license: apache-2.0
task_categories:
- translation
- automatic-speech-recognition
language:
- zh
- en
size_categories:
- 100K<n<1M
Attention2Probability: Attention-Driven Terminology Probability Estimation for Robust Speech-to-Text System
Attention2Probability (A2P) is a lightweight intervention scheme for speech terminology. The core approach is to use the cross-attention mechanism to retrieve the terms that may appear in the audio and add these terms to the prompt of the llm to complete the term intervention.
Data description
This project does not provide audio data for librispeech and aishell2. Please download them from other addresses. All the training data is provided in the data_json folder. The prefix path needs to be modified before use.
Training step
For English, the LibriSpeech dataset should first be utilized for pre-training. Subsequently, the second-stage training on LibriSpeech can be conducted by modifying the settings in the dataset configuration.
For Chinese, retrieving a single character in isolation lacks practical significance; thus, the Retriever can be directly trained using the Aishell-2 dataset. Finally, the models for both languages are fine-tuned on real-world data.
Citation
If you find A2P useful, please cite the paper:
@misc{du2025attention2probabilityattentiondriventerminologyprobability,
title={Attention2Probability: Attention-Driven Terminology Probability Estimation for Robust Speech-to-Text System},
author={Yanfan Du and Jun Zhang and Bin Wang and Jin Qiu and Lu Huang and Yuan Ge and Xiaoqian Liu and Tong Xiao and Jingbo Zhu},
year={2025},
eprint={2508.18701},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2508.18701},
}