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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type
double
to
List(Value('float64'))
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2223, in cast_table_to_schema
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2224, in <listcomp>
cast_array_to_feature(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2092, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
double
to
List(Value('float64'))
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 1451, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 994, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1858, 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.
meeting_type
string | room_size
list | room_type
string | rt60
float64 | fs
int64 | array_num
int64 | circle array's mic_num
int64 | circle array's center_pos
list | linear array's mic_num
int64 | linear array's center_pos
list | host_label
string | src_num
int64 | src_pos
list | SRR
float64 | DRR
float64 | point noise SNR
int64 | diffuse noise SNR
int64 | gain
list | avg_SNR
list | audio_len
float64 | vad_dur
float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
speech
|
[
8.452962337201681,
7.997692667324846,
4.813992992131043
] |
middle
| 0.77 | 16,000 | 1 | 4 |
[
[
3.1864811686008405,
3.998846333662423
],
[
8.15296233720168,
3.998846333662423
]
] | 8 |
[
8.15296233720168,
3.998846333662423
] |
aishell_1_0081
| 13 |
[
[
4.143658300167482,
4.681278500519514,
1.389
],
[
1.003399562516245,
2.982414770178338,
1.28
],
[
2.305456418740266,
3.1225517600891104,
1.377
],
[
2.924330723596281,
3.0581065515334025,
1.234
],
[
4.241302625665026,
5.690023479988722,
1.283
],
[
3.258958119700071,
4.288007924697927,
1.279
],
[
3.6896594967058216,
2.283481705404528,
1.384
],
[
5.381881641832949,
2.928841614939504,
1.338
],
[
3.2939469058670845,
5.087291999896971,
1.311
],
[
4.708809569515716,
2.0932848027144653,
1.218
],
[
4.640528655916501,
5.313035255616892,
1.326
],
[
2.293760655861684,
5.828199312761888,
1.274
]
] | 1.179472 | -5.811952 | 2 | 6 |
[
1.2281979268288739,
3.989982619236166,
3.3895233184935667,
3.531890103837567,
1.5940334411777193,
1.2249838712248273,
1.1882712331444814,
3.641399343506436,
3.9762177339842264,
4.593234244334342,
4.404189128356041,
4.844689176621928,
3.2164898522317857,
4.9857252690596905
] |
[
0.029980707553241122,
0.1773217516158913
] | 898.171 | 761.979 |
speech
|
[
9.475441571557885,
7.900973400094324,
4.877561943728762
] |
middle
| 0.65 | 16,000 | 1 | 6 |
[
[
3.6577207857789427,
3.950486700047162
],
[
9.175441571557885,
3.950486700047162
]
] | 8 |
[
9.175441571557885,
3.950486700047162
] |
aishell_1_0048
| 11 |
[
[
1.6532078428791053,
3.392718466106184,
1.296
],
[
3.8374839594268453,
3.9166889737543893,
1.276
],
[
3.5187726807635746,
3.580381766714042,
1.399
],
[
3.474911818078655,
6.289199280477275,
1.323
],
[
4.987335880698108,
5.303919431937251,
1.332
],
[
3.272313780395953,
1.904230082814208,
1.252
],
[
5.278479278800551,
4.816073081855011,
1.227
],
[
2.401222253028871,
2.910470882944491,
1.348
],
[
4.1065516768279915,
4.390800891214232,
1.379
],
[
4.637749391358401,
2.8590015844464665,
1.342
]
] | 1.797345 | -5.52182 | 2 | 5 |
[
2.6385719101447003,
2.844853032383726,
2.317778849524054,
4.132191578092523,
3.6545649364139874,
1.5328811253792534,
3.1191482262097625,
1.3089639704740534,
2.879237108627045,
2.3941757572290627,
1.566387385073853,
1.8564662013917501
] |
[
-1.9693264601900096,
-1.435280718322775
] | 823.976 | 703.845 |
speech
|
[
9.319455192941078,
7.518278852766072,
4.684774280829166
] |
middle
| 0.58 | 16,000 | 1 | 6 |
[
[
3.579727596470539,
3.759139426383036
],
[
9.019455192941077,
3.759139426383036
]
] | 8 |
[
9.019455192941077,
3.759139426383036
] |
libri_2007
| 17 |
[
[
1.8587760825787105,
4.3206634288163555,
1.297
],
[
4.486022719385444,
3.7239414994307527,
1.314
],
[
4.17976902585012,
1.893180433556257,
1.294
],
[
3.162214733363551,
5.361948914739197,
1.281
],
[
3.944350483396549,
2.8294107940723228,
1.387
],
[
3.3664537160484462,
4.099641496607374,
1.305
],
[
3.7626241467253525,
4.410551172978948,
1.21
],
[
3.687226759478791,
3.7431004805960835,
1.216
],
[
3.713142602249014,
3.1776034844661787,
1.2
],
[
4.233196986736894,
4.52066786837755,
1.317
],
[
4.227736075867461,
3.2599169576231692,
1.36
],
[
5.482017609009799,
3.7188424450210946,
1.272
],
[
5.1418903016288136,
4.411574135308664,
1.374
],
[
1.7002191728925393,
2.3506784675090837,
1.293
],
[
2.3493183234943267,
5.245606738401193,
1.293
],
[
3.2350640915220907,
3.512954338121906,
1.396
]
] | 3.199267 | -4.359558 | 4 | 5 |
[
4.95322624517229,
4.4250093712131235,
3.4485899591248277,
2.052437028781726,
2.512842761017079,
4.085336322306162,
2.6955821690632398,
1.132695199135639,
4.682056458905128,
3.3368423568679377,
1.6841165574178296,
4.299771067736403,
4.72146182600976,
3.7033972429122364,
1.3694650322590811,
4.577731934602478,
1.2488152833727302,
3.1074838123777844
] |
[
-2.5296151817641035,
-1.9797552768570839
] | 1,767.214 | 1,656.46 |
speech
|
[
9.951425869958369,
7.337213625095212,
4.886609614121968
] |
middle
| 0.56 | 16,000 | 1 | 4 |
[
[
3.9757129349791844,
3.668606812547606
],
[
9.651425869958368,
3.668606812547606
]
] | 8 |
[
9.651425869958368,
3.668606812547606
] |
aishell_1_0003
| 19 |
[
[
4.041923611875185,
3.4045482741542106,
1.288
],
[
4.675688739366896,
4.20323059215072,
1.218
],
[
4.11529958928503,
1.7258867049761042,
1.353
],
[
4.012327039659131,
3.9578248692869797,
1.387
],
[
2.7852433305393336,
3.578053631241638,
1.344
],
[
2.214954903887413,
2.4069131341838856,
1.391
],
[
5.617199474797809,
2.0162071658571286,
1.344
],
[
4.484803076974365,
3.2979823181699843,
1.264
],
[
4.742785365837152,
2.056479561414992,
1.298
],
[
3.2360082720817083,
3.239967748540583,
1.281
],
[
3.8073107901842205,
2.961526706780034,
1.262
],
[
5.175667846618011,
3.4807672175511635,
1.324
],
[
6.359039193924055,
1.884980715216829,
1.344
],
[
3.362369490567003,
2.5299303053929174,
1.277
],
[
3.2435387809485454,
5.283618380594812,
1.304
],
[
1.9370237800268812,
5.904198702174666,
1.254
],
[
4.50800268561181,
4.535121861642944,
1.259
],
[
3.7890305926598478,
1.672424692223245,
1.237
]
] | 3.436264 | -4.220023 | 2 | 8 |
[
4.9770822909397125,
1.4025922562315891,
4.942062198957956,
4.105159273496225,
1.279210026680682,
3.8663563492643997,
1.822640359973935,
3.121291636995405,
1.2309246744123334,
3.6054991497266204,
4.742105248169764,
1.8323109285820416,
3.779133378334546,
3.7050946829184817,
1.2016639436749958,
4.957054149293864,
1.032983419137926,
1.5083793492091315,
2.777314709464033,
4.267361001724268
] |
[
3.5298585700755565,
2.929143024083943
] | 2,030.833 | 1,858.479 |
speech
|
[
9.82459137542946,
7.211189575794183,
4.044383112555088
] |
middle
| 0.73 | 16,000 | 1 | 6 |
[
[
3.87229568771473,
3.6055947878970915
],
[
9.524591375429459,
3.6055947878970915
]
] | 8 |
[
9.524591375429459,
3.6055947878970915
] |
aishell_1_0002
| 14 |
[
[
2.9770331143653372,
2.046731009922788,
1.21
],
[
2.717118670414334,
2.4874699680866694,
1.212
],
[
2.921713681540661,
4.667825945968941,
1.34
],
[
3.885514335707844,
3.432426014616733,
1.275
],
[
4.444368348330958,
3.811621885141946,
1.216
],
[
4.919910821195482,
5.853778819984189,
1.364
],
[
4.052074346419511,
1.682220984251886,
1.241
],
[
2.202988801024957,
4.334269746292379,
1.353
],
[
4.33309909099935,
6.590932160770519,
1.304
],
[
3.4814500651222358,
3.6141597512717416,
1.381
],
[
4.797863356896225,
3.436126918455601,
1.292
],
[
2.5735250076277723,
4.109822109104878,
1.252
],
[
5.596386791148817,
3.8833483025241007,
1.329
]
] | 1.546632 | -6.110805 | 3 | 4 |
[
2.8112404483053135,
3.2200002011213895,
3.3985277202151885,
4.988921263084325,
4.276192412850287,
1.8904372185896112,
2.762229437700113,
4.7901121240974085,
1.3832511338590345,
3.0223329926961093,
2.9131240616329337,
1.2999983684795988,
2.6930942699227858,
1.813070473134415,
3.658751336691573
] |
[
-1.922740424528849,
-2.317119572279397
] | 831.508 | 702.899 |
speech
|
[
9.31959687002039,
7.051648648676726,
4.295549115205281
] |
middle
| 0.6 | 16,000 | 1 | 4 |
[
[
3.6197984350101953,
3.525824324338363
],
[
9.01959687002039,
3.525824324338363
]
] | 8 |
[
9.01959687002039,
3.525824324338363
] |
aishell_1_0016
| 18 |
[
[
5.360760413395232,
2.3668245398166894,
1.35
],
[
3.793527136180609,
3.3122027314547706,
1.273
],
[
1.283671059041831,
1.8312743573071524,
1.251
],
[
2.951776285587355,
5.0325107405670355,
1.374
],
[
3.57204194438174,
2.1721764809116513,
1.373
],
[
5.451013909812479,
5.52923027865642,
1.203
],
[
3.873854752604856,
2.7366838119435757,
1.281
],
[
4.306552604376752,
3.6251219428973287,
1.33
],
[
2.285784492235608,
2.5142702763030975,
1.367
],
[
3.3727090579899905,
6.431594176676087,
1.273
],
[
4.242472263318929,
3.0225327494257623,
1.215
],
[
5.613653391326041,
1.8820935040250377,
1.308
],
[
4.008630124655794,
1.4438715688313626,
1.389
],
[
0.9003071997717753,
3.0425503989761484,
1.253
],
[
4.73959274726214,
2.435970980665207,
1.249
],
[
1.8098609543525719,
3.340053976510674,
1.338
],
[
3.9593107113302133,
4.102276994806689,
1.311
]
] | 2.565379 | -4.915805 | 4 | 6 |
[
1.5989970114722367,
2.623887885265467,
3.2471142205667416,
3.1634870067720007,
1.1034119806830391,
4.982202723954021,
1.7098458127549505,
3.13619836042491,
1.5151781571156708,
2.21998202913302,
3.93897991938105,
2.145557136525662,
4.4057770096777595,
3.9114383372580916,
1.511500678887979,
4.916549551483545,
3.4724949983774835,
3.6772282343927194,
2.5102155961244734
] |
[
0.01825448974203299,
-0.29469275400121236
] | 799.405 | 674.302 |
speech
|
[
11.311359619397974,
8.742785253709748,
4.752787249246121
] |
large
| 0.71 | 16,000 | 2 | 6 |
[
[
3.4485489340806956,
4.371392626854874
],
[
6.062810685317278,
4.371392626854874
],
[
11.011359619397973,
4.371392626854874
]
] | 8 |
[
11.011359619397973,
4.371392626854874
] |
libri_3274
| 28 |
[
[
5.284946700419767,
1.8348442254508504,
1.368
],
[
3.986429324293185,
4.059099867666409,
1.302
],
[
6.529358429289928,
6.722530881080173,
1.396
],
[
1.9123009110022418,
3.3968726903110684,
1.204
],
[
6.223759747797927,
6.395256465185158,
1.201
],
[
6.327944345769049,
2.235054693285135,
1.35
],
[
7.141108996941081,
3.3965867538948284,
1.327
],
[
4.849993930632438,
5.350700085211462,
1.207
],
[
4.200608647590789,
8.117802662495789,
1.289
],
[
6.261403336213396,
4.279292119325427,
1.273
],
[
4.620329729586838,
4.49388238460737,
1.29
],
[
2.106168214082297,
2.9314490740467614,
1.245
],
[
3.9559094159506705,
5.531736739577353,
1.335
],
[
4.841820785752125,
4.096552917174275,
1.315
],
[
2.33972331054442,
5.108537471552788,
1.264
],
[
5.300447336358472,
4.697009629103692,
1.203
],
[
5.223866780764242,
0.8546896414375142,
1.238
],
[
3.278569465342996,
2.3080927400871936,
1.208
],
[
2.4733597105014336,
1.328320093397069,
1.293
],
[
3.1745124464823564,
7.076003010219573,
1.292
],
[
8.105335171235348,
4.79846605477611,
1.36
],
[
4.3349031851709885,
3.915961175918005,
1.325
],
[
3.8587673040549832,
6.397532890548576,
1.24
],
[
1.8562661399280942,
2.318123576371666,
1.368
],
[
1.3847461673639505,
3.8985568139128235,
1.227
],
[
1.9872361600974213,
5.192308866530981,
1.319
],
[
7.117910465090191,
3.7607547224722375,
1.229
]
] | 1.114246 | -5.473667 | 3 | 3 |
[
4.4686486024195045,
1.6898122065956045,
1.8163749468569201,
1.9807304511672084,
2.705109552110536,
2.5828760916684033,
1.191589409285572,
4.741434005872216,
4.6040905852509,
2.8653138867403993,
1.0949869115669273,
1.3706553500013308,
3.152699644078819,
1.2026216656715634,
4.231762439006929,
1.2201639326817775,
2.117688408904102,
3.1956259987879796,
1.9407234489960108,
2.4001779161151595,
2.5728963587334945,
1.5422725336374628,
2.4907560318529764,
1.908894377362111,
2.60845773866571,
4.303742895127922,
2.435962265865047,
2.3011436890944346,
4.391373468578145
] |
[
1.906310266520712,
1.9290772118368322,
2.177534802641514
] | 2,311.951 | 2,174.324 |
desk
|
[
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| 23 |
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| 14 |
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| 28 |
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| 15 |
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| 12 |
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| 11 |
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| 25 |
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| 26 |
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| 17 |
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aishell_1_0090
| 19 |
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libri_1547
| 18 |
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aishell_1_0012
| 18 |
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libri_331
| 19 |
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libri_1264
| 13 |
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speech
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aishell_1_0071
| 19 |
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libri_1154
| 11 |
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| 23 |
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| 13 |
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End of preview.
Dataset Card for Multi-Talker-SD
Dataset Description
Multi-Talker-SD is a large-scale bilingual (English–Mandarin) multi-speaker meeting dataset designed to support research on speaker diarization and meeting transcription.
- Size: 1,000 simulated meetings
- Participants per meeting: 10–30 speakers
- Average duration: ~20 minutes per meeting, up to one hour
- Languages: English, Mandarin (code-switching possible)
- Audio characteristics: realistic speaker overlap, turn-taking patterns, reverberation, and noise injection
- Metadata: speaker gender, language, session type, utterance timing
The audio is synthesized using utterances from AIShell-1 (Mandarin) and LibriSpeech (English), with added noise and reverberation to approximate real meeting conditions.
- Curated by: AISG Speech Lab
- License: Apache-2.0
Dataset Sources
- Repository: GitHub - Multi-Talker-SD
- Dataset on HF Hub: Multi-Talker-SD
Direct Use
- Research on speaker diarization under multilingual and overlapped speech conditions
- Meeting transcription in bilingual settings
- Controlled experiments on the effects of speaker metadata (gender, language, etc.)
- Training and evaluation of overlap-aware diarization models
Dataset Structure
- Audio files (.wav): multi-speaker simulated meetings
- RTTM files: diarization annotations with speaker labels and timestamps
- Metadata files: speaker profiles including gender, language, and session type
Each example contains:
- Meeting ID
- List of speakers (with attributes)
- Audio waveform
- RTTM segmentation
Dataset Creation
Source Data
- English speech: LibriSpeech
- Mandarin speech: AIShell-1
- Noise sources: point-source and diffuse-field noise corpora
- Processing: audio mixing, reverberation simulation, overlap control
Personal and Sensitive Information
No personally identifiable or sensitive data is included. All speech is sourced from public corpora.
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