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Speaker Diarization On Nist Sre 2000

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DER(%)

Résultats

Résultats de performance de divers modèles sur ce benchmark

Paper Title
x-vector (PLDA + AHC)8.39TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context
TitaNet-L (NME-SC)6.73TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context
TitaNet-M (NME-SC)6.47TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context
TitaNet-S (NME-SC)6.37TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context
x-vector (MCGAN)5.73TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context
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Speaker Diarization On Nist Sre 2000 | SOTA | HyperAI