metadata
license: apache-2.0
language:
- en
pipeline_tag: text-generation
inference: false
fine-tuning: true
tags:
- generative error correction
- large language model
- LLaMA
metrics:
- wer
datasets:
- PeacefulData/Robust-HyPoradise
This repo releases the trained LLaMA-adapter weights in paper "Large Language Models are Efficient Learners of Noise-Robust Speech Recognition."
GitHub: https://github.com/YUCHEN005/RobustGER
Data: https://huggingface.co/datasets/PeacefulData/Robust-HyPoradise
Model: This repo
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.
@inproceedings{hu2024large,
title={Large Language Models are Efficient Learners of Noise-Robust Speech Recognition},
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},
booktitle={International Conference on Learning Representations},
year={2024}
}