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espnet
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mms_ulab_v2

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Audio Classification

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wanchichen commited on Jul 1

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@@ -4055,7 +4055,7 @@ It can be used for language identification, spoken language modelling, or speech
 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.
 For more details about the dataset and its usage, please refer to our [paper]().

 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](https://huggingface.co/espnet/xeus), a multilingual speech encoder for 4000+ languages.
 For more details about the dataset and its usage, please refer to our [paper]().