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README.md

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-[diarizers-community](https://huggingface.co/diarizers-community) aims to promote speaker diarization on the Hugging Face hub. It comes with [diarizers](https://github.com/kamilakesbi/diarizers), a library for fine-tuning pyannote models that is compatible with the Hugging Face ecosystem.
+[diarizers-community](https://huggingface.co/diarizers-community) aims to promote speaker diarization on the Hugging Face hub. It comes with [diarizers](https://github.com/kamilakesbi/diarizers), a library for fine-tuning pyannote speaker diarzaition models that is compatible with the Hugging Face ecosystem.
 
-It hosts: 
+This organization contains: 
+
+- A collection of [multilingual speaker diarization datasets](https://huggingface.co/collections/diarizers-community/speaker-diarization-datasets-66261b8d571552066e003788) that are compatible with diarizers. They have been processed using [diarizers scripts](https://github.com/kamilakesbi/diarizers/blob/main/datasets/README.md).
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+The currently available datasets are the CallHome (Japanese, Chinese, German, Spanish, English), the AMI Corpus (English), Vox-Converse (English) and Simsamu (French). We aim at adding more datasets in the future to support speaker diarization on the Hub. 
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+- A collection of [5 fine-tuned segmentation model](https://huggingface.co/collections/diarizers-community/models-66261d0f9277b825c807ff2a) baselines that can be used in a pyannote speaker diarization pipeline.
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+- Each model has been fine-tuned on a specific language of the Callhome dataset. In comparison to the pretrained [pyannote segmentation model](https://huggingface.co/pyannote/segmentation-3.0), they reach better performance on each of the Callhome test sets:
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+** ADD BENCHMARK ** 
 
-- A collection of speaker diarization datasets that are compatible with diarizers. They have been generated using [diarizers scripts](https://github.com/kamilakesbi/diarizers/blob/main/datasets/README.md).  Each of these datasets comes with the following features: