Dataset Preview
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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 5 new columns ({'0.849219', '0.305556', '111.240000', 'u5MPyrRJPmc', '108.240000'}) and 5 missing columns ({'233.266000', '0.780469', '0.670833', 'CJoOwXcjhds', '239.367000'}).
This happened while the csv dataset builder was generating data using
hf://datasets/bbrothers/avspeech-metadata/avspeech_test.csv (at revision c51a0db620e40bb0552c0d3fc1f13d68e93e5f95)
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
u5MPyrRJPmc: string
108.240000: double
111.240000: double
0.849219: double
0.305556: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 861
to
{'CJoOwXcjhds': Value('string'), '233.266000': Value('float64'), '239.367000': Value('float64'), '0.780469': Value('float64'), '0.670833': Value('float64')}
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 5 new columns ({'0.849219', '0.305556', '111.240000', 'u5MPyrRJPmc', '108.240000'}) and 5 missing columns ({'233.266000', '0.780469', '0.670833', 'CJoOwXcjhds', '239.367000'}).
This happened while the csv dataset builder was generating data using
hf://datasets/bbrothers/avspeech-metadata/avspeech_test.csv (at revision c51a0db620e40bb0552c0d3fc1f13d68e93e5f95)
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.
CJoOwXcjhds
string | 233.266000
float64 | 239.367000
float64 | 0.780469
float64 | 0.670833
float64 |
|---|---|---|---|---|
AvWWVOgaMlk
| 90
| 93.566667
| 0.586719
| 0.311111
|
Y8HMIm8mdns
| 171.607767
| 174.607767
| 0.505729
| 0.240741
|
akwvpAiLFk0
| 144.68
| 150
| 0.698438
| 0.288889
|
Swss72CHSWg
| 90.023267
| 97.2972
| 0.230729
| 0.20463
|
ymD5uLlLc0g
| 36.033
| 40.9
| 0.341667
| 0.475926
|
DuWE-CQDlEk
| 211.266667
| 221.7
| 0.788281
| 0.401389
|
uCGKDCWxqxo
| 16.56
| 30
| 0.420833
| 0.482407
|
-A9gdf3j2xo
| 295.165
| 298.165
| 0.507812
| 0.233333
|
labiHToR5nk
| 266.52
| 269.52
| 0.522656
| 0.243056
|
xbgfxIc-nbs
| 116.149367
| 119.986533
| 0.504167
| 0.45
|
QoQF8N5ZsQA
| 240.006433
| 244.961389
| 0.450781
| 0.358333
|
307DK9nGQhw
| 64.097367
| 73.006267
| 0.327604
| 0.17963
|
5qy9Ujv9XdM
| 61.494767
| 65.331933
| 0.557813
| 0.392593
|
UBL2Vowiulk
| 30.113422
| 33.616922
| 0.725
| 0.393056
|
LcyrfLT2tto
| 95.5985
| 98.5985
| 0.471094
| 0.409722
|
sujFCXbYkMo
| 30
| 34.466667
| 0.528906
| 0.477778
|
R0u9E8GsUXk
| 114.466667
| 118.166667
| 0.879687
| 0.829167
|
bNxD_breZy8
| 198.734
| 201.734
| 0.539062
| 0.240278
|
AQDWwktBhaw
| 30.03
| 40.807433
| 0.469531
| 0.293056
|
Dtn8xZ3BiGY
| 114.31
| 119.828
| 0.489063
| 0.316667
|
Cy9SUMj5wGY
| 16.133333
| 30
| 0.789062
| 0.598611
|
8nQBG5hvjpk
| 283.286
| 286.286
| 0.792188
| 0.348611
|
rCp8Jae81KU
| 257.6
| 260.6
| 0.711979
| 0.374074
|
PmD-LzPS2rg
| 282.5823
| 285.5853
| 0.371875
| 0.425
|
BrCcDt6GNkk
| 281.333333
| 284.466667
| 0.55
| 0.244444
|
IrXrbrZWflA
| 203.169
| 209.976
| 0.416146
| 0.271296
|
512K2S3De-A
| 282.6824
| 288.855233
| 0.514844
| 0.338889
|
01qWxISqaHg
| 87
| 90
| 0.46875
| 0.303977
|
2f32XSMYlDk
| 73.440033
| 77.844433
| 0.150521
| 0.163889
|
lcClO5lHEjA
| 120.086633
| 124.991533
| 0.439063
| 0.348611
|
q1doqKlHRuY
| 18.9
| 23.333333
| 0.102083
| 0.834259
|
tdTXVU5wN8I
| 188.32
| 199.28
| 0.492188
| 0.421296
|
h-fSfAFufCo
| 153.9538
| 160.226733
| 0.496354
| 0.378704
|
srwckJKdeS0
| 174.36
| 177.44
| 0.51875
| 0.702778
|
DIWf1t-HzwI
| 74.207467
| 77.210467
| 0.471875
| 0.405556
|
YXcVkIEMGds
| 295.08
| 300
| 0.390104
| 0.198148
|
BsUzOhJ9WGU
| 53.053
| 59.993
| 0.497396
| 0.45
|
JjduaMIoKvI
| 266.9697
| 269.9697
| 0.476562
| 0.366667
|
IlnHVjvBDU0
| 275.76
| 288.16
| 0.475
| 0.304167
|
zFH0QbS-l-w
| 287.153533
| 291.557933
| 0.53125
| 0.418056
|
h5wT_c4fQ1o
| 168.201367
| 179.9798
| 0.525521
| 0.27037
|
3AsPqH3QaQM
| 273.439833
| 282.949333
| 0.524219
| 0.259722
|
aaEA__Js2u0
| 270
| 273.266667
| 0.869531
| 0.7875
|
7rYeSDHS0U0
| 120
| 134.28
| 0.485156
| 0.276389
|
qpEzCs23PWE
| 134.100633
| 144.110633
| 0.501042
| 0.303704
|
8E2UlNrLNmk
| 50.721
| 53.721
| 0.4625
| 0.323148
|
BjvtZkHWExY
| 79.370958
| 89.506083
| 0.314063
| 0.197222
|
qzM4wshoqGs
| 91.36
| 94.36
| 0.555729
| 0.348148
|
871zAw-g1ZM
| 120.566667
| 124.133333
| 0.526563
| 0.386111
|
JpJoybtabbU
| 186.866667
| 190.566667
| 0.254167
| 0.465741
|
lUdymhI3Zl4
| 203
| 208.4
| 0.520833
| 0.403704
|
RdUVaYI3bmg
| 120.522522
| 127.861611
| 0.517708
| 0.09537
|
Uu1xVo0CF5o
| 106.5064
| 119.986533
| 0.552604
| 0.285185
|
WfpZPDqNNg0
| 260.433
| 269.999
| 0.723958
| 0.248148
|
G7xm-5aDZyg
| 114.52
| 120
| 0.486458
| 0.234259
|
jdshBkVfjrA
| 293.852
| 299.975
| 0.433594
| 0.476389
|
3gcWAZSNi2E
| 30.997633
| 38.204833
| 0.598958
| 0.317593
|
Wl3HSpsiIb4
| 229.646089
| 235.360122
| 0.627344
| 0.226389
|
yeqK6kqoIYk
| 221.2
| 227.68
| 0.306792
| 0.295833
|
YWgXhe7JYp4
| 144.602789
| 149.899756
| 0.835417
| 0.151852
|
ReXQGb2k3fo
| 11.166667
| 22.2
| 0.417187
| 0.429167
|
2RvWHWhyx1w
| 56.993267
| 59.993267
| 0.527344
| 0.375
|
AOoqrXx5BNU
| 164.3
| 177.267
| 0.541146
| 0.544444
|
_8K1hWkirLo
| 90
| 96.64
| 0.494271
| 0.300926
|
cPUBnjqIaXI
| 189.933333
| 195.466667
| 0.797656
| 0.443056
|
342Pxxa7n8Q
| 253.2
| 256.56
| 0.308854
| 0.371296
|
umcJyBaatBs
| 105.533333
| 119.466667
| 0.607031
| 0.408333
|
QYnLgIsR3bc
| 180.5804
| 184.150633
| 0.492969
| 0.277778
|
ohd_xOV6zW4
| 56.993
| 59.993
| 0.515104
| 0.469444
|
DxpQmBfA6vM
| 83.086
| 86.086
| 0.314583
| 0.442593
|
xwxbJkXRJHw
| 247.64
| 254.12
| 0.455469
| 0.201389
|
Gqt1A6O6UTk
| 66.3
| 69.366
| 0.759375
| 0.181944
|
YOySUCOJUtQ
| 127.994533
| 141.107633
| 0.566406
| 0.240278
|
ft3fl0x3gFo
| 232.966
| 240
| 0.520312
| 0.445833
|
7DBdAnTuw5c
| 61.394667
| 66.524789
| 0.503125
| 0.242593
|
ibPOxQ7XYPk
| 30.16
| 37.44
| 0.478125
| 0.263889
|
ausPEm5ZWQE
| 76.916667
| 90
| 0.39604
| 0.286111
|
a2iQ7kB5b6s
| 136.28
| 140.76
| 0.517188
| 0.446296
|
WddCvVatDlo
| 240
| 251.3
| 0.6375
| 0.558333
|
04BgTYq4Ckk
| 273.25
| 284.042
| 0.539844
| 0.452778
|
wBDD5wTG7P0
| 200.866
| 207.766
| 0.432031
| 0.201389
|
6LapKTptu8w
| 162.033
| 172.799
| 0.517188
| 0.216667
|
gX8qtrFaLs4
| 120.9238
| 123.9238
| 0.496354
| 0.306481
|
XXtkzCkzA64
| 106.92
| 119.92
| 0.608333
| 0.313889
|
TH0xt8XIvVs
| 120.007
| 134.352
| 0.549219
| 0.295833
|
H2VCPO0isFQ
| 31.489789
| 35.744044
| 0.817708
| 0.127778
|
aVP0dc3dvtA
| 143.41
| 149.984
| 0.485938
| 0.27963
|
5fnzANZN-O4
| 120.125
| 135.058333
| 0.558333
| 0.220833
|
alHB2f34oRI
| 115.482033
| 119.586133
| 0.568229
| 0.280556
|
98iIikUQgWQ
| 233.666
| 239.989
| 0.522656
| 0.376389
|
81jh1rIVC0g
| 257.96
| 263.08
| 0.5
| 0.249074
|
UVDnhj-jZl0
| 106.2
| 110.333333
| 0.875
| 0.854167
|
awqKt7frvJI
| 166.36
| 169.36
| 0.549219
| 0.25
|
RfP2dOHPej8
| 232.498933
| 239.872967
| 0.710156
| 0.347222
|
GtM2sM6r3So
| 124.257467
| 131.9318
| 0.483594
| 0.341667
|
k3NzaNrdALo
| 74.066667
| 77.166667
| 0.699219
| 0.358333
|
vK-snIInirc
| 138.1
| 149.566667
| 0.825521
| 0.4375
|
r3N3LCHqjdI
| 164.430933
| 176.860022
| 0.457292
| 0.268519
|
gOWL5FwU4c4
| 37.68
| 42.8
| 0.496868
| 0.354167
|
MZnQ3eZuUAE
| 241.96
| 245.24
| 0.651563
| 0.441667
|
End of preview.
YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
AVSpeech Metadata Files
This repository contains the metadata CSV files for the AVSpeech dataset by Google Research.
Dataset Description
AVSpeech is a large-scale audio-visual speech dataset containing over 290,000 video segments from YouTube, designed for audio-visual speech recognition and lip reading research.
Files
avspeech_train.csv(128 MB) - Training set with 2,621,845 video segments from 270k videosavspeech_test.csv(9 MB) - Test set with video segments from a separate set of 22k videos
CSV Format
Each row contains:
YouTube ID, start_time, end_time, x_coordinate, y_coordinate
Where:
- YouTube ID: The YouTube video identifier
- start_time: Start time of the segment in seconds
- end_time: End time of the segment in seconds
- x_coordinate: X coordinate of the speaker's face center (normalized 0.0-1.0, 0.0 = left)
- y_coordinate: Y coordinate of the speaker's face center (normalized 0.0-1.0, 0.0 = top)
The train and test sets have disjoint speakers.
Usage
With Hugging Face Hub
from huggingface_hub import hf_hub_download
# Download train CSV
train_csv = hf_hub_download(
repo_id="bbrothers/avspeech-metadata",
filename="avspeech_train.csv",
repo_type="dataset"
)
# Download test CSV
test_csv = hf_hub_download(
repo_id="bbrothers/avspeech-metadata",
filename="avspeech_test.csv",
repo_type="dataset"
)
With our dataset loader
from ml.data.av_speech.dataset import AVSpeechDataset
# Initialize dataset (will auto-download CSVs if needed)
dataset = AVSpeechDataset()
# Download videos
dataset.download(
splits=['train', 'test'],
max_videos=100, # Or None for all videos
num_workers=4
)
Citation
If you use this dataset, please cite the original AVSpeech paper:
@inproceedings{ephrat2018looking,
title={Looking to listen at the cocktail party: A speaker-independent audio-visual model for speech separation},
author={Ephrat, Ariel and Mosseri, Inbar and Lang, Oran and Dekel, Tali and Wilson, Kevin and Hassidim, Avinatan and Freeman, William T and Rubinstein, Michael},
booktitle={ACM SIGGRAPH 2018},
year={2018}
}
Links
Notes
- This repository only contains the metadata CSV files, not the actual video content
- Videos must be downloaded from YouTube using the provided YouTube IDs
- Some videos may no longer be available (deleted, private, or geo-blocked)
- Estimated total dataset size: ~4500 hours of video
- Downloads last month
- 38