The dataset viewer is not available for this subset.
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.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.
Uzbek Speech Corpus (USC)
Summary: This repository contains dataset for reproducing the results presented in the paper "USC: An Open-Source Uzbek Speech Corpus" (https://arxiv.org/abs/2107.14419). The Uzbek Speech Corpus (USC) is a freely available, manually checked speech corpus comprising 958 speakers and 105 hours of transcribed audio recordings. This is, to the best of the authors' knowledge, the first open-source Uzbek speech corpus dedicated to Automatic Speech Recognition (ASR). The repository provides pre-trained models and training recipes using both DNN-HMM and end-to-end (E2E) architectures, achieving promising word error rates (WER) of 18.1% and 17.4% on validation and test sets respectively. The code builds upon ESPnet.
Dataset Summary:
| Feature | Description |
|---|---|
| Language | Uzbek |
| Size | 105 hours of audio |
| Number of Speakers | 958 |
| Transcription | Manual, checked by native speakers |
| ASR Architectures | DNN-HMM and End-to-End (E2E) |
| WER (Validation) | 18.1% |
| WER (Test) | 17.4% |
Github Repository: https://github.com/IS2AI/Uzbek_ASR
Authors:
- Muhammadjon Musaev
- Saida Mussakhojayeva
- Ilyos Khujayorov
- Yerbolat Khassanov
- Mannon Ochilov
- Huseyin Atakan Varol
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