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.
Multilingual Speech Recognition for Turkic Languages
This Hugging Face dataset card summarizes the work presented in the paper "Multilingual Speech Recognition for Turkic Languages" (link). This repository provides pre-trained models and details regarding the training process for a multilingual Automatic Speech Recognition (ASR) system focused on Turkic languages. The models are trained on a combination of publicly available and custom-gathered datasets.
GitHub Repository: [Insert GitHub Repository Link Here]
Model Description
This work presents pre-trained multilingual ASR models capable of transcribing speech in several Turkic languages. Two models are available: one specifically trained on Turkic languages and a second trained on a broader set of languages (the exact composition of which is not specified in the provided text). These models utilize the ESPnet framework.
Pre-trained Models
| Model Name | Link |
|---|---|
| Turkic Languages Model | https://drive.google.com/file/d/1GtK-OrH3ZRYz2Zc8vf-xndp7R9dic4rV/view?usp=sharing |
| All Languages Model | https://drive.google.com/file/d/15Dc4Uwzqqrw3jkE5-zrgVAyNddGS7onw/view?usp=sharing |
Datasets
The models were trained using a combination of datasets. Specific details about data splits and preprocessing are not provided in the source material. The following datasets were utilized:
- KSC (link)
- TSC (link)
- USC (link)
- Common Voice 10.0 (for Azerbaijani, Bashkir, Chuvash, Kazakh, Kyrgyz, Sakha, Turkish, Tatar, Uzbek, and Uyghur)
The languages covered are Azerbaijani, Bashkir, Chuvash, Kazakh, Kyrgyz, Sakha, Turkish, Tatar, Uzbek, and Uyghur.
Citation
@Article{info14020074,
AUTHOR = {Mussakhojayeva, Saida and Dauletbek, Kaisar and Yeshpanov, Rustem and Varol, Huseyin Atakan},
TITLE = {Multilingual Speech Recognition for Turkic Languages},
JOURNAL = {Information},
VOLUME = {14},
YEAR = {2023},
NUMBER = {2},
ARTICLE-NUMBER = {74},
URL = {https://www.mdpi.com/2078-2489/14/2/74},
ISSN = {2078-2489}
}
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