": "2025-10-27T01:44:29.769433",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
84
| 18
|
{
"duration_seconds": 38.78,
"duration_formatted": "0:38",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 0.89,
"audio_codec": null
}
|
{
"word_count": 74,
"character_count": 395,
"unique_word_count": 53,
"lexical_diversity": 0.716,
"sentence_count": 1,
"wpm": 114.5
}
|
{
"upload_timestamp": "2025-10-27T01:44:06.362952",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
83
| 19
|
{
"duration_seconds": 106.78,
"duration_formatted": "1:46",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 2.44,
"audio_codec": null
}
|
{
"word_count": 189,
"character_count": 1196,
"unique_word_count": 117,
"lexical_diversity": 0.619,
"sentence_count": 8,
"wpm": 106.2
}
|
{
"upload_timestamp": "2025-10-27T01:43:50.645428",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
100
| 2
|
{
"duration_seconds": 45.5,
"duration_formatted": "0:45",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 1.04,
"audio_codec": null
}
|
{
"word_count": 103,
"character_count": 601,
"unique_word_count": 72,
"lexical_diversity": 0.699,
"sentence_count": 6,
"wpm": 135.8
}
|
{
"upload_timestamp": "2025-10-27T01:49:24.498335",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
82
| 20
|
{
"duration_seconds": 54.33,
"duration_formatted": "0:54",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 1.24,
"audio_codec": null
}
|
{
"word_count": 125,
"character_count": 736,
"unique_word_count": 77,
"lexical_diversity": 0.616,
"sentence_count": 8,
"wpm": 138
}
|
{
"upload_timestamp": "2025-10-27T01:43:12.731654",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
81
| 21
|
{
"duration_seconds": 160.03,
"duration_formatted": "2:40",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 3.66,
"audio_codec": null
}
|
{
"word_count": 405,
"character_count": 2186,
"unique_word_count": 205,
"lexical_diversity": 0.506,
"sentence_count": 18,
"wpm": 151.8
}
|
{
"upload_timestamp": "2025-10-27T01:41:01.938865",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
80
| 22
|
{
"duration_seconds": 149.58,
"duration_formatted": "2:29",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 3.42,
"audio_codec": null
}
|
{
"word_count": 187,
"character_count": 1046,
"unique_word_count": 108,
"lexical_diversity": 0.578,
"sentence_count": 11,
"wpm": 75
}
|
{
"upload_timestamp": "2025-10-27T01:40:45.391810",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
79
| 23
|
{
"duration_seconds": 48.46,
"duration_formatted": "0:48",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 1.11,
"audio_codec": null
}
|
{
"word_count": 79,
"character_count": 475,
"unique_word_count": 52,
"lexical_diversity": 0.658,
"sentence_count": 3,
"wpm": 97.8
}
|
{
"upload_timestamp": "2025-10-27T01:40:27.009086",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
78
| 24
|
{
"duration_seconds": 104.83,
"duration_formatted": "1:44",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 2.4,
"audio_codec": null
}
|
{
"word_count": 199,
"character_count": 1039,
"unique_word_count": 124,
"lexical_diversity": 0.623,
"sentence_count": 16,
"wpm": 113.9
}
|
{
"upload_timestamp": "2025-10-27T01:40:07.434558",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
77
| 25
|
{
"duration_seconds": 19.12,
"duration_formatted": "0:19",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 0.44,
"audio_codec": null
}
|
{
"word_count": 46,
"character_count": 212,
"unique_word_count": 40,
"lexical_diversity": 0.87,
"sentence_count": 3,
"wpm": 144.4
}
|
{
"upload_timestamp": "2025-10-27T01:39:55.634910",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
76
| 26
|
{
"duration_seconds": 258.3,
"duration_formatted": "4:18",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 5.91,
"audio_codec": null
}
|
{
"word_count": 516,
"character_count": 2789,
"unique_word_count": 233,
"lexical_diversity": 0.452,
"sentence_count": 21,
"wpm": 119.9
}
|
{
"upload_timestamp": "2025-10-27T01:39:20.700196",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
75
| 27
|
{
"duration_seconds": 199.9,
"duration_formatted": "3:19",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 4.58,
"audio_codec": null
}
|
{
"word_count": 447,
"character_count": 2451,
"unique_word_count": 210,
"lexical_diversity": 0.47,
"sentence_count": 20,
"wpm": 134.2
}
|
{
"upload_timestamp": "2025-10-27T01:39:03.749136",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
74
| 28
|
{
"duration_seconds": 67.81,
"duration_formatted": "1:07",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 1.55,
"audio_codec": null
}
|
{
"word_count": 153,
"character_count": 852,
"unique_word_count": 93,
"lexical_diversity": 0.608,
"sentence_count": 10,
"wpm": 135.4
}
|
{
"upload_timestamp": "2025-10-27T01:38:45.132245",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
73
| 29
|
{
"duration_seconds": 27.98,
"duration_formatted": "0:27",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 0.64,
"audio_codec": null
}
|
{
"word_count": 54,
"character_count": 302,
"unique_word_count": 43,
"lexical_diversity": 0.796,
"sentence_count": 4,
"wpm": 115.8
}
|
{
"upload_timestamp": "2025-10-27T01:38:29.682105",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
99
| 3
|
{
"duration_seconds": 142.47,
"duration_formatted": "2:22",
"bitrate": 192000,
"sample_rate": 44100,
"channels": 2,
"file_size_mb": 3.26,
"audio_codec": null
}
|
{
"word_count": 297,
"character_count": 1671,
"unique_word_count": 148,
"lexical_diversity": 0.498,
"sentence_count": 10,
"wpm": 125.1
}
|
{
"upload_timestamp": "2025-10-27T01:48:53.637285",
"recording_date": "2025-10-27T00:00:00",
"recording_time_of_day": "night"
}
|
[] |
72
| 30
|
{
"duration_seconds": 83.62,
"duration_formatted": "1:23",
"bitrate": 192000,
"sample_rate": 48000,
"channels": 1,
"file_size_mb": 1.91,
"audio_codec": null
}
|
{
"word_count": 208,
"character_count": 1160,
"unique_word_count": 106,
"lexical_diversity": 0.51,
"sentence_count": 19,
"wpm": 149.2
}
|
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"recording_date": "2025-10-27T00:00:00",
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}
|
[] |
7
| 95
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{
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"recording_date": "2025-10-27T00:00:00",
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|
[] |
6
| 96
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{
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|
{
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"recording_time_of_day": "night"
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|
[] |
5
| 97
|
{
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|
{
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{
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|
[] |
4
| 98
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{
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{
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|
{
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|
[] |
End of preview.
YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
Voice Notes Dataset
Dataset Description
This dataset contains real-world voice recordings with transcripts and comprehensive annotations.
Dataset Statistics
- Total Entries: 2
- Audio Files: 2
- Uncorrected Transcripts: 2
- Ground Truth Transcripts: 0
- Annotation Files: 2
- Export Date: 2025-10-27
Dataset Structure
audio/ # Audio recordings (MP3, etc.)
├── 1.mp3
├── 2.mp3
└── ...
transcripts/
├── uncorrected/ # Original STT transcripts
│ ├── 1.txt
│ ├── 2.txt
│ └── ...
└── ground_truths/ # Corrected transcripts (when available)
├── 1.txt
├── 2.txt
└── ...
annotations/ # Metadata and annotations
├── 1.json
├── 2.json
└── ...
Annotation Schema
Each annotation file contains:
- Audio metadata (duration, bitrate, sample rate, etc.)
- Text metrics (word count, WPM, lexical diversity)
- Temporal information (recording date, time of day)
- Custom annotations (audio quality, classification, etc.)
Use Cases
- Real-World STT Evaluation: Test speech-to-text models on non-ideal conditions
- Voice Note Classification: Train models to categorize voice notes
- Audio Quality Assessment: Analyze impact of background noise on transcription
Citation
If you use this dataset, please cite:
@dataset{voice_notes_dataset,
author = {Daniel Rosehill},
title = {Voice Notes Dataset},
year = {2025},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/datasets/...}}
}
License
[Specify your license here]
Contact
For questions or feedback, please contact: [email protected]
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