ESPnet
audio
self-supervised-learning
speech-recognition
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  [Paper](https://arxiv.org/abs/2309.15317)
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  This model was trained by [William Chen](https://wanchichen.github.io/) using ESPNet2's SSL recipe in [espnet](https://github.com/espnet/espnet/).
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- WavLabLM is an self-supervised audio encoder pre-trained on 40,000 hours of multilingual data across 136 languages. This specific variant, WavLabLM-MK, uses a K-means model trained on English data for the quantization, making it especially strong for European languages.
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  ```BibTex
 
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  [Paper](https://arxiv.org/abs/2309.15317)
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  This model was trained by [William Chen](https://wanchichen.github.io/) using ESPNet2's SSL recipe in [espnet](https://github.com/espnet/espnet/).
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+ WavLabLM is an self-supervised audio encoder pre-trained on 40,000 hours of multilingual data across 136 languages. This specific variant, WavLabLM-EK, uses a K-means model trained on English data for the quantization, making it especially strong for European languages.
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  ```BibTex