Hyperbolic Softmax and HAM-Softmax in hyperbolic space reduce equal error rates by 27.84% and 14.23% on average versus standard Softmax and AM-Softmax by modeling hierarchical speaker features.
Overview of speaker modeling and its ap- plications: From the lens of deep speaker representation learn- ing
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Hyperbolic Additive Margin Softmax with Hierarchical Information for Speaker Verification
Hyperbolic Softmax and HAM-Softmax in hyperbolic space reduce equal error rates by 27.84% and 14.23% on average versus standard Softmax and AM-Softmax by modeling hierarchical speaker features.