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README.md

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+---
+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}
+}
+```