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# LAU eval dataset
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This dataset was created while evaluating and comparing the models trained with Listen Attend Understand regularization and our [E2E-ST model](https://huggingface.co/
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The audio is from jeli-asr test set; the regularization loss weight lambda in the paper is represented by the character "k" in the fields of this dataset, each field represent a model with a specific decoding strategy (CTC or TDT)
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---
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## Citation
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```bibtex
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@misc{diarra2025lau,
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title={Listen, Attend, Understand: a Regularization Technique for stable E2E Speech Translation training on High Variance labels},
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author={Diarra, Yacouba and Leventhal, Michael},
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year={2025},
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eprint={2512.XXXXX},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2512.XXXXX},
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}
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```
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# LAU eval dataset
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This dataset was created while evaluating and comparing the models trained with Listen Attend Understand regularization and our [E2E-ST model](https://huggingface.co/anonymousnowhere/st-soloni-114m-tdt-ctc).
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The audio is from jeli-asr test set; the regularization loss weight lambda in the paper is represented by the character "k" in the fields of this dataset, each field represent a model with a specific decoding strategy (CTC or TDT)
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