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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.
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The speaker embeddings are recommended for tasks which rely directly on the speaker
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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.
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See the original ECAPA2 paper for more details about the architecture and employed training strategy.
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ECAPA2 is a hybrid neural network architecture and training strategy for generating robust speaker embeddings.
|
8 |
The provided pre-trained model has an easy-to-use API to extract speaker embeddings and other hierarchical features.
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9 |
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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.
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See the original ECAPA2 paper for more details about the architecture and employed training strategy.
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