Soundwave: Less is More for Speech-Text Alignment in LLMs
πββ¬ Github ο½ π Paperο½ πΌ Online Demo
Model Description
Soundwave is a Speech-to-Text model that bridges the gap between speech and text. It is trained on just 10k hours of data and delivers exceptional performance in speech translation and AIR-Bench speech tasks.
Key Features
- A Speech-to-Text Model Bridging the Gap Between Speech and Text
- Utilizes Data-Efficient Strategy and Unique Architecture, Trained on Only 10k Hours of Data
- Exceptional Performance in Speech Translation and AIR-Bench Speech Tasks
- Retains Intelligence During Conversations, Ideal for Interactive Tasks
Usage
Load the Soundwave model and run inference with your audio files as shown in the GitHub repository.
π Citation
@article{zhang2025soundwave,
title={Soundwave: Less is More for Speech-Text Alignment in LLMs},
author={Zhang, Yuhao and Liu, Zhiheng and Bu, Fan and Zhang, Ruiyu and Wang, Benyou and Li, Haizhou},
journal={arXiv preprint arXiv:2502.12900},
year={2025}
}
- Downloads last month
- 0
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no library tag.