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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/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 298, 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 80, 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 65, 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 352, in get_dataset_split_names
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 303, 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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Uzbek Automatic Speech Recognition (ASR) using the USC Corpus

This dataset card describes the Uzbek Speech Corpus (USC) and its associated Automatic Speech Recognition (ASR) system. This repository provides the code used in the paper "USC: An Open-Source Uzbek Speech Corpus". The ASR system is built upon ESPnet and Kaldi. Pre-trained models are available.

Repository: [Link to Hugging Face Repository (replace with actual link)]

Summary

This repository contains the code and recipes for training and using an Automatic Speech Recognition (ASR) system for the Uzbek language, utilizing the open-source Uzbek Speech Corpus (USC). The system is built upon the ESPnet framework and uses Kaldi for some functionalities. Pre-trained Conformer models are provided. The repository requires the prior installation of ESPnet and Kaldi.

Authors

  • Muhammadjon Musaev
  • Saida Mussakhojayeva
  • Ilyos Khujayorov
  • Yerbolat Khassanov
  • Mannon Ochilov
  • Huseyin Atakan Varol

Citation 

@article{musayev2021usc,
  title={USC: An Open-Source Uzbek Speech Corpus},
  author={Musaev, Muhammadjon and Mussakhojayeva, Saida and Khujayorov, Ilyos and Khassanov, Yerbolat and Ochilov, Mannon and Varol, Huseyin Atakan},
  journal={arXiv preprint arXiv:2107.14419},
  year={2021}
}

Related Projects and Libraries

Pre-trained Models

Pre-trained Conformer models are available. (Specific download location omitted as per instructions)

Data Splits

Information on data splits is available in the original paper and dataset itself (links omitted as per instructions)

Contact Information

(Contact information may be added here if available)

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