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  ### Dataset Summary
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- 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.
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  ### Supported Tasks and Leaderboards
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- 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.
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  ### Languages
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- XBMU-AMDO31 contains audio, a Tibetan pronunciation dictionary and transcription data in Amdo Tibetan.
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  ## Dataset Structure
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  ### Data Splits
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- 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
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- | Subset | Hours | Male | Female | Remarks |
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- | ------ | ----- | ---- | ------ | --------------------------------------- |
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- | Train | 25.41 | 27 | 27 | 18539 sentences recorded by 54 speakers |
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- | Dev | 2.81 | 2 | 4 | 2050 sentences recorded by 6 speakers |
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- | Test | 2.85 | 3 | 3 | 2041 sentences recorded by 6 speakers |
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  ## Dataset Creation
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  ### Licensing Information
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- This dataset is distributed under CC BY-SA 4.0.
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  ### Citation Information
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  ### Contributions
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- Thanks to [@speechless-z](https://github.com/speechless-z) for adding this dataset.
 
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  ### Dataset Summary
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+ [More Information Needed]
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  ### Supported Tasks and Leaderboards
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+ [More Information Needed]
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  ### Languages
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+ [More Information Needed]
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  ## Dataset Structure
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  ### Data Splits
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+ [More Information Needed]
 
 
 
 
 
 
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  ## Dataset Creation
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  ### Licensing Information
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+ [More Information Needed]
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  ### Citation Information
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  ### Contributions
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+ Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.