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README.md

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 MMS ulab v2 is a a massively multilingual speech dataset that contains  **8900 hours** of unlabeled speech across **4023 languages**. In total, it contains 189 language families.
 It can be used for language identification, spoken language modelling, or speech representation learning.
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 MMS ulab v2 is a reproduced and extended version of the MMS ulab dataset originally proposed in [Scaling Speech Technology to 1000+ Languages](https://arxiv.org/abs/2305.13516), covering more languages and containing more data.
 This dataset includes the raw unsegmented audio in a 16kHz single channel format. It can be segmented into utterances with a voice activity detection (VAD) model such as [this one](https://github.com/wiseman/py-webrtcvad).
 We use 6700 hours of MMS ulab v2 (post-segmentation) to train [XEUS](), a multilingual speech encoder for 4000+ languages.