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## WavLabLM-MS 40k
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## WavLabLM-MS 40k
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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-MS, went through a second stage of pre-training on a balanced subset of the data to improve performance on lower-resource languages.
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It achieves comparable performance to XLS-R 128 on the [ML-SUPERB Benchmark](https://arxiv.org/abs/2305.10615) with only 10% of the pre-training data.
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