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Speech Separation On Wsj0 3Mix

Métriques

SI-SDRi

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
SI-SDRi
Paper TitleRepository
Gated DualPathRNN16.85Voice Separation with an Unknown Number of Multiple Speakers-
Sandglasset17.1Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation-
MossFormer (M) + DM20.8MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions-
MossFormer (L) + DM21.2MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions-
SepTDA23.7Boosting Unknown-number Speaker Separation with Transformer Decoder-based Attractor-
Separate And Diffuse20.9Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation-
MossFormer222.2MossFormer2: Combining Transformer and RNN-Free Recurrent Network for Enhanced Time-Domain Monaural Speech Separation-
SepIt20.1SepIt: Approaching a Single Channel Speech Separation Bound-
SepFormer19.5Attention is All You Need in Speech Separation-
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Speech Separation On Wsj0 3Mix | SOTA | HyperAI