ESPnet
audio
self-supervised-learning
beats
jaeyeonkim99's picture
Upload README.md with huggingface_hub
2f73d42 verified
|
Raw
History Blame Contribute Delete
1.53 kB
---
tags:
- espnet
- audio
- self-supervised-learning
- beats
datasets:
- audioset
license: cc-by-4.0
arxiv: 2212.09058
---
# BEATs base encoder — AudioSet-2M, iteration 1
BEATs base audio encoder pre-trained on AudioSet-2M with ESPnet, reproducing
[BEATs](https://arxiv.org/abs/2212.09058) (Table 4). Iteration 1 is trained against the
discrete targets of the [iteration-1 VQ tokenizer](https://huggingface.co/jaeyeonkim99/BEATs-tokenizer-AS2M-iter1).
Produced by the [egs2/audioset/ssl1](https://github.com/espnet/espnet/tree/master/egs2/audioset/ssl1) recipe.
## Usage
Load into an ESPnet downstream classification recipe (e.g. `egs2/esc50/asr1`,
`egs2/as20k/cls1`) via `beats_ckpt_path`:
```yaml
encoder: beats
encoder_conf:
beats_ckpt_path: beats_encoder_iter1.pt
fbank_mean: 15.66439
fbank_std: 6.38312
```
## Downstream results
| | AS-20K test mAP | ESC-50 (5-fold acc) |
|---|---|---|
| iter 1 | 31.26 | 93.35 |
## Citation
```bibtex
@inproceedings{chen2022beats,
title={BEATs: Audio Pre-Training with Acoustic Tokenizers},
author={Chen, Sanyuan and Wu, Yu and Wang, Chengyi and Liu, Shujie and
Tompkins, Daniel and Chen, Zhuo and Wei, Furu},
booktitle={ICML}, year={2023}
}
@inproceedings{bharadwaj2025openbeats,
title={OpenBEATs: A Fully Open-Source General-Purpose Audio Encoder},
author={Bharadwaj, Shikhar and Cornell, Samuele and Choi, Kwanghee and
Fukayama, Satoru and Shim, Hye-jin and Deshmukh, Soham and Watanabe, Shinji},
booktitle={WASPAA}, year={2025}
}
```