Datasets:

syzym
/

xbmu_amdo31

Tasks:

Automatic Speech Recognition

Languages: tib

Multilinguality: monolingual

Size Categories: 10K<n<100K

Annotations Creators: expert-generated

License:

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Cannot get the config names for the dataset.

Error code:   ConfigNamesError
Exception:    FileNotFoundError
Message:      Couldn't find a dataset script at /src/services/worker/syzym/xbmu_amdo31/xbmu_amdo31.py or any data file in the same directory. Couldn't find 'syzym/xbmu_amdo31' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in syzym/xbmu_amdo31. 
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 55, in compute_config_names_response
                  for config in sorted(get_dataset_config_names(path=dataset, token=hf_token))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1508, in dataset_module_factory
                  raise FileNotFoundError(
              FileNotFoundError: Couldn't find a dataset script at /src/services/worker/syzym/xbmu_amdo31/xbmu_amdo31.py or any data file in the same directory. Couldn't find 'syzym/xbmu_amdo31' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in syzym/xbmu_amdo31.

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Dataset Card for [XBMU-AMDO31]

Dataset Summary

XBMU-AMDO31 dataset is a speech recognition corpus of Amdo Tibetan dialect. The open source corpus contains 31 hours of speech data and resources related to build speech recognition systems, including transcribed texts and a Tibetan pronunciation dictionary.

Supported Tasks and Leaderboards

automatic-speech-recognition: The dataset can be used to train a model for Amdo Tibetan Automatic Speech Recognition (ASR). It was recorded by 66 native speakers of Amdo Tibetan, and the recorded audio was processed and manually inspected. The most common evaluation metric is the word error rate (WER). The task has an active leaderboard which can be found at https://github.com/sendream/xbmu_amdo31#leaderboard and ranks models based on their WER.

Languages

XBMU-AMDO31 contains audio, a Tibetan pronunciation dictionary and transcription data in Amdo Tibetan.

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

The dataset has three splits: train, evaluation (dev) and test.Each speaker had approximately 450 sentences, with a small number of individuals having fewer than 200 sen