speechbrain
/

REAL-M-sisnr-estimator

audio-source-separation

Source Separation

Speech Separation

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Mirco commited on Oct 20, 2021

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8708c6a

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1 Parent(s): 122a916

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@@ -74,11 +74,12 @@ from speechbrain.pretrained import SepformerSeparation as separator
 from speechbrain.pretrained.interfaces import SNREstimator as snrest
 import torchaudio
 model = separator.from_hparams(source="speechbrain/sepformer-whamr", savedir='pretrained_models/sepformer-whamr2')
 est_sources = model.separate_file(path='speechbrain/sepformer-wsj02mix/test_mixture.wav')
-snr_est_model = snrest.from_hparams(source="speechbrain/REAL-M-sisnr-estimator-main")
 mix, fs = torchaudio.load('test_mixture.wav')
 snrhat = snr_est_model.estimate_batch(mix, est_sources)

 from speechbrain.pretrained.interfaces import SNREstimator as snrest
 import torchaudio
+# 1- Separate the mixture with a pretrained model (sepformer-whamr in this case)
 model = separator.from_hparams(source="speechbrain/sepformer-whamr", savedir='pretrained_models/sepformer-whamr2')
 est_sources = model.separate_file(path='speechbrain/sepformer-wsj02mix/test_mixture.wav')
+# 2- Estimate the performance
+snr_est_model = snrest.from_hparams(source="speechbrain/REAL-M-sisnr-estimator",savedir='pretrained_models/REAL-M-sisnr-estimator')
 mix, fs = torchaudio.load('test_mixture.wav')
 snrhat = snr_est_model.estimate_batch(mix, est_sources)