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README.md

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 The available datasets are the CallHome (Japanese, Chinese, German, Spanish, English), AMI Corpus (English), Vox-Converse (English) and Simsamu (French). We aim to add more datasets in the future to better support speaker diarising on the Hub.
 
-- A collection of [five fine-tuned segmentation model](https://huggingface.co/collections/diarizers-community/models-66261d0f9277b825c807ff2a) baselines which are compatible with pyannote. 
+- A collection of multilingual [fine-tuned segmentation model](https://huggingface.co/collections/diarizers-community/models-66261d0f9277b825c807ff2a) baselines compatible with pyannote. 
 
-Each model has been fine-tuned on a specific Callhome language subset. They achieve better performances on multilingual data compared to pyannote's pre-trained [segmentation model](https://huggingface.co/pyannote/segmentation-3.0): 
+Each model has been fine-tuned on a specific Callhome language subset. They achieve better performances on multilingual data compared to pyannote's pre-trained [segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) model: 
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-** ADD BENCHMARK ** 
 
 Note: Results have been obtained using the [test script](https://github.com/kamilakesbi/diarizers/blob/main/test_segmentation.py) from diarizers.