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 5 new columns ({'supervisions', 'start', 'recording', 'channel', 'duration'}) and 1 missing columns ({'tracks'}).
This happened while the json dataset builder was generating data using
gzip://lsheavymix_cuts_train_small_snr_aug_mono_rir.jsonl::hf://datasets/zrjin/LibriheavyMix-small@954c172930e38863cef97796443c56e3f3b170be/small-lhotse/lsheavymix_cuts_train_small_snr_aug_mono_rir.jsonl.gz
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 "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
id: string
start: double
duration: double
channel: int64
supervisions: list<item: struct<id: string, recording_id: string, start: double, duration: double, channel: int64, language: string, speaker: string, custom: struct<texts: list<item: string>, pre_texts: list<item: string>, begin_byte: int64, end_byte: int64>>>
child 0, item: struct<id: string, recording_id: string, start: double, duration: double, channel: int64, language: string, speaker: string, custom: struct<texts: list<item: string>, pre_texts: list<item: string>, begin_byte: int64, end_byte: int64>>
child 0, id: string
child 1, recording_id: string
child 2, start: double
child 3, duration: double
child 4, channel: int64
child 5, language: string
child 6, speaker: string
child 7, custom: struct<texts: list<item: string>, pre_texts: list<item: string>, begin_byte: int64, end_byte: int64>
child 0, texts: list<item: string>
child 0, item: string
child 1, pre_texts: list<item: string>
child 0, item: string
child 2, begin_byte: int64
child 3, end_byte: int64
recording: struct<id: string, sources: list<item: struct<type: string, channels: list<item: int64>, source: string>>, sampling_rate: int64, num_samples: int64, duration: double, channel_ids: list<item: int64>>
child 0, id: string
child 1, sources: list<item: struct<type: string, channels: list<item: int64>, source: string>>
child 0, item: struct<type: string, channels: list<item: int64>, source: string>
child 0, type: string
child 1, channels: list<item: int64>
child 0, item: int64
child 2, source: string
child 2, sampling_rate: int64
child 3, num_samples: int64
child 4, duration: double
child 5, channel_ids: list<item: int64>
child 0, item: int64
type: string
to
{'id': Value(dtype='string', id=None), 'tracks': [{'cut': {'id': Value(dtype='string', id=None), 'start': Value(dtype='float64', id=None), 'duration': Value(dtype='float64', id=None), 'channel': Value(dtype='int64', id=None), 'supervisions': [{'id': Value(dtype='string', id=None), 'recording_id': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'duration': Value(dtype='float64', id=None), 'channel': Value(dtype='int64', id=None), 'language': Value(dtype='string', id=None), 'speaker': Value(dtype='string', id=None), 'custom': {'texts': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'pre_texts': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'begin_byte': Value(dtype='int64', id=None), 'end_byte': Value(dtype='int64', id=None)}}], 'features': {'type': Value(dtype='string', id=None), 'num_frames': Value(dtype='int64', id=None), 'num_features': Value(dtype='int64', id=None), 'frame_shift': Value(dtype='float64', id=None), 'sampling_rate': Value(dtype='int64', id=None), 'start': Value(dtype='float64', id=None), 'duration': Value(dtype='float64', id=None), 'storage_type': Value(dtype='string', id=None), 'storage_path': Value(dtype='string', id=None), 'storage_key': Value(dtype='string', id=None), 'recording_id': Value(dtype='string', id=None), 'channels': Value(dtype='int64', id=None)}, 'recording': {'id': Value(dtype='string', id=None), 'sources': [{'type': Value(dtype='string', id=None), 'channels': Sequence(fea
...
Value(dtype='int64', id=None), 'num_features': Value(dtype='int64', id=None), 'frame_shift': Value(dtype='float64', id=None), 'sampling_rate': Value(dtype='int64', id=None), 'start': Value(dtype='float64', id=None), 'duration': Value(dtype='float64', id=None), 'storage_type': Value(dtype='string', id=None), 'storage_path': Value(dtype='string', id=None), 'storage_key': Value(dtype='string', id=None), 'recording_id': Value(dtype='string', id=None), 'channels': Value(dtype='int64', id=None)}, 'recording': {'id': Value(dtype='string', id=None), 'sources': [{'type': Value(dtype='string', id=None), 'channels': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), 'source': Value(dtype='string', id=None)}], 'sampling_rate': Value(dtype='int64', id=None), 'num_samples': Value(dtype='int64', id=None), 'duration': Value(dtype='float64', id=None), 'channel_ids': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)}, 'custom': {'text_path': Value(dtype='string', id=None)}, 'sampling_rate': Value(dtype='int64', id=None), 'feat_value': Value(dtype='float64', id=None), 'num_frames': Value(dtype='int64', id=None), 'num_features': Value(dtype='int64', id=None), 'frame_shift': Value(dtype='float64', id=None), 'num_samples': Value(dtype='int64', id=None)}, 'type': Value(dtype='string', id=None), 'offset': Value(dtype='float64', id=None)}]}, 'type': Value(dtype='string', id=None), 'offset': Value(dtype='float64', id=None)}], 'type': Value(dtype='string', id=None)}
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 1572, 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 1136, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, 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 2013, 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 ({'supervisions', 'start', 'recording', 'channel', 'duration'}) and 1 missing columns ({'tracks'}).
This happened while the json dataset builder was generating data using
gzip://lsheavymix_cuts_train_small_snr_aug_mono_rir.jsonl::hf://datasets/zrjin/LibriheavyMix-small@954c172930e38863cef97796443c56e3f3b170be/small-lhotse/lsheavymix_cuts_train_small_snr_aug_mono_rir.jsonl.gz
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.
id string | tracks list | type string |
|---|---|---|
510c8613-0aec-4cf7-9720-2f07a4f69e24 | [
{
"cut": {
"id": "small/3864/florida_sketchbook_0911_librivox_64kb_mp3/floridasketch_08_torrey_64kb_19_repeat0",
"start": 243.12,
"duration": 13.959,
"channel": 0,
"supervisions": [
{
"id": "small/3864/florida_sketchbook_0911_librivox_64kb_mp3/floridasketch_08_tor... | MixedCut |
d8c63a8e-f22e-42cd-89f6-72ab0aeeb724 | [
{
"cut": {
"id": "small/1085/book_1001_nights2_0908_librivox_64kb_mp3/thousand_nights_vol02_02_burton_64kb_22_repeat0",
"start": 891.84,
"duration": 6.399,
"channel": 0,
"supervisions": [
{
"id": "small/1085/book_1001_nights2_0908_librivox_64kb_mp3/thousand_nights... | MixedCut |
0bfed93d-1f2c-4b18-b5fa-285e48b7719c | [
{
"cut": {
"id": "small/1557/nippon_libriviox_64kb_mp3/nippon_noyes_ry_64kb_0_repeat0",
"start": 13.84,
"duration": 13.44,
"channel": 0,
"supervisions": [
{
"id": "small/1557/nippon_libriviox_64kb_mp3/nippon_noyes_ry_64kb_0",
"recording_id": "small/1557/... | MixedCut |
84e62f40-aa6a-4105-aee6-582d6846345b | [
{
"cut": {
"id": "small/3157/lincoln_story_book2_0902_librivox_64kb_mp3/lincolnstorybook_260_williams_64kb_7_repeat0",
"start": 90.4,
"duration": 14.799,
"channel": 0,
"supervisions": [
{
"id": "small/3157/lincoln_story_book2_0902_librivox_64kb_mp3/lincolnstoryboo... | MixedCut |
609fe9d5-ddf6-4935-ad48-83181a214a4f | [
{
"cut": {
"id": "small/1166/expedition_humphry_clinker_0908_librivox_64kb_mp3/expeditionofhumphryclinker_20_smollett_64kb_19_repeat0",
"start": 461.56,
"duration": 6.16,
"channel": 0,
"supervisions": [
{
"id": "small/1166/expedition_humphry_clinker_0908_librivox_... | MixedCut |
b6df2949-cc44-40d5-ad8f-10c69b0fb078 | [
{
"cut": {
"id": "small/4196/steep_trails_10-02_librivox_64kb_mp3/steeptrails_14_muir_64kb_11_repeat0",
"start": 92.8,
"duration": 14.519,
"channel": 0,
"supervisions": [
{
"id": "small/4196/steep_trails_10-02_librivox_64kb_mp3/steeptrails_14_muir_64kb_11",
... | MixedCut |
11299744-61cb-4f8a-b1be-38b046cf229d | [
{
"cut": {
"id": "small/4015/canadas_hundred_days_2_1002_librivox_64kb_mp3/canadashundreddays_2_04_livesay_64kb_10_repeat0",
"start": 613.28,
"duration": 13.159,
"channel": 0,
"supervisions": [
{
"id": "small/4015/canadas_hundred_days_2_1002_librivox_64kb_mp3/cana... | MixedCut |
d28ef642-b095-4da2-95e5-5763d995bd04 | [
{
"cut": {
"id": "small/205/short_story_008_64kb_mp3/country_life_in_canada_haight_ehl_64kb_11_repeat0",
"start": 304.88,
"duration": 13.199,
"channel": 0,
"supervisions": [
{
"id": "small/205/short_story_008_64kb_mp3/country_life_in_canada_haight_ehl_64kb_11",
... | MixedCut |
5e4ea168-623b-48a6-9092-3582c168c4fc | [
{
"cut": {
"id": "small/4443/commentary_galatians_1010_librivox_64kb_mp3/comment_galatians_13_luther_64kb_17_repeat0",
"start": 434.32,
"duration": 14.639,
"channel": 0,
"supervisions": [
{
"id": "small/4443/commentary_galatians_1010_librivox_64kb_mp3/comment_gala... | MixedCut |
c125a80d-ca71-40f5-87f7-7075292a31e6 | [
{
"cut": {
"id": "small/147/canterburytales_librivox_64kb_mp3/canterburytales_03_chaucer_64kb_15_repeat0",
"start": 189.36,
"duration": 5.6,
"channel": 0,
"supervisions": [
{
"id": "small/147/canterburytales_librivox_64kb_mp3/canterburytales_03_chaucer_64kb_15",
... | MixedCut |
4b3dd410-6549-4b8d-9e6c-db242931b8c4 | [
{
"cut": {
"id": "small/6965/toysofpeace_1204_librivox_64kb_mp3/toysofpeace_30_saki_64kb_9_repeat0",
"start": 73.48,
"duration": 13.399,
"channel": 0,
"supervisions": [
{
"id": "small/6965/toysofpeace_1204_librivox_64kb_mp3/toysofpeace_30_saki_64kb_9",
"... | MixedCut |
fbfb0f76-5515-4561-a2ab-f07288c507fd | [
{
"cut": {
"id": "small/618/shortpoetry_005_librivox_64kb_mp3/absolution_sassoon_wts_64kb_1_repeat0",
"start": 23.28,
"duration": 7.199,
"channel": 0,
"supervisions": [
{
"id": "small/618/shortpoetry_005_librivox_64kb_mp3/absolution_sassoon_wts_64kb_1",
... | MixedCut |
8fc90d4f-b094-4694-85df-dda17d1a25be | [
{
"cut": {
"id": "small/2784/short_poetry_067_librivox_64kb_mp3/mezzocammin_longfellow_aj_64kb_0_repeat0",
"start": 76.4,
"duration": 14.4,
"channel": 0,
"supervisions": [
{
"id": "small/2784/short_poetry_067_librivox_64kb_mp3/mezzocammin_longfellow_aj_64kb_0",
... | MixedCut |
1bd870b3-ce18-4baf-a34e-793ee9c401d8 | [
{
"cut": {
"id": "small/3157/commentary_galatians_1010_librivox_64kb_mp3/comment_galatians_19_luther_64kb_94_repeat0",
"start": 1462.64,
"duration": 9.64,
"channel": 0,
"supervisions": [
{
"id": "small/3157/commentary_galatians_1010_librivox_64kb_mp3/comment_galat... | MixedCut |
768b88a8-b9dd-4042-87e7-88a8e6a97bc4 | [
{
"cut": {
"id": "small/5192/tristramshandy4_1008_librivox_64kb_mp3/tristramshandy4_09_sterne_64kb_2_repeat0",
"start": 1048,
"duration": 7.959,
"channel": 0,
"supervisions": [
{
"id": "small/5192/tristramshandy4_1008_librivox_64kb_mp3/tristramshandy4_09_sterne_64... | MixedCut |
bf6d11b3-d363-4588-8803-0d660358eb93 | [
{
"cut": {
"id": "small/1472/stops_punctuate_0711_librivox_64kb_mp3/stops_05_allardyce_64kb_27_repeat0",
"start": 34.36,
"duration": 13.399,
"channel": 0,
"supervisions": [
{
"id": "small/1472/stops_punctuate_0711_librivox_64kb_mp3/stops_05_allardyce_64kb_27",
... | MixedCut |
End of preview.
No dataset card yet
- Downloads last month
- 10