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Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError Message: The split names could not be parsed from the dataset config. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 153, in compute compute_split_names_from_info_response( File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 125, in compute_split_names_from_info_response config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config) File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise raise CachedArtifactError( libcommon.simple_cache.CachedArtifactError: The previous step failed. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, in get_dataset_config_info for split_generator in builder._split_generators( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 88, in _split_generators raise ValueError( ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types. 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/split_names.py", line 71, in compute_split_names_from_streaming_response for split in get_dataset_split_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 572, in get_dataset_split_names info = get_dataset_config_info( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, in get_dataset_config_info raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.
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Unsupervised malay speakers from youtube videos
10492 unique speakers with at least 75 hours of voice activities. Steps to reproduce at https://github.com/huseinzol05/malaya-speech/blob/master/data/youtube/process-youtube.ipynb
how-to
Download and extract processed-youtube.tar.gz, each processed videos saved as pickle,
{video_name}.pkl
.Each pickle file got,
[{'wav_data': '/home/husein/ssd2/processed-youtube-v2/"Abam_peluk_saya_lama_atas_pentas_akhir_MLM"-_Ali_Puteh_menangis_imbau_saat_manis_dengan_arwah_abang-_MdgGr7VD7w/0.mp3',
'timestamp': datetime.datetime(2023, 3, 2, 18, 45, 45, 778042),
'asr_model': ('kenapa tak mahu bangun kau abang',
[0.5325799628135358],
[309, 9, 399, 633, 108, 252]),
'classification_model': (array([ 3.02432757e-03, -3.64390127e-02, 2.93319039e-02, -2.84599233e-02,
-5.04244901e-02, 6.03185333e-02, 7.04260264e-03, 7.36895157e-03,
2.41034012e-02, -3.31214964e-02, -1.61228217e-02, -1.92081463e-02,
-1.77928973e-02, 1.05488757e-02, 5.11314301e-03, 2.08497643e-02,
2.80407351e-02, -1.34683009e-02, 1.10213496e-02, -5.76948654e-03,
2.11171638e-02, -3.10498872e-03, 1.60899870e-02, -2.22061612e-02,
-3.09270490e-02, 1.03673469e-02, 2.29822248e-02, 5.44358939e-02,
-9.44061391e-03, 3.24469656e-02, -1.40673192e-02, 6.55731931e-03,
1.94134321e-02, 2.31755860e-02, -8.62774719e-03, -3.72681394e-03,
-3.17485556e-02, -1.12474747e-02, 1.65595114e-02, 2.31244415e-02,
3.28784771e-02, 8.52510054e-03, -6.41896739e-04, 3.13562714e-03,
-3.15982029e-02, 1.72785181e-03, 1.58039071e-02, -9.93900001e-03,
2.03248486e-02, -2.98949536e-02, 3.53759155e-02, 3.06809470e-02,
-3.68881435e-03, -3.98267582e-02, -2.07101982e-02, 2.51877047e-02,
-2.51530181e-03, 1.06034977e-02, 1.24978041e-02, 2.35916697e-03,
1.31300613e-02, -1.62451845e-02, -2.09861826e-02, 3.17490734e-02,
-1.18532358e-02, 4.25735563e-02, 4.17908467e-02, 1.21251179e-03,
-3.85571155e-03, -9.50544327e-03, -7.37808086e-03, 2.63940021e-02,
1.09219365e-02, 3.05683501e-02, -4.08848785e-02, -1.71920974e-02,
-1.46033484e-02, -3.29053291e-05, 3.84788848e-02, -7.86552951e-03,
1.01251132e-03, 2.72140447e-02, 2.52339337e-02, 3.39004360e-02,
-1.38184745e-02, 2.60320995e-02, -1.01425601e-02, -1.16012329e-02,
4.30319924e-03, -1.01203052e-02, -4.66396799e-03, -2.64480542e-02,
3.44322808e-02, -4.64622118e-03, 1.06053520e-02, 1.37923108e-02,
-2.05409434e-03, -1.19995829e-02, 2.10450366e-02, -2.87155900e-03,
-1.39515549e-02, -1.51185887e-02, 2.29053162e-02, -1.78178120e-02,
1.95855577e-03, 2.37271357e-02, 2.80657201e-03, -6.08753460e-03,
-2.01220363e-02, 3.22612897e-02, 1.82474777e-02, 5.31493872e-02,
-7.08705634e-02, 2.76431069e-03, 1.03597697e-02, -3.53837833e-02,
1.38167264e-02, -5.91275143e-03, 1.84398554e-02, 6.05177172e-02,
1.14565976e-02, 1.56977493e-02, -1.82731878e-02, -4.58574407e-02,
-1.08330613e-02, -1.16500622e-02, -1.19803764e-04, 6.48374185e-02,
-1.21538760e-03, -5.41793741e-02, 1.38867721e-02, 3.52845751e-02,
-2.08288375e-02, 1.03750750e-02, -2.17110049e-02, 2.29265504e-02,
-1.21381739e-02, -1.47071329e-03, -4.36875001e-02, -2.25690063e-02,
-4.16939743e-02, -8.39853752e-03, -2.06098761e-02, 2.30504461e-02,
3.48615423e-02, -4.18495797e-02, -2.41985917e-03, -3.18994140e-03,
1.22078639e-02, -9.50168632e-03, -1.97298196e-03, 1.30731370e-02,
2.07234323e-02, 1.08521534e-02, 2.30542179e-02, -2.54045837e-02,
1.45645533e-02, -1.08493539e-02, -1.30415503e-02, 3.29123251e-02,
3.46204527e-02, 2.58748885e-04, -1.28235819e-03, -1.32823242e-02,
5.47284493e-03, -2.62062326e-02, 2.31803600e-02, -2.04505119e-02,
2.32407395e-02, 2.12946888e-02, -1.28869051e-02, -6.81399694e-03,
5.68802692e-02, 4.31004271e-04, 1.67261921e-02, 2.93559525e-02,
1.32581135e-02, -9.03073605e-03, -9.38207190e-03, 1.74718127e-02,
1.72506981e-02, 5.02267219e-02, -1.32851647e-02, 5.07321544e-02,
-1.87530685e-02, 4.18599546e-02, 1.50075918e-02, -2.61102356e-02,
-1.59594957e-02, 1.36823149e-03, -9.64679196e-03, 1.71130225e-02],
dtype=float32),
'speaker 0')}]
- all mp3 files postprocessing using https://malaya-speech.readthedocs.io/en/latest/load-noise-reduction.html and https://malaya-speech.readthedocs.io/en/latest/load-speech-enhancement.html
wav_data
is directory of the audio, prune the path to proper extracted directory.asr_model
is predicted using the best model that we have,conformer-medium
, returned(text, probability, subwords)
, https://malaya-speech.readthedocs.io/en/latest/load-stt-transducer-model-pt.htmlclassification_model
is predicted using NEMO TITANET Large speaker verification model, https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/titanet_large, with streaming speaker similarity, https://malaya-speech.readthedocs.io/en/latest/huggingface-repository.html
- Group by similar speakers using pagerank method (scipy.sparse.linalg.gmres),
- 90% similar, from 10492 unique speakers become 6085 unique speakers, https://github.com/huseinzol05/malaya-speech/blob/master/data/youtube/mapping-youtube-speakers-90.json
- 85% similar, from 10492 unique speakers become 4312 unique speakers, https://github.com/huseinzol05/malaya-speech/blob/master/data/youtube/mapping-youtube-speakers-85.json
- 80% similar, from 10492 unique speakers become 2912 unique speakers, https://github.com/huseinzol05/malaya-speech/blob/master/data/youtube/mapping-youtube-speakers-80.json
Speaker name defined as,
import os
import pickle
pkl = 'filename.pkl'
with open(pkl, 'rb') as fopen:
data = pickle.load(fopen)
filename = os.path.split(pkl)[1].replace('.pkl', '')
for result in data:
speaker_name = f'{filename}-{speaker}'
actual_speaker = unique_speakers[speaker_name]
Check example at https://github.com/huseinzol05/malaya-speech/blob/master/data/youtube/calculate-lengths-80.ipynb
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