Speech Enhancement On Deep Noise Suppression
المقاييس
PESQ-WB
SI-SDR-WB
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
اسم النموذج | PESQ-WB | SI-SDR-WB |
---|---|---|
high-fidelity-speech-enhancement-with-band | 3.42 | 21.3 |
النموذج 2 | 1.58 | 9.1 |
remixit-continual-self-training-of-speech | 2.34 | 16.0 |
interactive-speech-and-noise-modeling-for-1 | - | - |
remixit-continual-self-training-of-speech | 2.95 | 19.7 |
النموذج 6 | 3.69 | 21.15 |
raw-speech-enhancement-with-deep-state-space | 2.98 | - |
high-fidelity-speech-enhancement-with-band | - | 21.4 |
real-time-monaural-speech-enhancement-with | 2.77 | - |
a-mask-free-neural-network-for-monaural | 3.43 | 20.31 |
high-fidelity-speech-enhancement-with-band | 3.45 | 21.1 |
النموذج 12 | 3.81 | 22.22 |
real-time-monaural-speech-enhancement-with | 2.82 | - |
tf-locoformer-transformer-with-local-modeling | 3.72 | 23.3 |
dccrn-deep-complex-convolution-recurrent-1 | - | - |
monaural-speech-enhancement-with-complex | 3.23 | - |
dual-signal-transformation-lstm-network-for | - | 16.34 |
fullsubnet-channel-attention-fullsubnet-with | 3.218 | 16.81 |
real-time-monaural-speech-enhancement-with | 2.82 | - |
continual-self-training-with-bootstrapped | 2.69 | 18.6 |
fullsubnet-a-full-band-and-sub-band-fusion | 2.777 | 17.29 |
real-time-monaural-speech-enhancement-with | 2.79 | - |
high-fidelity-speech-enhancement-with-band | 3.32 | - |
a-modulation-domain-loss-for-neural-network-1 | 2.75 | - |
cleanunet-2-a-hybrid-speech-denoising-model | 3.262 | - |
high-fidelity-speech-enhancement-with-band | 3.53 | 21.4 |
continual-self-training-with-bootstrapped | 2.60 | 18.0 |
speech-denoising-in-the-waveform-domain-with | 3.146 | - |
dccrn-deep-complex-convolution-recurrent-1 | - | - |
weighted-speech-distortion-losses-for-neural-1 | 2.65 | - |
phase-aware-single-stage-speech-denoising-and-1 | - | 16.22 |
exploring-the-best-loss-function-for-dnn-1 | 2.73 | - |
poconet-better-speech-enhancement-with | 2.7885 | - |
explicit-estimation-of-magnitude-and-phase | 3.62 | 21.03 |