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  ---
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- license: mit
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  language_creators:
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  - expert-generated
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  task_categories:
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  - text-generation
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  tags:
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- - code
 
 
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  pretty_name: Robust HyPoradise
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  size_categories:
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  - 10M<n<100M
 
 
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  ---
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- # HypothesesParadise
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- - This repo releases the Robust HyPoradise dataset in paper "Large Language Models are Efficient Learners of Noise-Robust Speech Recognition."
 
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- - If you consider this work would be related or useful for your research, please consider to cite the work in ICLR 2024. Thank you.
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  ```bib
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- @article{hu2024large,
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  title={Large Language Models are Efficient Learners of Noise-Robust Speech Recognition},
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- author={Hu, Yuchen and Chen, Chen and Yang, Chao-Han Huck and Li, Ruizhe and Zhang, Chao and Chen, Pin-Yu and Chng, EnSiong},
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- journal={Proc. ICLR},
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  year={2024}
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  }
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  ```
 
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  ---
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+ license: apache-2.0
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  language_creators:
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  - expert-generated
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  task_categories:
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  - text-generation
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  tags:
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+ - generative error correction
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+ - large language model
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+ - LLaMA
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  pretty_name: Robust HyPoradise
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  size_categories:
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  - 10M<n<100M
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+ language:
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+ - en
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  ---
 
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+ # HypothesesParadise
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+ This repo releases the Robust HyPoradise dataset in paper "Large Language Models are Efficient Learners of Noise-Robust Speech Recognition."
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+ If you consider this work would be related or useful for your research, please kindly consider to cite the work in ICLR 2024. Thank you.
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  ```bib
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+ @inproceedings{hu2024large,
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  title={Large Language Models are Efficient Learners of Noise-Robust Speech Recognition},
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+ author={Hu, Yuchen and Chen, Chen and Yang, Chao-Han Huck and Li, Ruizhe and Zhang, Chao and Chen, Pin-Yu and Chng, Eng Siong},
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+ booktitle={International Conference on Learning Representations},
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  year={2024}
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  }
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  ```