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SOTA
Speech Separation
Speech Separation On Whamr
Speech Separation On Whamr
Metrics
SI-SDRi
Results
Performance results of various models on this benchmark
Columns
Model Name
SI-SDRi
Paper Title
TF-Locoformer (M)
18.5
TF-Locoformer: Transformer with Local Modeling by Convolution for Speech Separation and Enhancement
TF-Locoformer (S)
17.4
TF-Locoformer: Transformer with Local Modeling by Convolution for Speech Separation and Enhancement
SepReformer-L + DM
17.1
Separate and Reconstruct: Asymmetric Encoder-Decoder for Speech Separation
MossFormer2
17.0
MossFormer2: Combining Transformer and RNN-Free Recurrent Network for Enhanced Time-Domain Monaural Speech Separation
MossFormer (L) + DM
16.3
MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions
TD-Conformer (XL) + DM
14.6
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Improved Sudo rm -rf (U=36)
13.5
Compute and memory efficient universal sound source separation
TD-Conformer (L) + DM
13.4
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Wavesplit
13.2
Wavesplit: End-to-End Speech Separation by Speaker Clustering
DPTNET - SRSSN
12.3
Stepwise-Refining Speech Separation Network via Fine-Grained Encoding in High-order Latent Domain
DPRNN - SRSSN
12.3
Stepwise-Refining Speech Separation Network via Fine-Grained Encoding in High-order Latent Domain
VSUNOS
12.2
Voice Separation with an Unknown Number of Multiple Speakers
Sudo rm -rf (U=16)
12.1
Sudo rm -rf: Efficient Networks for Universal Audio Source Separation
TD-Confomer (M) + DM
12
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Deformable TCN + Dynamic Mixing
11.1
Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation
TD-Confomer (S)
10.5
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Deformable TCN + Shared Weights + Dynamic Mixing
10.1
Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation
Bi-LSTM-TASNET
9.2
WHAM!: Extending Speech Separation to Noisy Environments
0 of 18 row(s) selected.
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HyperAI
HyperAI
Home
Console
Docs
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Papers
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Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Speech Separation
Speech Separation On Whamr
Speech Separation On Whamr
Metrics
SI-SDRi
Results
Performance results of various models on this benchmark
Columns
Model Name
SI-SDRi
Paper Title
TF-Locoformer (M)
18.5
TF-Locoformer: Transformer with Local Modeling by Convolution for Speech Separation and Enhancement
TF-Locoformer (S)
17.4
TF-Locoformer: Transformer with Local Modeling by Convolution for Speech Separation and Enhancement
SepReformer-L + DM
17.1
Separate and Reconstruct: Asymmetric Encoder-Decoder for Speech Separation
MossFormer2
17.0
MossFormer2: Combining Transformer and RNN-Free Recurrent Network for Enhanced Time-Domain Monaural Speech Separation
MossFormer (L) + DM
16.3
MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions
TD-Conformer (XL) + DM
14.6
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Improved Sudo rm -rf (U=36)
13.5
Compute and memory efficient universal sound source separation
TD-Conformer (L) + DM
13.4
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Wavesplit
13.2
Wavesplit: End-to-End Speech Separation by Speaker Clustering
DPTNET - SRSSN
12.3
Stepwise-Refining Speech Separation Network via Fine-Grained Encoding in High-order Latent Domain
DPRNN - SRSSN
12.3
Stepwise-Refining Speech Separation Network via Fine-Grained Encoding in High-order Latent Domain
VSUNOS
12.2
Voice Separation with an Unknown Number of Multiple Speakers
Sudo rm -rf (U=16)
12.1
Sudo rm -rf: Efficient Networks for Universal Audio Source Separation
TD-Confomer (M) + DM
12
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Deformable TCN + Dynamic Mixing
11.1
Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation
TD-Confomer (S)
10.5
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Deformable TCN + Shared Weights + Dynamic Mixing
10.1
Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation
Bi-LSTM-TASNET
9.2
WHAM!: Extending Speech Separation to Noisy Environments
0 of 18 row(s) selected.
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