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README.md
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ECAPA2 is a hybrid neural network architecture and training strategy for generating robust speaker embeddings.
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The provided pre-trained model has an easy-to-use API to extract speaker embeddings and other hierarchical features. More information can be found in our original ECAPA2 paper.
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The speaker embeddings are recommended for tasks which rely directly on the identity of the speaker (e.g. speaker verification and speaker diarization).
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The hierarchical features are most useful for tasks capturing intra-speaker variance (e.g. emotion recognition and speaker profiling) and prove complimentary with the speaker embedding in our experience. See our speaker profiling paper for an example usage of the hierarchical features.
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/620f6a7d110b521c673c1914/cmd1Nvk6_WXInUKrjgXPj.png" width="300"/>
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ECAPA2 is a hybrid neural network architecture and training strategy for generating robust speaker embeddings.
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The provided pre-trained model has an easy-to-use API to extract speaker embeddings and other hierarchical features. More information can be found in our original ECAPA2 paper.
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The speaker embeddings are recommended for tasks which rely directly on the identity of the speaker (e.g. speaker verification and speaker diarization).
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The hierarchical features are most useful for tasks capturing intra-speaker variance (e.g. emotion recognition and speaker profiling) and prove complimentary with the speaker embedding in our experience. See our speaker profiling paper for an example usage of the hierarchical features.
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/620f6a7d110b521c673c1914/cmd1Nvk6_WXInUKrjgXPj.png" width="300"/>
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